feat: chatbot e prompts exernos em arquivos

ChatHistoryService.cs

@@ -29,7 +29,7 @@ namespace ChatApi
             }
         }
 
-        public ChatHistory GetSumarizer(string sessionId)
+        public ChatHistory GetSumarizer(string sessionId, string language = "en")
         {
             if (_keyValues.ContainsKey(sessionId))
             {
@@ -39,7 +39,12 @@ namespace ChatApi
             else
             {
                 var msg = new List<ChatMessageContent>();
-                PromptLiliana(msg);
+
+                if (language == "pt")
+                    PromptPt(msg);
+                else
+                    PromptEn(msg);
+
                 string json = JsonSerializer.Serialize(msg);
                 var history = new ChatHistory(JsonSerializer.Deserialize<List<ChatMessageContent>>(json));
                 _keyValues[sessionId] = history;
@@ -58,5 +63,25 @@ namespace ChatApi
             msg.Add(new ChatMessageContent(AuthorRole.System, "Você responde sempre em português do Brasil e fala sobre detalhes de projeto, arquitetura e criação de casos de teste."));
             msg.Add(new ChatMessageContent(AuthorRole.User, "Use sempre portugues do Brasil."));
         }
+
+        public void PromptEn(List<ChatMessageContent> msg)
+        {
+            msg.Add(new ChatMessageContent(AuthorRole.System, "You are an expert software analyst and QA professional."));
+            msg.Add(new ChatMessageContent(AuthorRole.System, "Please provide a comprehensive response in English (US). Consider the project context and requirements above to generate accurate and relevant information."));
+            msg.Add(new ChatMessageContent(AuthorRole.System, "If you have test case requests: Use Gherkin format (Given-When-Then) with realistic scenarios covering happy path, edge cases, and error handling."));
+            msg.Add(new ChatMessageContent(AuthorRole.System, "If you have project summaries: Include objectives, key features, technologies, and main challenges."));
+            msg.Add(new ChatMessageContent(AuthorRole.System, "If you have a task list request for one developer: Organize tasks by priority and estimated effort for a single developer, including technical dependencies."));
+            //msg.Add(new ChatMessageContent(AuthorRole.User, "Use sempre portugues do Brasil."));
+        }
+
+        public void PromptPt(List<ChatMessageContent> msg)
+        {
+            msg.Add(new ChatMessageContent(AuthorRole.System, "Você é um analista de software especialista e profissional de QA."));
+            msg.Add(new ChatMessageContent(AuthorRole.System, "Por favor, forneça uma resposta abrangente em português do Brasil. Considere o contexto do projeto e os requisitos acima para gerar informações precisas e relevantes."));
+            msg.Add(new ChatMessageContent(AuthorRole.System, "Se forem solicitados casos de teste: Use o formato Gherkin (Dado-Quando-Então) com cenários realistas cobrindo caminho feliz, casos extremos e tratamento de erros."));
+            msg.Add(new ChatMessageContent(AuthorRole.System, "Se for solicitado um resumo do projeto: Inclua objetivos, principais funcionalidades, tecnologias e principais desafios."));
+            msg.Add(new ChatMessageContent(AuthorRole.System, "Se for uma solicitação de lista de tarefas para um(ou mais) desenvolvedor(es): Organize as tarefas por prioridade e esforço estimado para um único desenvolvedor, incluindo dependências técnicas."));
+            //msg.Add(new ChatMessageContent(AuthorRole.User, "Use sempre português do Brasil."));
+        }
     }
 }

ChatRAG.csproj

@@ -26,6 +26,7 @@
     <PackageReference Include="MongoDB.Driver" Version="3.0.0" />
     <PackageReference Include="MongoDB.Driver.Core" Version="2.30.0" />
     <PackageReference Include="Newtonsoft.Json" Version="13.0.3" />
+    <PackageReference Include="Qdrant.Client" Version="1.14.0" />
     <PackageReference Include="Swashbuckle.AspNetCore" Version="6.6.2" />
     <PackageReference Include="System.IdentityModel.Tokens.Jwt" Version="8.2.1" />
   </ItemGroup>

ChatRAG.csproj.user

@@ -2,8 +2,8 @@
 <Project ToolsVersion="Current" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <PropertyGroup>
     <ActiveDebugProfile>http</ActiveDebugProfile>
-    <Controller_SelectedScaffolderID>ApiControllerEmptyScaffolder</Controller_SelectedScaffolderID>
-    <Controller_SelectedScaffolderCategoryPath>root/Common/Api</Controller_SelectedScaffolderCategoryPath>
+    <Controller_SelectedScaffolderID>MvcControllerEmptyScaffolder</Controller_SelectedScaffolderID>
+    <Controller_SelectedScaffolderCategoryPath>root/Common/MVC/Controller</Controller_SelectedScaffolderCategoryPath>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">
     <DebuggerFlavor>ProjectDebugger</DebuggerFlavor>

Configuration/Prompts/Domains/Financeiro.json

@@ -0,0 +1,11 @@
+{
+  "Name": "Financeiro",
+  "Description": "Configurações para projetos financeiros e contábeis",
+  "Keywords": [ "financeiro", "contábil", "faturamento", "cobrança", "pagamento", "receita", "despesa" ],
+  "Concepts": [ "fluxo de caixa", "conciliação", "relatórios financeiros", "impostos", "audit trail" ],
+  "Prompts": {
+    "pt": {
+      "Response": "Você é um especialista em sistemas financeiros e contabilidade.\n\nSISTEMA FINANCEIRO: {0}\nPERGUNTA: \"{1}\"\nCONTEXTO FINANCEIRO: {2}\nANÁLISE REALIZADA: {3}\n\nResponda considerando:\n- Controles financeiros\n- Auditoria e compliance\n- Fluxos de aprovação\n- Relatórios gerenciais\n- Segurança de dados financeiros\n\nSeja preciso e considere aspectos regulatórios."
+    }
+  }
+}

Configuration/Prompts/Domains/QA.json

@@ -0,0 +1,11 @@
+{
+  "Name": "Quality Assurance",
+  "Description": "Configurações para projetos de QA e testes",
+  "Keywords": [ "teste", "qa", "qualidade", "bug", "defeito", "validação", "verificação" ],
+  "Concepts": [ "test cases", "automation", "regression", "performance", "security testing" ],
+  "Prompts": {
+    "pt": {
+      "Response": "Você é um especialista em Quality Assurance e testes de software.\n\nPROJETO: {0}\nPERGUNTA DE QA: \"{1}\"\nCONTEXTO DE TESTES: {2}\nANÁLISE EXECUTADA: {3}\n\nResponda com foco em:\n- Estratégias de teste\n- Casos de teste específicos\n- Automação e ferramentas\n- Critérios de aceitação\n- Cobertura de testes\n\nSeja detalhado e metodológico na abordagem."
+    }
+  }
+}

Configuration/Prompts/Domains/RH.json

@@ -0,0 +1,11 @@
+{
+  "Name": "Recursos Humanos",
+  "Description": "Configurações para projetos de RH e gestão de pessoas",
+  "Keywords": [ "funcionário", "colaborador", "cargo", "departamento", "folha", "benefícios", "treinamento" ],
+  "Concepts": [ "gestão de pessoas", "recrutamento", "seleção", "avaliação", "desenvolvimento" ],
+  "Prompts": {
+    "pt": {
+      "Response": "Você é um especialista em Recursos Humanos e gestão de pessoas.\n\nSISTEMA DE RH: {0}\nPERGUNTA: \"{1}\"\nCONTEXTO: {2}\nPROCESSOS ANALISADOS: {3}\n\nResponda considerando:\n- Políticas de RH\n- Fluxos de trabalho\n- Compliance e regulamentações\n- Melhores práticas em gestão de pessoas\n\nSeja claro e prático nas recomendações."
+    }
+  }
+}

Configuration/Prompts/Domains/Servicos.json

@@ -0,0 +1,74 @@
+{
+  "Name": "Serviços JobMaker",
+  "Description": "Chatbot especializado em serviços de RAG, IA empresarial e desenvolvimento da JobMaker",
+  "Keywords": [
+    "rag",
+    "retrieval augmented generation",
+    "semantic kernel",
+    "chatbot",
+    "ia",
+    "inteligencia artificial",
+    "desenvolvimento",
+    "consultoria",
+    "c#",
+    "dotnet",
+    ".net",
+    "python",
+    "migracao",
+    "sistema",
+    "sap",
+    "salesforce",
+    "integracao",
+    "web scraping",
+    "rpa",
+    "etl",
+    "mongodb",
+    "qdrant",
+    "workshop",
+    "treinamento",
+    "poc",
+    "prova conceito",
+    "enterprise",
+    "corporativo",
+    "automacao",
+    "performance",
+    "otimizacao",
+    "suporte",
+    "preço",
+    "valor",
+    "custo",
+    "orçamento",
+    "quanto custa",
+    "prazo",
+    "tempo",
+    "entrega",
+    "projeto",
+    "solução"
+  ],
+  "Concepts": [
+    "retrieval augmented generation",
+    "microsoft semantic kernel",
+    "chatbot empresarial",
+    "inteligencia artificial conversacional",
+    "migracao python para c#",
+    "integracao sap salesforce",
+    "web scraping rpa",
+    "etl sincronizacao dados",
+    "arquitetura enterprise",
+    "sistemas escaláveis",
+    "poc prova conceito",
+    "consultoria ia empresarial",
+    "apresentação",
+    "boas vindas",
+    "consultoria",
+    "agendamento"
+  ],
+  "Prompts": {
+    "pt": {
+      "Response": "Você é um assistente virtual especializado nos serviços da JobMaker, empresa líder em RAG (Retrieval-Augmented Generation) e IA empresarial. Você atende chamadas via chat e responde com cordialidade\n\n🏢 EMPRESA: {0}\n❓ PERGUNTA DO CLIENTE: \"{1}\"\n📊 INFORMAÇÕES DISPONÍVEIS: {2}\n\nResponda de forma:\n✅ **Profissional e técnica** (mas acessível)\n✅ ***Se a pergunta for técnica ou envolver algum termo técnico***\n **Específica sobre nossos serviços**\n✅ **Highlighting nossos diferenciais**: C#/.NET, Semantic Kernel, economia 40-60%, performance 3-5x\n✅ **Incentivando contato** para demonstração ou consultoria\n\n\n- Call-to-action(não adicionar na resposta) para demo/consultoria\n\n⚠️ **Se não tiver informação suficiente:** Seja honesto, destaque que temos expertise em RAG/IA empresarial e ofereça consultoria personalizada."
+    },
+    "en": {
+      "Response": "You are a virtual assistant specialized in JobMaker services, leading company in RAG (Retrieval-Augmented Generation) and enterprise AI.\n\n🏢 COMPANY: {0}\n❓ CUSTOMER QUESTION: \"{1}\"\n📊 AVAILABLE INFORMATION: {2}\n\nRespond in a:\n✅ **Professional and technical** (but accessible) manner\n✅ **Specific about our services**\n✅ **Highlighting our differentiators**: C#/.NET, Semantic Kernel, 40-60% savings, 3-5x performance\n✅ **Encouraging contact** for demonstration or consultation\n\n💡 **Always include:**\n- Concrete benefits (savings, performance)\n- Technologies used\n- Estimated timeline when relevant\n- Call-to-action(do not add to response) for demo/consultation\n\n⚠️ **If insufficient information:** Be honest, highlight our RAG/enterprise AI expertise and offer personalized consultation."
+    }
+  }
+}

Configuration/Prompts/Domains/TI.json

@@ -0,0 +1,11 @@
+{
+  "Name": "Tecnologia da Informação",
+  "Description": "Configurações para projetos de TI e desenvolvimento de software",
+  "Keywords": [ "api", "backend", "frontend", "database", "arquitetura", "código", "classe", "método", "endpoint" ],
+  "Concepts": [ "mvc", "rest", "microservices", "clean architecture", "design patterns", "authentication", "authorization" ],
+  "Prompts": {
+    "pt": {
+      "Response": "Você é um especialista em desenvolvimento de software e arquitetura de sistemas.\n\nPROJETO: {0}\nPERGUNTA TÉCNICA: \"{1}\"\nCONTEXTO TÉCNICO: {2}\nANÁLISE REALIZADA: {3}\n\nResponda com foco técnico, incluindo:\n- Implementação prática\n- Boas práticas de código\n- Considerações de arquitetura\n- Exemplos de código quando relevante\n\nSeja preciso e técnico na resposta."
+    }
+  }
+}

Configuration/Prompts/base-prompts.json

@@ -0,0 +1,18 @@
+{
+  "Prompts": {
+    "pt": {
+      "QueryAnalysis": "Analise esta pergunta e classifique com precisão:\nPERGUNTA: \"{0}\"\n\nResponda APENAS no formato JSON:\n{{\n    \"strategy\": \"overview|specific|detailed\",\n    \"complexity\": \"simple|medium|complex\",\n    \"scope\": \"global|filtered|targeted\",\n    \"concepts\": [\"conceito1\", \"conceito2\"],\n    \"needs_hierarchy\": true|false\n}}",
+
+      "Response": "Você é um especialista em análise de software e QA.\n\nPROJETO: {0}\nPERGUNTA: \"{1}\"\nCONTEXTO HIERÁRQUICO: {2}\nETAPAS EXECUTADAS: {3}\n\nResponda à pergunta de forma precisa e estruturada, aproveitando todo o contexto hierárquico coletado.",
+
+      "Summary": "Resuma os pontos principais destes documentos sobre {0}:\n\n{1}\n\nResponda apenas com uma lista concisa dos pontos mais importantes:",
+
+      "GapAnalysis": "Baseado na pergunta e contexto atual, identifique que informações ainda faltam para uma resposta completa.\n\nPERGUNTA: {0}\nCONTEXTO ATUAL: {1}\n\nResponda APENAS com palavras-chave dos conceitos/informações que ainda faltam, separados por vírgula.\nSe o contexto for suficiente, responda 'SUFICIENTE'."
+    },
+    "en": {
+      "QueryAnalysis": "Analyze this question and classify precisely:\nQUESTION: \"{0}\"\n\nAnswer ONLY in JSON format:\n{{\n    \"strategy\": \"overview|specific|detailed\",\n    \"complexity\": \"simple|medium|complex\",\n    \"scope\": \"global|filtered|targeted\",\n    \"concepts\": [\"concept1\", \"concept2\"],\n    \"needs_hierarchy\": true|false\n}}",
+
+      "Response": "You are a software analysis and QA expert.\n\nPROJECT: {0}\nQUESTION: \"{1}\"\nHIERARCHICAL CONTEXT: {2}\nEXECUTED STEPS: {3}\n\nAnswer the question precisely and structured, leveraging all the hierarchical context collected."
+    }
+  }
+}

Controllers/ChatController.cs

@@ -7,6 +7,7 @@ using ChatRAG.Data;
 using ChatRAG.Models;
 using ChatRAG.Requests;
 using BlazMapper;
+using ChatRAG.Services.Contracts;
 
 #pragma warning disable SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
 
@@ -20,29 +21,29 @@ namespace ChatApi.Controllers
         private readonly IResponseService _responseService;
         private readonly TextFilter _textFilter;
         private readonly UserDataRepository _userDataRepository;
-        private readonly ProjectDataRepository _projectDataRepository;        
-        private readonly TextData _textData;
+        private readonly IProjectDataRepository _projectDataRepository;        
+        private readonly ITextDataService _textDataService;
         private readonly IHttpClientFactory _httpClientFactory;
 
         public ChatController(
             ILogger<ChatController> logger,
             IResponseService responseService,
             UserDataRepository userDataRepository,
-            TextData textData,
-            ProjectDataRepository projectDataRepository,
+            ITextDataService textDataService,
+            IProjectDataRepository projectDataRepository,
             IHttpClientFactory httpClientFactory)
         {
             _logger = logger;
             _responseService = responseService;
             _userDataRepository = userDataRepository;
-            _textData = textData;
+            _textDataService = textDataService;
             _projectDataRepository = projectDataRepository;
-            this._httpClientFactory = httpClientFactory;
+            _httpClientFactory = httpClientFactory;
         }
 
         [HttpPost]
         [Route("response")]
-        public async Task<IActionResult> GetResponse([FromForm] ChatRequest chatRequest)
+        public async Task<IActionResult> GetResponse([FromBody] ChatRequest chatRequest)
         {
             try
             {
@@ -61,7 +62,7 @@ namespace ChatApi.Controllers
         [Route("savegroup")]
         public async Task SaveSingleProject([FromBody] ProjectRequest project)
         {
-            var projectSave = project.MapTo<ProjectRequest, Project>(); 
+            var projectSave = project.MapTo<ProjectRequest, Project>();
             await _projectDataRepository.SaveAsync(projectSave);
         }
 
@@ -80,7 +81,37 @@ namespace ChatApi.Controllers
         {
             try
             {
-                await _textData.SalvarNoMongoDB(request.Id, request.Title, request.Content, request.ProjectId);
+                await _textDataService.SaveDocumentAsync(new DocumentInput
+                {
+                    Id = request.Id,
+                    Title = request.Title,
+                    Content = request.Content,
+                    ProjectId = request.ProjectId
+                });
+                return Created();
+            }
+            catch (Exception ex)
+            {
+                return StatusCode(500, ex.Message);
+            }
+        }
+
+        [HttpPost]
+        [Route("savetexts")]
+        public async Task<IActionResult> SaveTexts([FromBody] List<TextRequest> requests)
+        {
+            try
+            {
+                foreach(var request in requests)
+                {
+                    await _textDataService.SaveDocumentAsync(new DocumentInput
+                    {
+                        Id = request.Id,
+                        Title = request.Title,
+                        Content = request.Content,
+                        ProjectId = request.ProjectId
+                    });
+                }
                 return Created();
             }
             catch (Exception ex)
@@ -91,9 +122,9 @@ namespace ChatApi.Controllers
 
         [HttpGet]
         [Route("texts")]
-        public async Task<IEnumerable<TextResponse>> GetTexts()
+        public async Task<IEnumerable<TextResponse>> GetTexts(string groupId)
         {
-            var texts = await _textData.GetAll();
+            var texts = await _textDataService.GetByPorjectId(groupId);
             return texts.Select(t => {
                 return new TextResponse
                 {
@@ -108,7 +139,7 @@ namespace ChatApi.Controllers
         [Route("texts/id/{id}")]
         public async Task<TextResponse> GetText([FromRoute] string id)
         {
-            var textItem = await _textData.GetById(id);
+            var textItem = await _textDataService.GetById(id);
 
             return new TextResponse { 
                 Id = textItem.Id,

Controllers/MigrationController.cs

@@ -0,0 +1,419 @@
+using ChatApi.Data;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.SearchVectors;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.AspNetCore.Mvc;
+using Microsoft.Extensions.Options;
+using Microsoft.SemanticKernel.Embeddings;
+
+#pragma warning disable SKEXP0001
+
+namespace ChatApi.Controllers
+{
+    [ApiController]
+    [Route("api/[controller]")]
+    public class MigrationController : ControllerBase
+    {
+        private readonly IVectorDatabaseFactory _factory;
+        private readonly ILogger<MigrationController> _logger;
+        private readonly VectorDatabaseSettings _settings;
+        private readonly ITextEmbeddingGenerationService _embeddingService;
+        private readonly TextDataRepository _mongoRepository;
+
+        public MigrationController(
+            IVectorDatabaseFactory factory,
+            ILogger<MigrationController> logger,
+            IOptions<VectorDatabaseSettings> settings,
+            ITextEmbeddingGenerationService embeddingService,
+            TextDataRepository mongoRepository)
+        {
+            _factory = factory;
+            _logger = logger;
+            _settings = settings.Value;
+            _embeddingService = embeddingService;
+            _mongoRepository = mongoRepository;
+        }
+
+        /// <summary>
+        /// Status da migração e informações dos providers
+        /// </summary>
+        [HttpGet("status")]
+        public async Task<IActionResult> GetMigrationStatus()
+        {
+            try
+            {
+                var currentProvider = _factory.GetActiveProvider();
+
+                var status = new
+                {
+                    CurrentProvider = currentProvider,
+                    Settings = new
+                    {
+                        Provider = _settings.Provider,
+                        MongoDB = _settings.MongoDB != null ? new
+                        {
+                            DatabaseName = _settings.MongoDB.DatabaseName,
+                            TextCollection = _settings.MongoDB.TextCollectionName
+                        } : null,
+                        Qdrant = _settings.Qdrant != null ? new
+                        {
+                            Host = _settings.Qdrant.Host,
+                            Port = _settings.Qdrant.Port,
+                            Collection = _settings.Qdrant.CollectionName,
+                            VectorSize = _settings.Qdrant.VectorSize
+                        } : null
+                    },
+                    Stats = await GetProvidersStats()
+                };
+
+                return Ok(status);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao obter status da migração");
+                return StatusCode(500, new { error = ex.Message });
+            }
+        }
+
+        /// <summary>
+        /// Migra dados do MongoDB para Qdrant
+        /// </summary>
+        [HttpPost("mongo-to-qdrant")]
+        public async Task<IActionResult> MigrateMongoToQdrant(
+            [FromQuery] string? projectId = null,
+            [FromQuery] int batchSize = 50,
+            [FromQuery] bool dryRun = false)
+        {
+            try
+            {
+                if (_settings.Provider != "MongoDB")
+                {
+                    return BadRequest("Migração só funciona quando o provider atual é MongoDB");
+                }
+
+                _logger.LogInformation("Iniciando migração MongoDB → Qdrant. ProjectId: {ProjectId}, DryRun: {DryRun}",
+                    projectId, dryRun);
+
+                var result = await PerformMigration(projectId, batchSize, dryRun);
+
+                return Ok(result);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro durante migração MongoDB → Qdrant");
+                return StatusCode(500, new { error = ex.Message });
+            }
+        }
+
+        /// <summary>
+        /// Migra dados do Qdrant para MongoDB
+        /// </summary>
+        [HttpPost("qdrant-to-mongo")]
+        public async Task<IActionResult> MigrateQdrantToMongo(
+            [FromQuery] string? projectId = null,
+            [FromQuery] int batchSize = 50,
+            [FromQuery] bool dryRun = false)
+        {
+            try
+            {
+                if (_settings.Provider != "Qdrant")
+                {
+                    return BadRequest("Migração só funciona quando o provider atual é Qdrant");
+                }
+
+                _logger.LogInformation("Iniciando migração Qdrant → MongoDB. ProjectId: {ProjectId}, DryRun: {DryRun}",
+                    projectId, dryRun);
+
+                // TODO: Implementar migração reversa se necessário
+                return BadRequest("Migração Qdrant → MongoDB ainda não implementada");
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro durante migração Qdrant → MongoDB");
+                return StatusCode(500, new { error = ex.Message });
+            }
+        }
+
+        /// <summary>
+        /// Compara dados entre MongoDB e Qdrant
+        /// </summary>
+        [HttpPost("compare")]
+        public async Task<IActionResult> CompareProviders([FromQuery] string? projectId = null)
+        {
+            try
+            {
+                // Cria serviços para ambos os providers manualmente
+                var mongoService = CreateMongoService();
+                var qdrantService = await CreateQdrantService();
+
+                var comparison = await CompareData(mongoService, qdrantService, projectId);
+
+                return Ok(comparison);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao comparar providers");
+                return StatusCode(500, new { error = ex.Message });
+            }
+        }
+
+        /// <summary>
+        /// Limpa todos os dados do provider atual
+        /// </summary>
+        [HttpDelete("clear-current")]
+        public async Task<IActionResult> ClearCurrentProvider([FromQuery] string? projectId = null)
+        {
+            try
+            {
+                var vectorSearchService = _factory.CreateVectorSearchService();
+
+                if (string.IsNullOrEmpty(projectId))
+                {
+                    // Limpar tudo - PERIGOSO!
+                    return BadRequest("Limpeza completa requer confirmação. Use /clear-current/confirm");
+                }
+
+                // Limpar apenas um projeto
+                var documents = await vectorSearchService.GetDocumentsByProjectAsync(projectId);
+                var ids = documents.Select(d => d.Id).ToList();
+
+                foreach (var id in ids)
+                {
+                    await vectorSearchService.DeleteDocumentAsync(id);
+                }
+
+                return Ok(new
+                {
+                    provider = _settings.Provider,
+                    projectId,
+                    deletedCount = ids.Count
+                });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao limpar dados do provider");
+                return StatusCode(500, new { error = ex.Message });
+            }
+        }
+
+        /// <summary>
+        /// Testa conectividade dos providers
+        /// </summary>
+        [HttpGet("test-connections")]
+        public async Task<IActionResult> TestConnections()
+        {
+            var results = new Dictionary<string, object>();
+
+            // Testar MongoDB
+            try
+            {
+                var mongoService = CreateMongoService();
+                var mongoHealth = await mongoService.IsHealthyAsync();
+                var mongoStats = await mongoService.GetStatsAsync();
+
+                results["MongoDB"] = new
+                {
+                    healthy = mongoHealth,
+                    stats = mongoStats
+                };
+            }
+            catch (Exception ex)
+            {
+                results["MongoDB"] = new { healthy = false, error = ex.Message };
+            }
+
+            // Testar Qdrant
+            try
+            {
+                var qdrantService = await CreateQdrantService();
+                var qdrantHealth = await qdrantService.IsHealthyAsync();
+                var qdrantStats = await qdrantService.GetStatsAsync();
+
+                results["Qdrant"] = new
+                {
+                    healthy = qdrantHealth,
+                    stats = qdrantStats
+                };
+            }
+            catch (Exception ex)
+            {
+                results["Qdrant"] = new { healthy = false, error = ex.Message };
+            }
+
+            return Ok(results);
+        }
+
+        // ========================================
+        // MÉTODOS PRIVADOS
+        // ========================================
+
+        private async Task<object> PerformMigration(string? projectId, int batchSize, bool dryRun)
+        {
+            var mongoService = CreateMongoService();
+            var qdrantService = await CreateQdrantService();
+
+            // 1. Buscar dados do MongoDB
+            List<TextoComEmbedding> documents;
+            if (string.IsNullOrEmpty(projectId))
+            {
+                var allDocs = await _mongoRepository.GetAsync();
+                documents = allDocs.ToList();
+            }
+            else
+            {
+                var projectDocs = await _mongoRepository.GetByProjectIdAsync(projectId);
+                documents = projectDocs.ToList();
+            }
+
+            _logger.LogInformation("Encontrados {Count} documentos para migração", documents.Count);
+
+            if (dryRun)
+            {
+                return new
+                {
+                    dryRun = true,
+                    documentsFound = documents.Count,
+                    projects = documents.GroupBy(d => d.ProjetoId).Select(g => new {
+                        projectId = g.Key,
+                        count = g.Count()
+                    }).ToList()
+                };
+            }
+
+            // 2. Migrar em batches
+            var migrated = 0;
+            var errors = new List<string>();
+
+            for (int i = 0; i < documents.Count; i += batchSize)
+            {
+                var batch = documents.Skip(i).Take(batchSize);
+
+                foreach (var doc in batch)
+                {
+                    try
+                    {
+                        // Verificar se já existe no Qdrant
+                        var exists = await qdrantService.DocumentExistsAsync(doc.Id);
+                        if (exists)
+                        {
+                            _logger.LogDebug("Documento {Id} já existe no Qdrant, pulando", doc.Id);
+                            continue;
+                        }
+
+                        // Migrar documento
+                        await qdrantService.AddDocumentAsync(
+                            title: doc.Titulo,
+                            content: doc.Conteudo,
+                            projectId: doc.ProjetoId,
+                            embedding: doc.Embedding,
+                            metadata: new Dictionary<string, object>
+                            {
+                                ["project_name"] = doc.ProjetoNome ?? "",
+                                ["document_type"] = doc.TipoDocumento ?? "",
+                                ["category"] = doc.Categoria ?? "",
+                                ["tags"] = doc.Tags ?? Array.Empty<string>(),
+                                ["migrated_from"] = "MongoDB",
+                                ["migrated_at"] = DateTime.UtcNow.ToString("O")
+                            }
+                        );
+
+                        migrated++;
+
+                        if (migrated % 10 == 0)
+                        {
+                            _logger.LogInformation("Migrados {Migrated}/{Total} documentos", migrated, documents.Count);
+                        }
+                    }
+                    catch (Exception ex)
+                    {
+                        var error = $"Erro ao migrar documento {doc.Id}: {ex.Message}";
+                        errors.Add(error);
+                        _logger.LogError(ex, error);
+                    }
+                }
+            }
+
+            return new
+            {
+                totalDocuments = documents.Count,
+                migrated,
+                errors = errors.Count,
+                errorDetails = errors.Take(10).ToList(), // Primeiros 10 erros
+                batchSize,
+                duration = "Completed"
+            };
+        }
+
+        private async Task<object> CompareData(
+            IVectorSearchService mongoService,
+            IVectorSearchService qdrantService,
+            string? projectId)
+        {
+            var mongoStats = await mongoService.GetStatsAsync();
+            var qdrantStats = await qdrantService.GetStatsAsync();
+
+            var mongoCount = await mongoService.GetDocumentCountAsync(projectId);
+            var qdrantCount = await qdrantService.GetDocumentCountAsync(projectId);
+
+            return new
+            {
+                projectId,
+                comparison = new
+                {
+                    MongoDB = new
+                    {
+                        documentCount = mongoCount,
+                        healthy = await mongoService.IsHealthyAsync(),
+                        stats = mongoStats
+                    },
+                    Qdrant = new
+                    {
+                        documentCount = qdrantCount,
+                        healthy = await qdrantService.IsHealthyAsync(),
+                        stats = qdrantStats
+                    }
+                },
+                differences = new
+                {
+                    documentCountDiff = qdrantCount - mongoCount,
+                    inSync = mongoCount == qdrantCount
+                }
+            };
+        }
+
+        private MongoVectorSearchService CreateMongoService()
+        {
+            return new MongoVectorSearchService(_mongoRepository, _embeddingService);
+        }
+
+        private async Task<QdrantVectorSearchService> CreateQdrantService()
+        {
+            var qdrantSettings = Microsoft.Extensions.Options.Options.Create(_settings);
+            var logger = HttpContext.RequestServices.GetService<ILogger<QdrantVectorSearchService>>()!;
+
+            return new QdrantVectorSearchService(qdrantSettings, logger);
+        }
+
+        private async Task<Dictionary<string, object>> GetProvidersStats()
+        {
+            var stats = new Dictionary<string, object>();
+
+            try
+            {
+                var currentService = _factory.CreateVectorSearchService();
+                stats["current"] = await currentService.GetStatsAsync();
+            }
+            catch (Exception ex)
+            {
+                stats["current"] = new { error = ex.Message };
+            }
+
+            return stats;
+        }
+    }
+}
+
+#pragma warning restore SKEXP0001

Controllers/RAGStrategyController.cs

@@ -0,0 +1,225 @@
+using Microsoft.AspNetCore.Mvc;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.ResponseService;
+using ChatRAG.Contracts.VectorSearch;
+
+namespace ChatApi.Controllers
+{
+    [ApiController]
+    [Route("api/[controller]")]
+    public class RAGStrategyController : ControllerBase
+    {
+        private readonly IVectorDatabaseFactory _factory;
+        private readonly IServiceProvider _serviceProvider;
+        private readonly ILogger<RAGStrategyController> _logger;
+
+        public RAGStrategyController(
+            IVectorDatabaseFactory factory,
+            IServiceProvider serviceProvider,
+            ILogger<RAGStrategyController> logger)
+        {
+            _factory = factory;
+            _serviceProvider = serviceProvider;
+            _logger = logger;
+        }
+
+        /// <summary>
+        /// Lista as estratégias de RAG disponíveis
+        /// </summary>
+        [HttpGet("strategies")]
+        public IActionResult GetAvailableStrategies()
+        {
+            var strategies = new[]
+            {
+                new {
+                    name = "Standard",
+                    description = "RAG padrão com classificação automática de estratégia",
+                    service = "ResponseRAGService",
+                    features = new[] { "Busca por similaridade", "Filtros dinâmicos", "Classificação automática" }
+                },
+                new {
+                    name = "Hierarchical",
+                    description = "RAG hierárquico com múltiplas etapas de busca",
+                    service = "HierarchicalRAGService",
+                    features = new[] { "Análise de query", "Busca em múltiplas etapas", "Expansão de contexto", "Identificação de lacunas" }
+                }
+            };
+
+            return Ok(new
+            {
+                currentProvider = _factory.GetActiveProvider(),
+                availableStrategies = strategies
+            });
+        }
+
+        /// <summary>
+        /// Testa uma estratégia específica com uma pergunta
+        /// </summary>
+        [HttpPost("test/{strategy}")]
+        public async Task<IActionResult> TestStrategy(
+            [FromRoute] string strategy,
+            [FromBody] StrategyTestRequest request)
+        {
+            try
+            {
+                IResponseService responseService = strategy.ToLower() switch
+                {
+                    "standard" => _serviceProvider.GetRequiredService<ResponseRAGService>(),
+                    "hierarchical" => _serviceProvider.GetRequiredService<HierarchicalRAGService>(),
+                    _ => throw new ArgumentException($"Estratégia não suportada: {strategy}")
+                };
+
+                var stopwatch = System.Diagnostics.Stopwatch.StartNew();
+
+                // Usar dados mock se não fornecidos
+                var userData = request.UserData ?? new ChatApi.Models.UserData
+                {
+                    Id = "test-user",
+                    Name = "Test User"
+                };
+
+                var response = await responseService.GetResponse(
+                    userData,
+                    request.ProjectId,
+                    request.SessionId ?? Guid.NewGuid().ToString(),
+                    request.Question,
+                    request.Language ?? "pt"
+                );
+
+                stopwatch.Stop();
+
+                return Ok(new
+                {
+                    strategy,
+                    response,
+                    executionTime = stopwatch.ElapsedMilliseconds,
+                    provider = _factory.GetActiveProvider()
+                });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao testar estratégia {Strategy}", strategy);
+                return StatusCode(500, new { error = ex.Message });
+            }
+        }
+
+        /// <summary>
+        /// Compara resultados entre diferentes estratégias
+        /// </summary>
+        [HttpPost("compare")]
+        public async Task<IActionResult> CompareStrategies([FromBody] StrategyTestRequest request)
+        {
+            try
+            {
+                var userData = request.UserData ?? new ChatApi.Models.UserData
+                {
+                    Id = "test-user",
+                    Name = "Test User"
+                };
+
+                var sessionId = Guid.NewGuid().ToString();
+                var results = new Dictionary<string, object>();
+
+                // Testar estratégia padrão
+                try
+                {
+                    var standardService = _serviceProvider.GetRequiredService<ResponseRAGService>();
+                    var stopwatch1 = System.Diagnostics.Stopwatch.StartNew();
+                    var standardResponse = await standardService.GetResponse(
+                        userData, request.ProjectId, sessionId + "-standard",
+                        request.Question, request.Language ?? "pt");
+                    stopwatch1.Stop();
+
+                    results["standard"] = new
+                    {
+                        response = standardResponse,
+                        executionTime = stopwatch1.ElapsedMilliseconds,
+                        success = true
+                    };
+                }
+                catch (Exception ex)
+                {
+                    results["standard"] = new { success = false, error = ex.Message };
+                }
+
+                // Testar estratégia hierárquica
+                try
+                {
+                    var hierarchicalService = _serviceProvider.GetRequiredService<HierarchicalRAGService>();
+                    var stopwatch2 = System.Diagnostics.Stopwatch.StartNew();
+                    var hierarchicalResponse = await hierarchicalService.GetResponse(
+                        userData, request.ProjectId, sessionId + "-hierarchical",
+                        request.Question, request.Language ?? "pt");
+                    stopwatch2.Stop();
+
+                    results["hierarchical"] = new
+                    {
+                        response = hierarchicalResponse,
+                        executionTime = stopwatch2.ElapsedMilliseconds,
+                        success = true
+                    };
+                }
+                catch (Exception ex)
+                {
+                    results["hierarchical"] = new { success = false, error = ex.Message };
+                }
+
+                return Ok(new
+                {
+                    question = request.Question,
+                    projectId = request.ProjectId,
+                    provider = _factory.GetActiveProvider(),
+                    results
+                });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao comparar estratégias");
+                return StatusCode(500, new { error = ex.Message });
+            }
+        }
+
+        /// <summary>
+        /// Obtém métricas de performance das estratégias
+        /// </summary>
+        [HttpGet("metrics")]
+        public IActionResult GetMetrics()
+        {
+            // TODO: Implementar coleta de métricas real
+            var metrics = new
+            {
+                standard = new
+                {
+                    avgResponseTime = "1.2s",
+                    successRate = "98%",
+                    avgContextSize = "3 documentos",
+                    usage = "Alto"
+                },
+                hierarchical = new
+                {
+                    avgResponseTime = "2.1s",
+                    successRate = "95%",
+                    avgContextSize = "5-8 documentos",
+                    usage = "Médio"
+                },
+                recommendations = new[]
+                {
+                    "Use Standard para perguntas simples e rápidas",
+                    "Use Hierarchical para análises complexas que precisam de contexto profundo",
+                    "Hierarchical é melhor para perguntas técnicas detalhadas"
+                }
+            };
+
+            return Ok(metrics);
+        }
+    }
+
+    public class StrategyTestRequest
+    {
+        public string ProjectId { get; set; } = "";
+        public string Question { get; set; } = "";
+        public string? Language { get; set; }
+        public string? SessionId { get; set; }
+        public ChatApi.Models.UserData? UserData { get; set; }
+    }
+}

Controllers/sgnjnzt5.baf~

@@ -0,0 +1,225 @@
+using Microsoft.AspNetCore.Mvc;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.ResponseService;
+using ChatRAG.Contracts.VectorSearch;
+
+namespace ChatApi.Controllers
+{
+    [ApiController]
+    [Route("api/[controller]")]
+    public class RAGStrategyController : ControllerBase
+    {
+        private readonly IVectorDatabaseFactory _factory;
+        private readonly IServiceProvider _serviceProvider;
+        private readonly ILogger<RAGStrategyController> _logger;
+
+        public RAGStrategyController(
+            IVectorDatabaseFactory factory,
+            IServiceProvider serviceProvider,
+            ILogger<RAGStrategyController> logger)
+        {
+            _factory = factory;
+            _serviceProvider = serviceProvider;
+            _logger = logger;
+        }
+
+        /// <summary>
+        /// Lista as estratégias de RAG disponíveis
+        /// </summary>
+        [HttpGet("strategies")]
+        public IActionResult GetAvailableStrategies()
+        {
+            var strategies = new[]
+            {
+                new {
+                    name = "Standard",
+                    description = "RAG padrão com classificação automática de estratégia",
+                    service = "ResponseRAGService",
+                    features = new[] { "Busca por similaridade", "Filtros dinâmicos", "Classificação automática" }
+                },
+                new {
+                    name = "Hierarchical",
+                    description = "RAG hierárquico com múltiplas etapas de busca",
+                    service = "HierarchicalRAGService",
+                    features = new[] { "Análise de query", "Busca em múltiplas etapas", "Expansão de contexto", "Identificação de lacunas" }
+                }
+            };
+
+            return Ok(new
+            {
+                currentProvider = _factory.GetActiveProvider(),
+                availableStrategies = strategies
+            });
+        }
+
+        /// <summary>
+        /// Testa uma estratégia específica com uma pergunta
+        /// </summary>
+        [HttpPost("test/{strategy}")]
+        public async Task<IActionResult> TestStrategy(
+            [FromRoute] string strategy,
+            [FromBody] StrategyTestRequest request)
+        {
+            try
+            {
+                IResponseService responseService = strategy.ToLower() switch
+                {
+                    "standard" => _serviceProvider.GetRequiredService<ResponseRAGService>(),
+                    "hierarchical" => _serviceProvider.GetRequiredService<HierarchicalRAGService>(),
+                    _ => throw new ArgumentException($"Estratégia não suportada: {strategy}")
+                };
+
+                var stopwatch = System.Diagnostics.Stopwatch.StartNew();
+
+                // Usar dados mock se não fornecidos
+                var userData = request.UserData ?? new ChatApi.Models.UserData
+                {
+                    Id = "test-user",
+                    Name = "Test User"
+                };
+
+                var response = await responseService.GetResponse(
+                    userData,
+                    request.ProjectId,
+                    request.SessionId ?? Guid.NewGuid().ToString(),
+                    request.Question,
+                    request.Language ?? "pt"
+                );
+
+                stopwatch.Stop();
+
+                return Ok(new
+                {
+                    strategy,
+                    response,
+                    executionTime = stopwatch.ElapsedMilliseconds,
+                    provider = _factory.GetActiveProvider()
+                });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao testar estratégia {Strategy}", strategy);
+                return StatusCode(500, new { error = ex.Message });
+            }
+        }
+
+        /// <summary>
+        /// Compara resultados entre diferentes estratégias
+        /// </summary>
+        [HttpPost("compare")]
+        public async Task<IActionResult> CompareStrategies([FromBody] StrategyTestRequest request)
+        {
+            try
+            {
+                var userData = request.UserData ?? new ChatApi.Models.UserData
+                {
+                    Id = "test-user",
+                    Name = "Test User"
+                };
+
+                var sessionId = Guid.NewGuid().ToString();
+                var results = new Dictionary<string, object>();
+
+                // Testar estratégia padrão
+                try
+                {
+                    var standardService = _serviceProvider.GetRequiredService<ResponseRAGService>();
+                    var stopwatch1 = System.Diagnostics.Stopwatch.StartNew();
+                    var standardResponse = await standardService.GetResponse(
+                        userData, request.ProjectId, sessionId + "-standard",
+                        request.Question, request.Language ?? "pt");
+                    stopwatch1.Stop();
+
+                    results["standard"] = new
+                    {
+                        response = standardResponse,
+                        executionTime = stopwatch1.ElapsedMilliseconds,
+                        success = true
+                    };
+                }
+                catch (Exception ex)
+                {
+                    results["standard"] = new { success = false, error = ex.Message };
+                }
+
+                // Testar estratégia hierárquica
+                try
+                {
+                    var hierarchicalService = _serviceProvider.GetRequiredService<HierarchicalRAGService>();
+                    var stopwatch2 = System.Diagnostics.Stopwatch.StartNew();
+                    var hierarchicalResponse = await hierarchicalService.GetResponse(
+                        userData, request.ProjectId, sessionId + "-hierarchical",
+                        request.Question, request.Language ?? "pt");
+                    stopwatch2.Stop();
+
+                    results["hierarchical"] = new
+                    {
+                        response = hierarchicalResponse,
+                        executionTime = stopwatch2.ElapsedMilliseconds,
+                        success = true
+                    };
+                }
+                catch (Exception ex)
+                {
+                    results["hierarchical"] = new { success = false, error = ex.Message };
+                }
+
+                return Ok(new
+                {
+                    question = request.Question,
+                    projectId = request.ProjectId,
+                    provider = _factory.GetActiveProvider(),
+                    results
+                });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao comparar estratégias");
+                return StatusCode(500, new { error = ex.Message });
+            }
+        }
+
+        /// <summary>
+        /// Obtém métricas de performance das estratégias
+        /// </summary>
+        [HttpGet("metrics")]
+        public IActionResult GetMetrics()
+        {
+            // TODO: Implementar coleta de métricas real
+            var metrics = new
+            {
+                standard = new
+                {
+                    avgResponseTime = "1.2s",
+                    successRate = "98%",
+                    avgContextSize = "3 documentos",
+                    usage = "Alto"
+                },
+                hierarchical = new
+                {
+                    avgResponseTime = "2.1s",
+                    successRate = "95%",
+                    avgContextSize = "5-8 documentos",
+                    usage = "Médio"
+                },
+                recommendations = new[]
+                {
+                    "Use Standard para perguntas simples e rápidas",
+                    "Use Hierarchical para análises complexas que precisam de contexto profundo",
+                    "Hierarchical é melhor para perguntas técnicas detalhadas"
+                }
+            };
+
+            return Ok(metrics);
+        }
+    }
+
+    public class StrategyTestRequest
+    {
+        public string ProjectId { get; set; } = "";
+        public string Question { get; set; } = "";
+        public string? Language { get; set; }
+        public string? SessionId { get; set; }
+        public ChatApi.Models.UserData? UserData { get; set; }
+    }
+}

Data/30u0ddp1.org~

@@ -0,0 +1,255 @@
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+using System.Text;
+using System.Text.Json;
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+namespace ChatRAG.Data
+{
+    public class QdrantProjectDataRepository : IProjectDataRepository
+    {
+        private readonly HttpClient _httpClient;
+        private readonly string _collectionName;
+        private readonly ILogger<QdrantProjectDataRepository> _logger;
+        private readonly QdrantClient _qdrantClient;
+
+        public QdrantProjectDataRepository(
+            IOptions<VectorDatabaseSettings> settings,
+            HttpClient httpClient,
+            ILogger<QdrantProjectDataRepository> logger)
+        {
+            var qdrantSettings = settings.Value.Qdrant ?? throw new ArgumentNullException("Qdrant settings not configured");
+            _httpClient = httpClient;
+            _httpClient.BaseAddress = new Uri($"http://{qdrantSettings.Host}:{qdrantSettings.Port}");
+            _collectionName = qdrantSettings.GroupsCollectionName;
+            _logger = logger;
+
+            // Inicializa o QdrantClient - use GRPC (porta 6334) para melhor performance
+            _qdrantClient = new QdrantClient(qdrantSettings.Host, port: 6334, https: false);
+
+            InitializeAsync().GetAwaiter().GetResult();
+        }
+
+        private async Task InitializeAsync()
+        {
+            try
+            {
+                var exists = await _qdrantClient.CollectionExistsAsync(_collectionName);
+                if (!exists)
+                {
+                    await CreateProjectsCollection();
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao inicializar collection de projetos no Qdrant");
+            }
+        }
+
+        public async Task<List<Project>> GetAsync()
+        {
+            try
+            {
+                var scrollRequest = new ScrollPoints
+                {
+                    CollectionName = _collectionName,
+                    Filter = new Filter(), // Filtro vazio
+                    Limit = 1000,
+                    WithPayload = true,
+                    WithVectors = false
+                };
+
+                var result = await _qdrantClient.ScrollAsync(_collectionName, scrollRequest);
+
+                return result.Select(ConvertToProject)
+                    .Where(p => p != null)
+                    .ToList()!;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar projetos do Qdrant");
+                return new List<Project>();
+            }
+        }
+
+        public async Task<Project?> GetAsync(string id)
+        {
+            try
+            {
+                var points = await _qdrantClient.RetrieveAsync(
+                    _collectionName,
+                    new[] { PointId.Parser.Parse(id) },
+                    withPayload: true,
+                    withVectors: false
+                );
+
+                var point = points.FirstOrDefault();
+                return point != null ? ConvertToProject(point) : null;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar projeto {Id} no Qdrant", id);
+                return null;
+            }
+        }
+
+        public async Task CreateAsync(Project newProject)
+        {
+            try
+            {
+                var id = string.IsNullOrEmpty(newProject.Id) ? Guid.NewGuid().ToString() : newProject.Id;
+                newProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.Parser.Parse(id),
+                    Vectors = new float[384], // Vector dummy para projetos
+                    Payload =
+                    {
+                        ["id"] = newProject.Id,
+                        ["nome"] = newProject.Nome,
+                        ["descricao"] = newProject.Descricao,
+                        ["created_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao criar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task UpdateAsync(string id, Project updatedProject)
+        {
+            try
+            {
+                updatedProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.Parser.Parse(id),
+                    Vectors = new float[384], // Vector dummy
+                    Payload =
+                    {
+                        ["id"] = updatedProject.Id,
+                        ["nome"] = updatedProject.Nome,
+                        ["descricao"] = updatedProject.Descricao,
+                        ["updated_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar projeto {Id} no Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task SaveAsync(Project project)
+        {
+            try
+            {
+                if (string.IsNullOrEmpty(project.Id))
+                {
+                    await CreateAsync(project);
+                }
+                else
+                {
+                    var existing = await GetAsync(project.Id);
+                    if (existing == null)
+                    {
+                        await CreateAsync(project);
+                    }
+                    else
+                    {
+                        await UpdateAsync(project.Id, project);
+                    }
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task RemoveAsync(string id)
+        {
+            try
+            {
+                await _qdrantClient.DeleteAsync(
+                    _collectionName,
+                    new[] { PointId.Parser.Parse(id) }
+                );
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao remover projeto {Id} do Qdrant", id);
+                throw;
+            }
+        }
+
+        private async Task CreateProjectsCollection()
+        {
+            var vectorParams = new VectorParams
+            {
+                Size = 384,
+                Distance = Distance.Cosine
+            };
+
+            await _qdrantClient.CreateCollectionAsync(_collectionName, vectorParams);
+
+            _logger.LogInformation("Collection de projetos '{CollectionName}' criada no Qdrant", _collectionName);
+        }
+
+        private static Project? ConvertToProject(RetrievedPoint point)
+        {
+            try
+            {
+                if (point.Payload == null) return null;
+
+                return new Project
+                {
+                    Id = point.Payload.TryGetValue("id", out var idValue) ? idValue.StringValue : point.Id.ToString(),
+                    Nome = point.Payload.TryGetValue("nome", out var nomeValue) ? nomeValue.StringValue : "",
+                    Descricao = point.Payload.TryGetValue("descricao", out var descValue) ? descValue.StringValue : ""
+                };
+            }
+            catch
+            {
+                return null;
+            }
+        }
+    }
+
+    public class QdrantScrollResult
+    {
+        public QdrantScrollData? result { get; set; }
+    }
+
+    public class QdrantScrollData
+    {
+        public QdrantPoint[]? points { get; set; }
+    }
+
+    public class QdrantPointResult
+    {
+        public QdrantPoint? result { get; set; }
+    }
+
+    public class QdrantPoint
+    {
+        public string? id { get; set; }
+        public Dictionary<string, object>? payload { get; set; }
+    }
+}

Data/32reubjo.e20~

@@ -0,0 +1,255 @@
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+using System.Text;
+using System.Text.Json;
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+namespace ChatRAG.Data
+{
+    public class QdrantProjectDataRepository : IProjectDataRepository
+    {
+        private readonly HttpClient _httpClient;
+        private readonly string _collectionName;
+        private readonly ILogger<QdrantProjectDataRepository> _logger;
+        private readonly QdrantClient _qdrantClient;
+
+        public QdrantProjectDataRepository(
+            IOptions<VectorDatabaseSettings> settings,
+            HttpClient httpClient,
+            ILogger<QdrantProjectDataRepository> logger)
+        {
+            var qdrantSettings = settings.Value.Qdrant ?? throw new ArgumentNullException("Qdrant settings not configured");
+            _httpClient = httpClient;
+            _httpClient.BaseAddress = new Uri($"http://{qdrantSettings.Host}:{qdrantSettings.Port}");
+            _collectionName = qdrantSettings.GroupsCollectionName;
+            _logger = logger;
+
+            // Inicializa o QdrantClient - use GRPC (porta 6334) para melhor performance
+            _qdrantClient = new QdrantClient(qdrantSettings.Host, port: 6334, https: false);
+
+            InitializeAsync().GetAwaiter().GetResult();
+        }
+
+        private async Task InitializeAsync()
+        {
+            try
+            {
+                var exists = await _qdrantClient.CollectionExistsAsync(_collectionName);
+                if (!exists)
+                {
+                    await CreateProjectsCollection();
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao inicializar collection de projetos no Qdrant");
+            }
+        }
+
+        public async Task<List<Project>> GetAsync()
+        {
+            try
+            {
+                var scrollRequest = new ScrollPoints
+                {
+                    CollectionName = _collectionName,
+                    Filter = new Filter(), // Filtro vazio
+                    Limit = 1000,
+                    WithPayload = true,
+                    WithVectors = false
+                };
+
+                var result = await _qdrantClient.ScrollAsync(_collectionName, scrollRequest);
+
+                return result.Select(ConvertToProject)
+                    .Where(p => p != null)
+                    .ToList()!;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar projetos do Qdrant");
+                return new List<Project>();
+            }
+        }
+
+        public async Task<Project?> GetAsync(string id)
+        {
+            try
+            {
+                var points = await _qdrantClient.RetrieveAsync(
+                    _collectionName,
+                    new[] { PointId.Parser.ParseFrom(id) },
+                    withPayload: true,
+                    withVectors: false
+                );
+
+                var point = points.FirstOrDefault();
+                return point != null ? ConvertToProject(point) : null;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar projeto {Id} no Qdrant", id);
+                return null;
+            }
+        }
+
+        public async Task CreateAsync(Project newProject)
+        {
+            try
+            {
+                var id = string.IsNullOrEmpty(newProject.Id) ? Guid.NewGuid().ToString() : newProject.Id;
+                newProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.Parser.ParseFrom(id),
+                    Vectors = new float[384], // Vector dummy para projetos
+                    Payload =
+                    {
+                        ["id"] = newProject.Id,
+                        ["nome"] = newProject.Nome,
+                        ["descricao"] = newProject.Descricao,
+                        ["created_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao criar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task UpdateAsync(string id, Project updatedProject)
+        {
+            try
+            {
+                updatedProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.Parser.ParseFrom(id),
+                    Vectors = new float[384], // Vector dummy
+                    Payload =
+                    {
+                        ["id"] = updatedProject.Id,
+                        ["nome"] = updatedProject.Nome,
+                        ["descricao"] = updatedProject.Descricao,
+                        ["updated_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar projeto {Id} no Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task SaveAsync(Project project)
+        {
+            try
+            {
+                if (string.IsNullOrEmpty(project.Id))
+                {
+                    await CreateAsync(project);
+                }
+                else
+                {
+                    var existing = await GetAsync(project.Id);
+                    if (existing == null)
+                    {
+                        await CreateAsync(project);
+                    }
+                    else
+                    {
+                        await UpdateAsync(project.Id, project);
+                    }
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task RemoveAsync(string id)
+        {
+            try
+            {
+                await _qdrantClient.DeleteAsync(
+                    _collectionName,
+                    new[] { PointId.Parser.ParseFrom(id) }
+                );
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao remover projeto {Id} do Qdrant", id);
+                throw;
+            }
+        }
+
+        private async Task CreateProjectsCollection()
+        {
+            var vectorParams = new VectorParams
+            {
+                Size = 384,
+                Distance = Distance.Cosine
+            };
+
+            await _qdrantClient.CreateCollectionAsync(_collectionName, vectorParams);
+
+            _logger.LogInformation("Collection de projetos '{CollectionName}' criada no Qdrant", _collectionName);
+        }
+
+        private static Project? ConvertToProject(RetrievedPoint point)
+        {
+            try
+            {
+                if (point.Payload == null) return null;
+
+                return new Project
+                {
+                    Id = point.Payload.TryGetValue("id", out var idValue) ? idValue.StringValue : point.Id.ToString(),
+                    Nome = point.Payload.TryGetValue("nome", out var nomeValue) ? nomeValue.StringValue : "",
+                    Descricao = point.Payload.TryGetValue("descricao", out var descValue) ? descValue.StringValue : ""
+                };
+            }
+            catch
+            {
+                return null;
+            }
+        }
+    }
+
+    public class QdrantScrollResult
+    {
+        public QdrantScrollData? result { get; set; }
+    }
+
+    public class QdrantScrollData
+    {
+        public QdrantPoint[]? points { get; set; }
+    }
+
+    public class QdrantPointResult
+    {
+        public QdrantPoint? result { get; set; }
+    }
+
+    public class QdrantPoint
+    {
+        public string? id { get; set; }
+        public Dictionary<string, object>? payload { get; set; }
+    }
+}

Data/3qrw3lwa.v4s~

@@ -0,0 +1,255 @@
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+using System.Text;
+using System.Text.Json;
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+namespace ChatRAG.Data
+{
+    public class QdrantProjectDataRepository : IProjectDataRepository
+    {
+        private readonly HttpClient _httpClient;
+        private readonly string _collectionName;
+        private readonly ILogger<QdrantProjectDataRepository> _logger;
+        private readonly QdrantClient _qdrantClient;
+
+        public QdrantProjectDataRepository(
+            IOptions<VectorDatabaseSettings> settings,
+            HttpClient httpClient,
+            ILogger<QdrantProjectDataRepository> logger)
+        {
+            var qdrantSettings = settings.Value.Qdrant ?? throw new ArgumentNullException("Qdrant settings not configured");
+            _httpClient = httpClient;
+            _httpClient.BaseAddress = new Uri($"http://{qdrantSettings.Host}:{qdrantSettings.Port}");
+            _collectionName = qdrantSettings.GroupsCollectionName;
+            _logger = logger;
+
+            // Inicializa o QdrantClient - use GRPC (porta 6334) para melhor performance
+            _qdrantClient = new QdrantClient(qdrantSettings.Host, port: 6334, https: false);
+
+            InitializeAsync().GetAwaiter().GetResult();
+        }
+
+        private async Task InitializeAsync()
+        {
+            try
+            {
+                var exists = await _qdrantClient.CollectionExistsAsync(_collectionName);
+                if (!exists)
+                {
+                    await CreateProjectsCollection();
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao inicializar collection de projetos no Qdrant");
+            }
+        }
+
+        public async Task<List<Project>> GetAsync()
+        {
+            try
+            {
+                var scrollRequest = new ScrollPoints
+                {
+                    CollectionName = _collectionName,
+                    Filter = new Filter(), // Filtro vazio
+                    Limit = 1000,
+                    WithPayload = true,
+                    WithVectors = false
+                };
+
+                var result = await _qdrantClient.ScrollAsync(scrollRequest);
+
+                return result.Select(ConvertToProject)
+                    .Where(p => p != null)
+                    .ToList()!;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar projetos do Qdrant");
+                return new List<Project>();
+            }
+        }
+
+        public async Task<Project?> GetAsync(string id)
+        {
+            try
+            {
+                var points = await _qdrantClient.RetrieveAsync(
+                    _collectionName,
+                    new[] { PointId.NewGuid(Guid.Parse(id)) },
+                    withPayload: true,
+                    withVectors: false
+                );
+
+                var point = points.FirstOrDefault();
+                return point != null ? ConvertToProject(point) : null;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar projeto {Id} no Qdrant", id);
+                return null;
+            }
+        }
+
+        public async Task CreateAsync(Project newProject)
+        {
+            try
+            {
+                var id = string.IsNullOrEmpty(newProject.Id) ? Guid.NewGuid().ToString() : newProject.Id;
+                newProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.NewGuid(Guid.Parse(id)),
+                    Vectors = new float[384], // Vector dummy para projetos
+                    Payload =
+                    {
+                        ["id"] = newProject.Id,
+                        ["nome"] = newProject.Nome,
+                        ["descricao"] = newProject.Descricao,
+                        ["created_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao criar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task UpdateAsync(string id, Project updatedProject)
+        {
+            try
+            {
+                updatedProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.NewGuid(Guid.Parse(id)),
+                    Vectors = new float[384], // Vector dummy
+                    Payload =
+                    {
+                        ["id"] = updatedProject.Id,
+                        ["nome"] = updatedProject.Nome,
+                        ["descricao"] = updatedProject.Descricao,
+                        ["updated_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar projeto {Id} no Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task SaveAsync(Project project)
+        {
+            try
+            {
+                if (string.IsNullOrEmpty(project.Id))
+                {
+                    await CreateAsync(project);
+                }
+                else
+                {
+                    var existing = await GetAsync(project.Id);
+                    if (existing == null)
+                    {
+                        await CreateAsync(project);
+                    }
+                    else
+                    {
+                        await UpdateAsync(project.Id, project);
+                    }
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task RemoveAsync(string id)
+        {
+            try
+            {
+                await _qdrantClient.DeleteAsync(
+                    _collectionName,
+                    new[] { PointId.NewGuid(Guid.Parse(id)) }
+                );
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao remover projeto {Id} do Qdrant", id);
+                throw;
+            }
+        }
+
+        private async Task CreateProjectsCollection()
+        {
+            var vectorParams = new VectorParams
+            {
+                Size = 384,
+                Distance = Distance.Cosine
+            };
+
+            await _qdrantClient.CreateCollectionAsync(_collectionName, vectorParams);
+
+            _logger.LogInformation("Collection de projetos '{CollectionName}' criada no Qdrant", _collectionName);
+        }
+
+        private static Project? ConvertToProject(RetrievedPoint point)
+        {
+            try
+            {
+                if (point.Payload == null) return null;
+
+                return new Project
+                {
+                    Id = point.Payload.TryGetValue("id", out var idValue) ? idValue.StringValue : point.Id.ToString(),
+                    Nome = point.Payload.TryGetValue("nome", out var nomeValue) ? nomeValue.StringValue : "",
+                    Descricao = point.Payload.TryGetValue("descricao", out var descValue) ? descValue.StringValue : ""
+                };
+            }
+            catch
+            {
+                return null;
+            }
+        }
+    }
+
+    public class QdrantScrollResult
+    {
+        public QdrantScrollData? result { get; set; }
+    }
+
+    public class QdrantScrollData
+    {
+        public QdrantPoint[]? points { get; set; }
+    }
+
+    public class QdrantPointResult
+    {
+        public QdrantPoint? result { get; set; }
+    }
+
+    public class QdrantPoint
+    {
+        public string? id { get; set; }
+        public Dictionary<string, object>? payload { get; set; }
+    }
+}

Data/ChromaProjectDataRepository.cs

@@ -0,0 +1,331 @@
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.SearchVectors;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+using System.Text;
+using System.Text.Json;
+
+namespace ChatRAG.Data
+{
+
+    public class ChromaProjectDataRepository : IProjectDataRepository
+    {
+        private readonly HttpClient _httpClient;
+        private readonly string _collectionName;
+        private readonly ILogger<ChromaProjectDataRepository> _logger;
+
+        public ChromaProjectDataRepository(
+            IOptions<VectorDatabaseSettings> settings,
+            HttpClient httpClient,
+            ILogger<ChromaProjectDataRepository> logger)
+        {
+            var chromaSettings = settings.Value.Chroma ?? throw new ArgumentNullException("Chroma settings not configured");
+            _httpClient = httpClient;
+            _httpClient.BaseAddress = new Uri($"http://{chromaSettings.Host}:{chromaSettings.Port}");
+            _collectionName = "projects"; // Collection separada para projetos
+            _logger = logger;
+
+            InitializeAsync().GetAwaiter().GetResult();
+        }
+
+        private async Task InitializeAsync()
+        {
+            try
+            {
+                // Verificar se a collection existe, se não, criar
+                var collections = await GetCollectionsAsync();
+                if (!collections.Contains(_collectionName))
+                {
+                    await CreateProjectsCollection();
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao inicializar collection de projetos no Chroma");
+            }
+        }
+
+        public async Task<List<Project>> GetAsync()
+        {
+            try
+            {
+                var query = new
+                {
+                    where = new { entity_type = "project" },
+                    include = new[] { "documents", "metadatas" }
+                };
+
+                var json = JsonSerializer.Serialize(query);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v2/collections/{_collectionName}/get", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    _logger.LogError("Erro ao buscar projetos no Chroma");
+                    return new List<Project>();
+                }
+
+                var result = await response.Content.ReadAsStringAsync();
+                var getResult = JsonSerializer.Deserialize<ChromaGetResult>(result);
+
+                var projects = new List<Project>();
+                if (getResult?.ids?.Length > 0)
+                {
+                    for (int i = 0; i < getResult.ids.Length; i++)
+                    {
+                        var metadata = getResult.metadatas?[i];
+                        if (metadata != null)
+                        {
+                            projects.Add(new Project
+                            {
+                                Id = metadata.GetValueOrDefault("id")?.ToString() ?? getResult.ids[i],
+                                Nome = metadata.GetValueOrDefault("nome")?.ToString() ?? "",
+                                Descricao = metadata.GetValueOrDefault("descricao")?.ToString() ?? ""
+                            });
+                        }
+                    }
+                }
+
+                return projects;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar projetos do Chroma");
+                return new List<Project>();
+            }
+        }
+
+        public async Task<Project?> GetAsync(string id)
+        {
+            try
+            {
+                var query = new
+                {
+                    ids = new[] { id },
+                    include = new[] { "metadatas" }
+                };
+
+                var json = JsonSerializer.Serialize(query);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v2/collections/{_collectionName}/get", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    return null;
+                }
+
+                var result = await response.Content.ReadAsStringAsync();
+                var getResult = JsonSerializer.Deserialize<ChromaGetResult>(result);
+
+                if (getResult?.ids?.Length > 0 && getResult.metadatas?[0] != null)
+                {
+                    var metadata = getResult.metadatas[0];
+                    return new Project
+                    {
+                        Id = metadata.GetValueOrDefault("id")?.ToString() ?? id,
+                        Nome = metadata.GetValueOrDefault("nome")?.ToString() ?? "",
+                        Descricao = metadata.GetValueOrDefault("descricao")?.ToString() ?? ""
+                    };
+                }
+
+                return null;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar projeto {Id} no Chroma", id);
+                return null;
+            }
+        }
+
+        public async Task CreateAsync(Project newProject)
+        {
+            try
+            {
+                var id = string.IsNullOrEmpty(newProject.Id) ? Guid.NewGuid().ToString() : newProject.Id;
+                newProject.Id = id;
+
+                var document = new
+                {
+                    ids = new[] { id },
+                    documents = new[] { $"Projeto: {newProject.Nome}" },
+                    metadatas = new[] { new Dictionary<string, object>
+                    {
+                        ["id"] = id,
+                        ["nome"] = newProject.Nome,
+                        ["descricao"] = newProject.Descricao,
+                        ["created_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }},
+                    embeddings = new[] { new double[384] } // Vector dummy
+                };
+
+                var json = JsonSerializer.Serialize(document);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v2/collections/{_collectionName}/add", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    var error = await response.Content.ReadAsStringAsync();
+                    throw new Exception($"Erro ao criar projeto no Chroma: {error}");
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao criar projeto no Chroma");
+                throw;
+            }
+        }
+
+        public async Task UpdateAsync(string id, Project updatedProject)
+        {
+            try
+            {
+                // Chroma não tem update direto, então fazemos upsert
+                updatedProject.Id = id;
+
+                var document = new
+                {
+                    ids = new[] { id },
+                    documents = new[] { $"Projeto: {updatedProject.Nome}" },
+                    metadatas = new[] { new Dictionary<string, object>
+                    {
+                        ["id"] = id,
+                        ["nome"] = updatedProject.Nome,
+                        ["descricao"] = updatedProject.Descricao,
+                        ["updated_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }},
+                    embeddings = new[] { new double[384] }
+                };
+
+                var json = JsonSerializer.Serialize(document);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v2/collections/{_collectionName}/upsert", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    var error = await response.Content.ReadAsStringAsync();
+                    throw new Exception($"Erro ao atualizar projeto no Chroma: {error}");
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar projeto {Id} no Chroma", id);
+                throw;
+            }
+        }
+
+        public async Task SaveAsync(Project project)
+        {
+            try
+            {
+                if (string.IsNullOrEmpty(project.Id))
+                {
+                    await CreateAsync(project);
+                }
+                else
+                {
+                    var existing = await GetAsync(project.Id);
+                    if (existing == null)
+                    {
+                        await CreateAsync(project);
+                    }
+                    else
+                    {
+                        await UpdateAsync(project.Id, project);
+                    }
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar projeto no Chroma");
+                throw;
+            }
+        }
+
+        public async Task RemoveAsync(string id)
+        {
+            try
+            {
+                var deleteRequest = new
+                {
+                    ids = new[] { id }
+                };
+
+                var json = JsonSerializer.Serialize(deleteRequest);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v2/collections/{_collectionName}/delete", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    var error = await response.Content.ReadAsStringAsync();
+                    _logger.LogWarning("Erro ao remover projeto {Id} do Chroma: {Error}", id, error);
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao remover projeto {Id} do Chroma", id);
+                throw;
+            }
+        }
+
+        private async Task<string[]> GetCollectionsAsync()
+        {
+            try
+            {
+                var response = await _httpClient.GetAsync("/api/v2/collections");
+                if (!response.IsSuccessStatusCode)
+                {
+                    return Array.Empty<string>();
+                }
+
+                var content = await response.Content.ReadAsStringAsync();
+                var collections = JsonSerializer.Deserialize<string[]>(content);
+                return collections ?? Array.Empty<string>();
+            }
+            catch
+            {
+                return Array.Empty<string>();
+            }
+        }
+
+        private async Task CreateProjectsCollection()
+        {
+            var collection = new
+            {
+                name = _collectionName,
+                metadata = new
+                {
+                    description = "Projects Collection",
+                    created_at = DateTime.UtcNow.ToString("O")
+                }
+            };
+
+            var json = JsonSerializer.Serialize(collection);
+            var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+            var response = await _httpClient.PostAsync("/api/v2/collections", content);
+
+            if (!response.IsSuccessStatusCode)
+            {
+                var error = await response.Content.ReadAsStringAsync();
+                throw new Exception($"Erro ao criar collection de projetos: {error}");
+            }
+
+            _logger.LogInformation("Collection de projetos '{CollectionName}' criada no Chroma", _collectionName);
+        }
+    }
+
+    public class ChromaGetResult
+    {
+        public string[] ids { get; set; } = Array.Empty<string>();
+        public string[] documents { get; set; } = Array.Empty<string>();
+        public Dictionary<string, object>[]? metadatas { get; set; }
+    }
+}

Data/MongoProjectDataRepository.cs

@@ -1,25 +1,27 @@
 using ChatApi;
 using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Settings.ChatRAG.Configuration;
 using Microsoft.Extensions.Options;
 using MongoDB.Driver;
 
 namespace ChatRAG.Data
 {
-    public class ProjectDataRepository
+    public class MongoProjectDataRepository : IProjectDataRepository
     {
         private readonly IMongoCollection<Project> _textsCollection;
 
-        public ProjectDataRepository(
-            IOptions<DomvsDatabaseSettings> databaseSettings)
+        public MongoProjectDataRepository(
+            IOptions<VectorDatabaseSettings> databaseSettings)
         {
             var mongoClient = new MongoClient(
-                databaseSettings.Value.ConnectionString);
+                databaseSettings.Value.MongoDB.ConnectionString);
 
             var mongoDatabase = mongoClient.GetDatabase(
-                databaseSettings.Value.DatabaseName);
+                databaseSettings.Value.MongoDB.DatabaseName);
 
             _textsCollection = mongoDatabase.GetCollection<Project>(
-                databaseSettings.Value.ProjectCollectionName);
+                databaseSettings.Value.MongoDB.ProjectCollectionName);
         }
 
         public async Task<List<Project>> GetAsync() =>

Data/MongoTextDataService.cs

@@ -0,0 +1,178 @@
+using ChatApi.Data;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using Microsoft.SemanticKernel.Embeddings;
+
+#pragma warning disable SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+namespace ChatRAG.Data
+{
+    public class MongoTextDataService : ITextDataService
+    {
+        private readonly TextData _textData; // Sua classe existente!
+        private readonly ITextEmbeddingGenerationService _embeddingService;
+
+        public MongoTextDataService(
+            TextData textData,
+            ITextEmbeddingGenerationService embeddingService)
+        {
+            _textData = textData;
+            _embeddingService = embeddingService;
+        }
+
+        public string ProviderName => "MongoDB";
+
+        // ========================================
+        // MÉTODOS ORIGINAIS - Delega para TextData
+        // ========================================
+
+        public async Task SalvarNoMongoDB(string titulo, string texto, string projectId)
+        {
+            await _textData.SalvarNoMongoDB(titulo, texto, projectId);
+        }
+
+        public async Task SalvarNoMongoDB(string? id, string titulo, string texto, string projectId)
+        {
+            await _textData.SalvarNoMongoDB(id, titulo, texto, projectId);
+        }
+
+        public async Task SalvarTextoComEmbeddingNoMongoDB(string textoCompleto, string projectId)
+        {
+            await _textData.SalvarTextoComEmbeddingNoMongoDB(textoCompleto, projectId);
+        }
+
+        public async Task<IEnumerable<TextoComEmbedding>> GetAll()
+        {
+            return await _textData.GetAll();
+        }
+
+        public async Task<IEnumerable<TextoComEmbedding>> GetByPorjectId(string projectId)
+        {
+            return await _textData.GetByPorjectId(projectId);
+        }
+
+        public async Task<TextoComEmbedding> GetById(string id)
+        {
+            return await _textData.GetById(id);
+        }
+
+        // ========================================
+        // NOVOS MÉTODOS UNIFICADOS
+        // ========================================
+
+        public async Task<string> SaveDocumentAsync(DocumentInput document)
+        {
+            var id = document.Id ?? Guid.NewGuid().ToString();
+            await _textData.SalvarNoMongoDB(id, document.Title, document.Content, document.ProjectId);
+            return id;
+        }
+
+        public async Task UpdateDocumentAsync(string id, DocumentInput document)
+        {
+            await _textData.SalvarNoMongoDB(id, document.Title, document.Content, document.ProjectId);
+        }
+
+        public async Task DeleteDocumentAsync(string id)
+        {
+            // Implementar quando necessário ou usar TextDataRepository diretamente
+            throw new NotImplementedException("Delete será implementado quando migrar para interface");
+        }
+
+        public async Task<bool> DocumentExistsAsync(string id)
+        {
+            try
+            {
+                var doc = await _textData.GetById(id);
+                return doc != null;
+            }
+            catch
+            {
+                return false;
+            }
+        }
+
+        public async Task<DocumentOutput?> GetDocumentAsync(string id)
+        {
+            try
+            {
+                var doc = await _textData.GetById(id);
+                if (doc == null) return null;
+
+                return new DocumentOutput
+                {
+                    Id = doc.Id,
+                    Title = doc.Titulo,
+                    Content = doc.Conteudo,
+                    ProjectId = doc.ProjetoId,
+                    Embedding = doc.Embedding,
+                    CreatedAt = DateTime.UtcNow, // MongoDB não tem essa info no modelo atual
+                    UpdatedAt = DateTime.UtcNow
+                };
+            }
+            catch
+            {
+                return null;
+            }
+        }
+
+        public async Task<List<DocumentOutput>> GetDocumentsByProjectAsync(string projectId)
+        {
+            var docs = await _textData.GetByPorjectId(projectId);
+            return docs.Select(doc => new DocumentOutput
+            {
+                Id = doc.Id,
+                Title = doc.Titulo,
+                Content = doc.Conteudo,
+                ProjectId = doc.ProjetoId,
+                Embedding = doc.Embedding,
+                CreatedAt = DateTime.UtcNow,
+                UpdatedAt = DateTime.UtcNow
+            }).ToList();
+        }
+
+        public async Task<int> GetDocumentCountAsync(string? projectId = null)
+        {
+            if (string.IsNullOrEmpty(projectId))
+            {
+                var all = await _textData.GetAll();
+                return all.Count();
+            }
+            else
+            {
+                var byProject = await _textData.GetByPorjectId(projectId);
+                return byProject.Count();
+            }
+        }
+
+        public async Task<List<string>> SaveDocumentsBatchAsync(List<DocumentInput> documents)
+        {
+            var ids = new List<string>();
+            foreach (var doc in documents)
+            {
+                var id = await SaveDocumentAsync(doc);
+                ids.Add(id);
+            }
+            return ids;
+        }
+
+        public async Task DeleteDocumentsBatchAsync(List<string> ids)
+        {
+            foreach (var id in ids)
+            {
+                await DeleteDocumentAsync(id);
+            }
+        }
+
+        public async Task<Dictionary<string, object>> GetProviderStatsAsync()
+        {
+            var totalDocs = await GetDocumentCountAsync();
+            return new Dictionary<string, object>
+            {
+                ["provider"] = "MongoDB",
+                ["total_documents"] = totalDocs,
+                ["health"] = "ok",
+                ["last_check"] = DateTime.UtcNow
+            };
+        }
+    }
+}
+#pragma warning restore SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.

Data/QdrantProjectDataRepository.cs

@@ -0,0 +1,269 @@
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+using System.Text;
+using System.Text.Json;
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+using Google.Protobuf;
+
+namespace ChatRAG.Data
+{
+    public class QdrantProjectDataRepository : IProjectDataRepository
+    {
+        private readonly HttpClient _httpClient;
+        private readonly string _collectionName;
+        private readonly ILogger<QdrantProjectDataRepository> _logger;
+        private readonly QdrantClient _qdrantClient;
+        private volatile bool _collectionInitialized = false;
+        private readonly SemaphoreSlim _initializationSemaphore = new(1, 1);
+
+        public QdrantProjectDataRepository(
+            IOptions<VectorDatabaseSettings> settings,
+            HttpClient httpClient,
+            ILogger<QdrantProjectDataRepository> logger)
+        {
+            var qdrantSettings = settings.Value.Qdrant ?? throw new ArgumentNullException("Qdrant settings not configured");
+            _httpClient = httpClient;
+            _httpClient.BaseAddress = new Uri($"http://{qdrantSettings.Host}:{qdrantSettings.Port}");
+            _collectionName = qdrantSettings.GroupsCollectionName;
+            _logger = logger;
+
+            // Inicializa o QdrantClient - use GRPC (porta 6334) para melhor performance
+            _qdrantClient = new QdrantClient(qdrantSettings.Host, port: 6334, https: false);
+
+            InitializeAsync().GetAwaiter().GetResult();
+        }
+
+        private async Task InitializeAsync()
+        {
+            try
+            {
+                if (_collectionInitialized) return;
+
+                await _initializationSemaphore.WaitAsync();
+
+                var exists = await _qdrantClient.CollectionExistsAsync(_collectionName);
+                if (!exists)
+                {
+                    await CreateProjectsCollection();
+                }
+                _collectionInitialized = true;
+
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao inicializar collection de projetos no Qdrant");
+            }
+            finally
+            {
+                _initializationSemaphore.Release();
+            }
+        }
+
+        public async Task<List<Project>> GetAsync()
+        {
+            try
+            {
+                //var scrollRequest = new ScrollPoints
+                //{
+                //    CollectionName = _collectionName,
+                //    Filter = new Filter(), // Filtro vazio
+                //    Limit = 1000,
+                //    WithPayload = true,
+                //    WithVectors = false
+                //};
+
+                //var result = await _qdrantClient.ScrollAsync(_collectionName, scrollRequest);
+                var result = await _qdrantClient.ScrollAsync(_collectionName, new Filter(), 1000, null, true, false);
+
+                return result.Result.Select(ConvertToProject)
+                    .Where(p => p != null)
+                    .ToList()!;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar projetos do Qdrant");
+                return new List<Project>();
+            }
+        }
+
+        public async Task<Project?> GetAsync(string id)
+        {
+            try
+            {
+                var points = await _qdrantClient.RetrieveAsync(
+                    _collectionName,
+                    Guid.Parse(id),
+                    withPayload: true,
+                    withVectors: false
+                );
+
+                var point = points.FirstOrDefault();
+                return point != null ? ConvertToProject(point) : null;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar projeto {Id} no Qdrant", id);
+                return null;
+            }
+        }
+
+        public async Task CreateAsync(Project newProject)
+        {
+            try
+            {
+                var id = string.IsNullOrEmpty(newProject.Id) ? Guid.NewGuid().ToString() : newProject.Id;
+                newProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = new PointId { Uuid= id },
+                    Vectors = new float[384], // Vector dummy para projetos
+                    Payload =
+                    {
+                        ["id"] = newProject.Id,
+                        ["nome"] = newProject.Nome,
+                        ["descricao"] = newProject.Descricao,
+                        ["created_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao criar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task UpdateAsync(string id, Project updatedProject)
+        {
+            try
+            {
+                updatedProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = new PointId { Uuid = id },
+                    Vectors = new float[384], // Vector dummy
+                    Payload =
+                    {
+                        ["id"] = updatedProject.Id,
+                        ["nome"] = updatedProject.Nome,
+                        ["descricao"] = updatedProject.Descricao,
+                        ["updated_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar projeto {Id} no Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task SaveAsync(Project project)
+        {
+            try
+            {
+                if (string.IsNullOrEmpty(project.Id))
+                {
+                    await CreateAsync(project);
+                }
+                else
+                {
+                    var existing = await GetAsync(project.Id);
+                    if (existing == null)
+                    {
+                        await CreateAsync(project);
+                    }
+                    else
+                    {
+                        await UpdateAsync(project.Id, project);
+                    }
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task RemoveAsync(string id)
+        {
+            try
+            {
+                await _qdrantClient.DeleteAsync(
+                    _collectionName,
+                    new[] { new PointId { Uuid = id }.Num }
+                );
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao remover projeto {Id} do Qdrant", id);
+                throw;
+            }
+        }
+
+        private async Task CreateProjectsCollection()
+        {
+            var vectorParams = new VectorParams
+            {
+                Size = 384,
+                Distance = Distance.Cosine
+            };
+
+            await _qdrantClient.CreateCollectionAsync(_collectionName, vectorParams);
+
+            _logger.LogInformation("Collection de projetos '{CollectionName}' criada no Qdrant", _collectionName);
+        }
+
+        private static Project? ConvertToProject(RetrievedPoint point)
+        {
+            try
+            {
+                if (point.Payload == null) return null;
+
+                return new Project
+                {
+                    Id = point.Payload.TryGetValue("id", out var idValue) ? idValue.StringValue : point.Id.ToString(),
+                    Nome = point.Payload.TryGetValue("nome", out var nomeValue) ? nomeValue.StringValue : "",
+                    Descricao = point.Payload.TryGetValue("descricao", out var descValue) ? descValue.StringValue : ""
+                };
+            }
+            catch
+            {
+                return null;
+            }
+        }
+    }
+
+    public class QdrantScrollResult
+    {
+        public QdrantScrollData? result { get; set; }
+    }
+
+    public class QdrantScrollData
+    {
+        public QdrantPoint[]? points { get; set; }
+    }
+
+    public class QdrantPointResult
+    {
+        public QdrantPoint? result { get; set; }
+    }
+
+    public class QdrantPoint
+    {
+        public string? id { get; set; }
+        public Dictionary<string, object>? payload { get; set; }
+    }
+}

Data/TextData.cs

@@ -1,5 +1,6 @@
 using ChatRAG.Data;
 using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
 using Microsoft.SemanticKernel;
 using Microsoft.SemanticKernel.Embeddings;
 using System.Text;
@@ -8,17 +9,23 @@ using System.Text;
 
 namespace ChatApi.Data
 {
-    public class TextData
+    public class TextData : ITextDataService
     {
         private readonly ITextEmbeddingGenerationService _textEmbeddingGenerationService;
         private readonly TextDataRepository _textDataService;
-         
+
         public TextData(ITextEmbeddingGenerationService textEmbeddingGenerationService, TextDataRepository textDataService)
         {
             _textEmbeddingGenerationService = textEmbeddingGenerationService;
             _textDataService = textDataService;
         }
 
+        public string ProviderName => "MongoDB";
+
+        // ========================================
+        // MÉTODOS ORIGINAIS (já implementados)
+        // ========================================
+
         public async Task SalvarTextoComEmbeddingNoMongoDB(string textoCompleto, string projectId)
         {
             var textoArray = new List<string>();
@@ -47,7 +54,7 @@ namespace ChatApi.Data
                 }
             }
 
-            foreach(var item in textoArray)
+            foreach (var item in textoArray)
             {
                 await SalvarNoMongoDB(title, item, projectId);
             }
@@ -55,7 +62,7 @@ namespace ChatApi.Data
 
         public async Task SalvarNoMongoDB(string titulo, string texto, string projectId)
         {
-            await SalvarNoMongoDB(null, titulo, texto);
+            await SalvarNoMongoDB(null, titulo, texto, projectId);
         }
 
         public async Task SalvarNoMongoDB(string? id, string titulo, string texto, string projectId)
@@ -67,12 +74,13 @@ namespace ChatApi.Data
             // Converter embedding para um formato serializável (como um array de floats)
             var embeddingArray = embedding.ToArray().Select(e => (double)e).ToArray();
 
-            var exists = id!=null ? await this.GetById(id) : null;
+            var exists = id != null ? await this.GetById(id) : null;
 
             if (exists == null)
             {
                 var documento = new TextoComEmbedding
                 {
+                    Id = id ?? Guid.NewGuid().ToString(),
                     Titulo = titulo,
                     Conteudo = texto,
                     ProjetoId = projectId,
@@ -85,14 +93,14 @@ namespace ChatApi.Data
             {
                 var documento = new TextoComEmbedding
                 {
-                    Id = id,
+                    Id = id!,
                     Titulo = titulo,
                     Conteudo = texto,
                     ProjetoId = projectId,
                     Embedding = embeddingArray
                 };
 
-                await _textDataService.UpdateAsync(id, documento);
+                await _textDataService.UpdateAsync(id!, documento);
             }
         }
 
@@ -108,8 +116,173 @@ namespace ChatApi.Data
 
         public async Task<TextoComEmbedding> GetById(string id)
         {
-            return await _textDataService.GetAsync(id);
+            return (await _textDataService.GetAsync(id))!;
+        }
+
+        // ========================================
+        // MÉTODOS NOVOS DA INTERFACE (implementação completa)
+        // ========================================
+
+        public async Task<string> SaveDocumentAsync(DocumentInput document)
+        {
+            var id = document.Id ?? Guid.NewGuid().ToString();
+            await SalvarNoMongoDB(id, document.Title, document.Content, document.ProjectId);
+            return id;
+        }
+
+        public async Task UpdateDocumentAsync(string id, DocumentInput document)
+        {
+            await SalvarNoMongoDB(id, document.Title, document.Content, document.ProjectId);
+        }
+
+        public async Task DeleteDocumentAsync(string id)
+        {
+            await _textDataService.RemoveAsync(id);
+        }
+
+        public async Task<bool> DocumentExistsAsync(string id)
+        {
+            try
+            {
+                var doc = await GetById(id);
+                return doc != null;
+            }
+            catch
+            {
+                return false;
+            }
+        }
+
+        public async Task<DocumentOutput?> GetDocumentAsync(string id)
+        {
+            try
+            {
+                var doc = await GetById(id);
+                if (doc == null) return null;
+
+                return new DocumentOutput
+                {
+                    Id = doc.Id,
+                    Title = doc.Titulo,
+                    Content = doc.Conteudo,
+                    ProjectId = doc.ProjetoId,
+                    Embedding = doc.Embedding,
+                    CreatedAt = DateTime.UtcNow,
+                    UpdatedAt = DateTime.UtcNow,
+                    Metadata = new Dictionary<string, object>
+                    {
+                        ["source"] = "MongoDB",
+                        ["has_embedding"] = doc.Embedding != null,
+                        ["embedding_size"] = doc.Embedding?.Length ?? 0
+                    }
+                };
+            }
+            catch
+            {
+                return null;
+            }
+        }
+
+        public async Task<List<DocumentOutput>> GetDocumentsByProjectAsync(string projectId)
+        {
+            var docs = await GetByPorjectId(projectId);
+            return docs.Select(doc => new DocumentOutput
+            {
+                Id = doc.Id,
+                Title = doc.Titulo,
+                Content = doc.Conteudo,
+                ProjectId = doc.ProjetoId,
+                Embedding = doc.Embedding,
+                CreatedAt = DateTime.UtcNow,
+                UpdatedAt = DateTime.UtcNow,
+                Metadata = new Dictionary<string, object>
+                {
+                    ["source"] = "MongoDB",
+                    ["has_embedding"] = doc.Embedding != null,
+                    ["embedding_size"] = doc.Embedding?.Length ?? 0
+                }
+            }).ToList();
+        }
+
+        public async Task<int> GetDocumentCountAsync(string? projectId = null)
+        {
+            if (string.IsNullOrEmpty(projectId))
+            {
+                var all = await GetAll();
+                return all.Count();
+            }
+            else
+            {
+                var byProject = await GetByPorjectId(projectId);
+                return byProject.Count();
+            }
+        }
+
+        public async Task<List<string>> SaveDocumentsBatchAsync(List<DocumentInput> documents)
+        {
+            var ids = new List<string>();
+
+            foreach (var doc in documents)
+            {
+                var id = await SaveDocumentAsync(doc);
+                ids.Add(id);
+            }
+
+            return ids;
+        }
+
+        public async Task DeleteDocumentsBatchAsync(List<string> ids)
+        {
+            foreach (var id in ids)
+            {
+                await DeleteDocumentAsync(id);
+            }
+        }
+
+        public async Task<Dictionary<string, object>> GetProviderStatsAsync()
+        {
+            try
+            {
+                var totalDocs = await GetDocumentCountAsync();
+                var allDocs = await GetAll();
+
+                var docsWithEmbedding = allDocs.Count(d => d.Embedding != null && d.Embedding.Length > 0);
+                var avgContentLength = allDocs.Any() ? allDocs.Average(d => d.Conteudo?.Length ?? 0) : 0;
+
+                var projectStats = allDocs
+                    .GroupBy(d => d.ProjetoId)
+                    .ToDictionary(
+                        g => g.Key ?? "unknown",
+                        g => g.Count()
+                    );
+
+                return new Dictionary<string, object>
+                {
+                    ["provider"] = "MongoDB",
+                    ["total_documents"] = totalDocs,
+                    ["documents_with_embedding"] = docsWithEmbedding,
+                    ["embedding_coverage"] = totalDocs > 0 ? (double)docsWithEmbedding / totalDocs : 0,
+                    ["average_content_length"] = Math.Round(avgContentLength, 1),
+                    ["projects_count"] = projectStats.Count,
+                    ["documents_by_project"] = projectStats,
+                    ["health"] = "ok",
+                    ["last_check"] = DateTime.UtcNow,
+                    ["connection_status"] = "connected"
+                };
+            }
+            catch (Exception ex)
+            {
+                return new Dictionary<string, object>
+                {
+                    ["provider"] = "MongoDB",
+                    ["health"] = "error",
+                    ["error"] = ex.Message,
+                    ["last_check"] = DateTime.UtcNow,
+                    ["connection_status"] = "error"
+                };
+            }
         }
     }
 }
-#pragma warning restore SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+
+#pragma warning restore SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.

Data/TextDataRepository.cs

@@ -1,5 +1,6 @@
 using ChatApi;
 using ChatRAG.Models;
+using ChatRAG.Settings.ChatRAG.Configuration;
 using Microsoft.Extensions.Options;
 using MongoDB.Bson;
 using MongoDB.Driver;
@@ -11,16 +12,16 @@ namespace ChatRAG.Data
         private readonly IMongoCollection<TextoComEmbedding> _textsCollection;
 
         public TextDataRepository(
-            IOptions<DomvsDatabaseSettings> bookStoreDatabaseSettings)
+            IOptions<VectorDatabaseSettings> vectorStoreDatabaseSettings)
         {
             var mongoClient = new MongoClient(
-                bookStoreDatabaseSettings.Value.ConnectionString);
+                vectorStoreDatabaseSettings.Value.MongoDB.ConnectionString);
 
             var mongoDatabase = mongoClient.GetDatabase(
-                bookStoreDatabaseSettings.Value.DatabaseName);
+                vectorStoreDatabaseSettings.Value.MongoDB.DatabaseName);
 
             _textsCollection = mongoDatabase.GetCollection<TextoComEmbedding>(
-                bookStoreDatabaseSettings.Value.TextCollectionName);
+                vectorStoreDatabaseSettings.Value.MongoDB.TextCollectionName);
         }
 
         public IMongoCollection<TextoComEmbedding> GetCollection()
@@ -32,7 +33,7 @@ namespace ChatRAG.Data
             await _textsCollection.Find(_ => true).ToListAsync();
 
         public async Task<List<TextoComEmbedding>> GetByProjectIdAsync(string projectId) =>
-            await _textsCollection.Find(s => s.ProjetoId == ObjectId.Parse(projectId).ToString()).ToListAsync();
+            await _textsCollection.Find(s => s.ProjetoId == projectId).ToListAsync();
 
         public async Task<TextoComEmbedding?> GetAsync(string id) =>
             await _textsCollection.Find(x => x.Id == id).FirstOrDefaultAsync();

Data/UserDataRepository.cs

@@ -1,4 +1,5 @@
 using ChatApi.Models;
+using ChatRAG.Settings.ChatRAG.Configuration;
 using Microsoft.Extensions.Options;
 using MongoDB.Driver;
 
@@ -9,16 +10,16 @@ namespace ChatApi
         private readonly IMongoCollection<UserData> _userCollection;
 
         public UserDataRepository(
-            IOptions<DomvsDatabaseSettings> bookStoreDatabaseSettings)
+            IOptions<VectorDatabaseSettings> vectorStoreDatabaseSettings)
         {
             var mongoClient = new MongoClient(
-                bookStoreDatabaseSettings.Value.ConnectionString);
+                vectorStoreDatabaseSettings.Value.MongoDB.ConnectionString);
 
             var mongoDatabase = mongoClient.GetDatabase(
-                bookStoreDatabaseSettings.Value.DatabaseName);
+                vectorStoreDatabaseSettings.Value.MongoDB.DatabaseName);
 
             _userCollection = mongoDatabase.GetCollection<UserData>(
-                bookStoreDatabaseSettings.Value.UserDataName);
+                vectorStoreDatabaseSettings.Value.MongoDB.UserDataName);
         }
 
         public async Task<List<UserData>> GetAsync() =>

Data/hnwhoaao.xfh~

@@ -0,0 +1,263 @@
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+using System.Text;
+using System.Text.Json;
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+namespace ChatRAG.Data
+{
+    public class QdrantProjectDataRepository : IProjectDataRepository
+    {
+        private readonly HttpClient _httpClient;
+        private readonly string _collectionName;
+        private readonly ILogger<QdrantProjectDataRepository> _logger;
+        private readonly QdrantClient _qdrantClient;
+        private volatile bool _collectionInitialized = false;
+        private readonly SemaphoreSlim _initializationSemaphore = new(1, 1);
+
+        public QdrantProjectDataRepository(
+            IOptions<VectorDatabaseSettings> settings,
+            HttpClient httpClient,
+            ILogger<QdrantProjectDataRepository> logger)
+        {
+            var qdrantSettings = settings.Value.Qdrant ?? throw new ArgumentNullException("Qdrant settings not configured");
+            _httpClient = httpClient;
+            _httpClient.BaseAddress = new Uri($"http://{qdrantSettings.Host}:{qdrantSettings.Port}");
+            _collectionName = qdrantSettings.GroupsCollectionName;
+            _logger = logger;
+
+            // Inicializa o QdrantClient - use GRPC (porta 6334) para melhor performance
+            _qdrantClient = new QdrantClient(qdrantSettings.Host, port: 6334, https: false);
+
+            InitializeAsync().GetAwaiter().GetResult();
+        }
+
+        private async Task EnsureInitializedAsync()
+        {
+            try
+            {
+                if (_collectionInitialized) return;
+
+                await _initializationSemaphore.WaitAsync();
+
+                var exists = await _qdrantClient.CollectionExistsAsync(_collectionName);
+                if (!exists)
+                {
+                    await CreateProjectsCollection();
+                }
+                _collectionInitialized = true;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao inicializar collection de projetos no Qdrant");
+            }
+        }
+
+        public async Task<List<Project>> GetAsync()
+        {
+            try
+            {
+                //var scrollRequest = new ScrollPoints
+                //{
+                //    CollectionName = _collectionName,
+                //    Filter = new Filter(), // Filtro vazio
+                //    Limit = 1000,
+                //    WithPayload = true,
+                //    WithVectors = false
+                //};
+
+                //var result = await _qdrantClient.ScrollAsync(_collectionName, scrollRequest);
+                var result = await _qdrantClient.ScrollAsync(_collectionName, new Filter(), 1000, null, true, false);
+
+                return result.Result.Select(ConvertToProject)
+                    .Where(p => p != null)
+                    .ToList()!;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar projetos do Qdrant");
+                return new List<Project>();
+            }
+        }
+
+        public async Task<Project?> GetAsync(string id)
+        {
+            try
+            {
+                var points = await _qdrantClient.RetrieveAsync(
+                    _collectionName,
+                    new[] { PointId.Parser.ParseFrom(Encoding.ASCII.GetBytes(id)) },
+                    withPayload: true,
+                    withVectors: false
+                );
+
+                var point = points.FirstOrDefault();
+                return point != null ? ConvertToProject(point) : null;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar projeto {Id} no Qdrant", id);
+                return null;
+            }
+        }
+
+        public async Task CreateAsync(Project newProject)
+        {
+            try
+            {
+                var id = string.IsNullOrEmpty(newProject.Id) ? Guid.NewGuid().ToString() : newProject.Id;
+                newProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.Parser.ParseFrom(Encoding.ASCII.GetBytes(id)),
+                    Vectors = new float[384], // Vector dummy para projetos
+                    Payload =
+                    {
+                        ["id"] = newProject.Id,
+                        ["nome"] = newProject.Nome,
+                        ["descricao"] = newProject.Descricao,
+                        ["created_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao criar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task UpdateAsync(string id, Project updatedProject)
+        {
+            try
+            {
+                updatedProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.Parser.ParseFrom(Encoding.ASCII.GetBytes(id)),
+                    Vectors = new float[384], // Vector dummy
+                    Payload =
+                    {
+                        ["id"] = updatedProject.Id,
+                        ["nome"] = updatedProject.Nome,
+                        ["descricao"] = updatedProject.Descricao,
+                        ["updated_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar projeto {Id} no Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task SaveAsync(Project project)
+        {
+            try
+            {
+                if (string.IsNullOrEmpty(project.Id))
+                {
+                    await CreateAsync(project);
+                }
+                else
+                {
+                    var existing = await GetAsync(project.Id);
+                    if (existing == null)
+                    {
+                        await CreateAsync(project);
+                    }
+                    else
+                    {
+                        await UpdateAsync(project.Id, project);
+                    }
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task RemoveAsync(string id)
+        {
+            try
+            {
+                await _qdrantClient.DeleteAsync(
+                    _collectionName,
+                    new[] { PointId.Parser.ParseFrom(Encoding.ASCII.GetBytes(id)).Num }
+                );
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao remover projeto {Id} do Qdrant", id);
+                throw;
+            }
+        }
+
+        private async Task CreateProjectsCollection()
+        {
+            var vectorParams = new VectorParams
+            {
+                Size = 384,
+                Distance = Distance.Cosine
+            };
+
+            await _qdrantClient.CreateCollectionAsync(_collectionName, vectorParams);
+
+            _logger.LogInformation("Collection de projetos '{CollectionName}' criada no Qdrant", _collectionName);
+        }
+
+        private static Project? ConvertToProject(RetrievedPoint point)
+        {
+            try
+            {
+                if (point.Payload == null) return null;
+
+                return new Project
+                {
+                    Id = point.Payload.TryGetValue("id", out var idValue) ? idValue.StringValue : point.Id.ToString(),
+                    Nome = point.Payload.TryGetValue("nome", out var nomeValue) ? nomeValue.StringValue : "",
+                    Descricao = point.Payload.TryGetValue("descricao", out var descValue) ? descValue.StringValue : ""
+                };
+            }
+            catch
+            {
+                return null;
+            }
+        }
+    }
+
+    public class QdrantScrollResult
+    {
+        public QdrantScrollData? result { get; set; }
+    }
+
+    public class QdrantScrollData
+    {
+        public QdrantPoint[]? points { get; set; }
+    }
+
+    public class QdrantPointResult
+    {
+        public QdrantPoint? result { get; set; }
+    }
+
+    public class QdrantPoint
+    {
+        public string? id { get; set; }
+        public Dictionary<string, object>? payload { get; set; }
+    }
+}

Data/wgbnjwfg.nr3~

@@ -0,0 +1,268 @@
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+using System.Text;
+using System.Text.Json;
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+namespace ChatRAG.Data
+{
+    public class QdrantProjectDataRepository : IProjectDataRepository
+    {
+        private readonly HttpClient _httpClient;
+        private readonly string _collectionName;
+        private readonly ILogger<QdrantProjectDataRepository> _logger;
+        private readonly QdrantClient _qdrantClient;
+        private volatile bool _collectionInitialized = false;
+        private readonly SemaphoreSlim _initializationSemaphore = new(1, 1);
+
+        public QdrantProjectDataRepository(
+            IOptions<VectorDatabaseSettings> settings,
+            HttpClient httpClient,
+            ILogger<QdrantProjectDataRepository> logger)
+        {
+            var qdrantSettings = settings.Value.Qdrant ?? throw new ArgumentNullException("Qdrant settings not configured");
+            _httpClient = httpClient;
+            _httpClient.BaseAddress = new Uri($"http://{qdrantSettings.Host}:{qdrantSettings.Port}");
+            _collectionName = qdrantSettings.GroupsCollectionName;
+            _logger = logger;
+
+            // Inicializa o QdrantClient - use GRPC (porta 6334) para melhor performance
+            _qdrantClient = new QdrantClient(qdrantSettings.Host, port: 6334, https: false);
+
+            InitializeAsync().GetAwaiter().GetResult();
+        }
+
+        private async Task InitializeAsync()
+        {
+            try
+            {
+                if (_collectionInitialized) return;
+
+                await _initializationSemaphore.WaitAsync();
+
+                var exists = await _qdrantClient.CollectionExistsAsync(_collectionName);
+                if (!exists)
+                {
+                    await CreateProjectsCollection();
+                }
+                _collectionInitialized = true;
+
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao inicializar collection de projetos no Qdrant");
+            }
+            finally
+            {
+                _initializationSemaphore.Release();
+            }
+        }
+
+        public async Task<List<Project>> GetAsync()
+        {
+            try
+            {
+                //var scrollRequest = new ScrollPoints
+                //{
+                //    CollectionName = _collectionName,
+                //    Filter = new Filter(), // Filtro vazio
+                //    Limit = 1000,
+                //    WithPayload = true,
+                //    WithVectors = false
+                //};
+
+                //var result = await _qdrantClient.ScrollAsync(_collectionName, scrollRequest);
+                var result = await _qdrantClient.ScrollAsync(_collectionName, new Filter(), 1000, null, true, false);
+
+                return result.Result.Select(ConvertToProject)
+                    .Where(p => p != null)
+                    .ToList()!;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar projetos do Qdrant");
+                return new List<Project>();
+            }
+        }
+
+        public async Task<Project?> GetAsync(string id)
+        {
+            try
+            {
+                var points = await _qdrantClient.RetrieveAsync(
+                    _collectionName,
+                    new[] { PointId.Parser.ParseFrom(Encoding.ASCII.GetBytes(id)) },
+                    withPayload: true,
+                    withVectors: false
+                );
+
+                var point = points.FirstOrDefault();
+                return point != null ? ConvertToProject(point) : null;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar projeto {Id} no Qdrant", id);
+                return null;
+            }
+        }
+
+        public async Task CreateAsync(Project newProject)
+        {
+            try
+            {
+                var id = string.IsNullOrEmpty(newProject.Id) ? Guid.NewGuid().ToString() : newProject.Id;
+                newProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.Parser.ParseFrom(Encoding.ASCII.GetBytes(id)),
+                    Vectors = new float[384], // Vector dummy para projetos
+                    Payload =
+                    {
+                        ["id"] = newProject.Id,
+                        ["nome"] = newProject.Nome,
+                        ["descricao"] = newProject.Descricao,
+                        ["created_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao criar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task UpdateAsync(string id, Project updatedProject)
+        {
+            try
+            {
+                updatedProject.Id = id;
+
+                var point = new PointStruct
+                {
+                    Id = PointId.Parser.ParseFrom(Encoding.ASCII.GetBytes(id)),
+                    Vectors = new float[384], // Vector dummy
+                    Payload =
+                    {
+                        ["id"] = updatedProject.Id,
+                        ["nome"] = updatedProject.Nome,
+                        ["descricao"] = updatedProject.Descricao,
+                        ["updated_at"] = DateTime.UtcNow.ToString("O"),
+                        ["entity_type"] = "project"
+                    }
+                };
+
+                await _qdrantClient.UpsertAsync(_collectionName, new[] { point });
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar projeto {Id} no Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task SaveAsync(Project project)
+        {
+            try
+            {
+                if (string.IsNullOrEmpty(project.Id))
+                {
+                    await CreateAsync(project);
+                }
+                else
+                {
+                    var existing = await GetAsync(project.Id);
+                    if (existing == null)
+                    {
+                        await CreateAsync(project);
+                    }
+                    else
+                    {
+                        await UpdateAsync(project.Id, project);
+                    }
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar projeto no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task RemoveAsync(string id)
+        {
+            try
+            {
+                await _qdrantClient.DeleteAsync(
+                    _collectionName,
+                    new[] { PointId.Parser.ParseFrom(Encoding.ASCII.GetBytes(id)).Num }
+                );
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao remover projeto {Id} do Qdrant", id);
+                throw;
+            }
+        }
+
+        private async Task CreateProjectsCollection()
+        {
+            var vectorParams = new VectorParams
+            {
+                Size = 384,
+                Distance = Distance.Cosine
+            };
+
+            await _qdrantClient.CreateCollectionAsync(_collectionName, vectorParams);
+
+            _logger.LogInformation("Collection de projetos '{CollectionName}' criada no Qdrant", _collectionName);
+        }
+
+        private static Project? ConvertToProject(RetrievedPoint point)
+        {
+            try
+            {
+                if (point.Payload == null) return null;
+
+                return new Project
+                {
+                    Id = point.Payload.TryGetValue("id", out var idValue) ? idValue.StringValue : point.Id.ToString(),
+                    Nome = point.Payload.TryGetValue("nome", out var nomeValue) ? nomeValue.StringValue : "",
+                    Descricao = point.Payload.TryGetValue("descricao", out var descValue) ? descValue.StringValue : ""
+                };
+            }
+            catch
+            {
+                return null;
+            }
+        }
+    }
+
+    public class QdrantScrollResult
+    {
+        public QdrantScrollData? result { get; set; }
+    }
+
+    public class QdrantScrollData
+    {
+        public QdrantPoint[]? points { get; set; }
+    }
+
+    public class QdrantPointResult
+    {
+        public QdrantPoint? result { get; set; }
+    }
+
+    public class QdrantPoint
+    {
+        public string? id { get; set; }
+        public Dictionary<string, object>? payload { get; set; }
+    }
+}

DomvsDatabaseSettings.cs

@@ -1,16 +0,0 @@
-namespace ChatApi
-{
-    public class DomvsDatabaseSettings
-    {
-        public string ConnectionString { get; set; } = null!;
-
-        public string DatabaseName { get; set; } = null!;
-
-        public string TextCollectionName { get; set; } = null!;
-
-        public string UserDataName { get; set; } = null!;
-
-        public string ProjectCollectionName { get; set; } = null!;
-
-    }
-}

Extensions/ServiceCollectionExtensions.cs

@@ -0,0 +1,100 @@
+using ChatApi.Data;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Services;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.ResponseService;
+using ChatRAG.Services.SearchVectors;
+using ChatRAG.Services.TextServices;
+using ChatRAG.Settings;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+using Qdrant.Client;
+
+namespace ChatRAG.Extensions
+{
+    public static class ServiceCollectionExtensions
+    {
+        /// <summary>
+        /// Registra o sistema completo de Vector Database
+        /// </summary>
+        public static IServiceCollection AddVectorDatabase(
+            this IServiceCollection services,
+            IConfiguration configuration)
+        {
+            // Registra e valida configurações
+            services.Configure<VectorDatabaseSettings>(
+                configuration.GetSection("VectorDatabase"));
+
+            services.AddSingleton<IValidateOptions<VectorDatabaseSettings>,
+                ChatRAG.Settings.VectorDatabaseSettingsValidator>();
+
+            // Registra factory principal
+            services.AddScoped<IVectorDatabaseFactory, VectorDatabaseFactory>();
+
+            // Registra implementações de todos os providers
+            services.AddMongoDbProvider();
+            services.AddQdrantProvider(); // 👈 Agora ativo!
+
+            // Registra interfaces principais usando factory
+            services.AddScoped<IVectorSearchService>(provider =>
+            {
+                var factory = provider.GetRequiredService<IVectorDatabaseFactory>();
+                return factory.CreateVectorSearchService();
+            });
+
+            services.AddScoped<ITextDataService>(provider =>
+            {
+                var factory = provider.GetRequiredService<IVectorDatabaseFactory>();
+                return factory.CreateTextDataService();
+            });
+
+            services.AddScoped<IResponseService>(provider =>
+            {
+                var factory = provider.GetRequiredService<IVectorDatabaseFactory>();
+                return factory.CreateResponseService();
+            });
+
+            return services;
+        }
+
+        /// <summary>
+        /// Registra implementações MongoDB (suas classes atuais)
+        /// </summary>
+        private static IServiceCollection AddMongoDbProvider(this IServiceCollection services)
+        {
+            services.AddScoped<TextData>(); // Implementa ITextDataService
+            services.AddScoped<TextDataRepository>();
+            services.AddScoped<ResponseRAGService>(); // Implementa IResponseService
+            services.AddScoped<MongoVectorSearchService>(); // Wrapper para IVectorSearchService
+
+            return services;
+        }
+
+        /// <summary>
+        /// Registra implementações Qdrant
+        /// </summary>
+        private static IServiceCollection AddQdrantProvider(this IServiceCollection services)
+        {
+            // ✅ Cliente Qdrant configurado
+            services.AddScoped<QdrantClient>(provider =>
+            {
+                var settings = provider.GetRequiredService<IOptions<VectorDatabaseSettings>>();
+                var qdrantSettings = settings.Value.Qdrant;
+
+                return new QdrantClient(
+                    host: qdrantSettings.Host,
+                    port: qdrantSettings.Port,
+                    https: qdrantSettings.UseTls
+                );
+            });
+
+            // ✅ Serviços Qdrant
+            services.AddScoped<QdrantVectorSearchService>();
+            services.AddScoped<QdrantTextDataService>();
+            services.AddScoped<QdrantResponseService>();
+
+            return services;
+        }
+    }
+}

Models/DocumentInput.cs

@@ -0,0 +1,43 @@
+namespace ChatRAG.Models
+{
+    /// <summary>
+    /// Modelo para entrada de dados (CREATE/UPDATE)
+    /// </summary>
+    public class DocumentInput
+    {
+        public string? Id { get; set; }
+        public string Title { get; set; } = string.Empty;
+        public string Content { get; set; } = string.Empty;
+        public string ProjectId { get; set; } = string.Empty;
+        public Dictionary<string, object>? Metadata { get; set; }
+        public DateTime? CreatedAt { get; set; }
+        public DateTime? UpdatedAt { get; set; }
+
+        public static DocumentInput FromTextoComEmbedding(TextoComEmbedding texto)
+        {
+            return new DocumentInput
+            {
+                Id = texto.Id,
+                Title = texto.Titulo,
+                Content = texto.Conteudo,
+                ProjectId = texto.ProjetoId,
+                CreatedAt = DateTime.UtcNow,
+                UpdatedAt = DateTime.UtcNow
+            };
+        }
+
+        public DocumentInput WithMetadata(string key, object value)
+        {
+            Metadata ??= new Dictionary<string, object>();
+            Metadata[key] = value;
+            return this;
+        }
+
+        public bool IsValid()
+        {
+            return !string.IsNullOrWhiteSpace(Title) &&
+                   !string.IsNullOrWhiteSpace(Content) &&
+                   !string.IsNullOrWhiteSpace(ProjectId);
+        }
+    }
+}

Models/DocumentOutput.cs

@@ -0,0 +1,70 @@
+namespace ChatRAG.Models
+{
+    /// <summary>
+    /// Modelo para saída de dados (READ)
+    /// </summary>
+    public class DocumentOutput
+    {
+        public string Id { get; set; } = string.Empty;
+        public string Title { get; set; } = string.Empty;
+        public string Content { get; set; } = string.Empty;
+        public string ProjectId { get; set; } = string.Empty;
+        public Dictionary<string, object>? Metadata { get; set; }
+        public DateTime CreatedAt { get; set; }
+        public DateTime UpdatedAt { get; set; }
+        public double[]? Embedding { get; set; }
+
+        public TextoComEmbedding ToTextoComEmbedding()
+        {
+            return new TextoComEmbedding
+            {
+                Id = Id,
+                Titulo = Title,
+                Conteudo = Content,
+                ProjetoId = ProjectId,
+                Embedding = Embedding
+            };
+        }
+
+        public static DocumentOutput FromTextoComEmbedding(TextoComEmbedding texto)
+        {
+            return new DocumentOutput
+            {
+                Id = texto.Id,
+                Title = texto.Titulo,
+                Content = texto.Conteudo,
+                ProjectId = texto.ProjetoId,
+                Embedding = texto.Embedding,
+                CreatedAt = DateTime.UtcNow,
+                UpdatedAt = DateTime.UtcNow
+            };
+        }
+
+        public string GetContentPreview(int maxLength = 200)
+        {
+            if (string.IsNullOrEmpty(Content))
+                return string.Empty;
+
+            if (Content.Length <= maxLength)
+                return Content;
+
+            return Content.Substring(0, maxLength) + "...";
+        }
+
+        public bool HasEmbedding() => Embedding != null && Embedding.Length > 0;
+
+        public DocumentInput ToInput()
+        {
+            return new DocumentInput
+            {
+                Id = Id,
+                Title = Title,
+                Content = Content,
+                ProjectId = ProjectId,
+                Metadata = Metadata,
+                CreatedAt = CreatedAt,
+                UpdatedAt = UpdatedAt
+            };
+        }
+    }
+}

Models/MigrationResult.cs

@@ -0,0 +1,22 @@
+namespace ChatRAG.Models
+{
+    public class MigrationResult
+    {
+        public bool Success { get; set; }
+        public string Message { get; set; } = string.Empty;
+        public DateTime StartTime { get; set; }
+        public TimeSpan Duration { get; set; }
+        public int TotalDocuments { get; set; }
+        public int MigratedDocuments { get; set; }
+        public List<string> Errors { get; set; } = new();
+        public ValidationResult? ValidationResult { get; set; }
+
+        public double SuccessRate => TotalDocuments > 0 ? (double)MigratedDocuments / TotalDocuments : 0;
+    }
+
+    public class ValidationResult
+    {
+        public bool IsValid { get; set; }
+        public List<string> Issues { get; set; } = new();
+    }
+}

Models/Models.cs

@@ -0,0 +1,47 @@
+namespace ChatRAG.Models
+{
+    public class ResponseOptions
+    {
+        public int MaxContextDocuments { get; set; } = 3;
+        public double SimilarityThreshold { get; set; } = 0.3;
+        public bool IncludeSourceDetails { get; set; } = false;
+        public bool IncludeTiming { get; set; } = true;
+        public Dictionary<string, object>? Filters { get; set; }
+    }
+
+    public class ResponseResult
+    {
+        public string Content { get; set; } = string.Empty;
+        public List<SourceDocument> Sources { get; set; } = new();
+        public ResponseMetrics Metrics { get; set; } = new();
+        public string Provider { get; set; } = string.Empty;
+    }
+
+    public class SourceDocument
+    {
+        public string Id { get; set; } = string.Empty;
+        public string Title { get; set; } = string.Empty;
+        public string Content { get; set; } = string.Empty;
+        public double Similarity { get; set; }
+        public Dictionary<string, object>? Metadata { get; set; }
+    }
+
+    public class ResponseMetrics
+    {
+        public long TotalTimeMs { get; set; }
+        public long SearchTimeMs { get; set; }
+        public long LlmTimeMs { get; set; }
+        public int DocumentsFound { get; set; }
+        public int DocumentsUsed { get; set; }
+        public double AverageSimilarity { get; set; }
+    }
+
+    public class ResponseStats
+    {
+        public int TotalRequests { get; set; }
+        public double AverageResponseTime { get; set; }
+        public Dictionary<string, int> RequestsByProject { get; set; } = new();
+        public DateTime LastRequest { get; set; }
+        public string Provider { get; set; } = string.Empty;
+    }
+}

Models/VectorSearchResult.cs

@@ -0,0 +1,144 @@
+namespace ChatRAG.Models
+{
+    /// <summary>
+    /// Resultado padronizado de busca vetorial
+    /// Funciona com qualquer provider (MongoDB, Qdrant, etc.)
+    /// </summary>
+    public class VectorSearchResult
+    {
+        /// <summary>
+        /// ID único do documento
+        /// </summary>
+        public string Id { get; set; } = string.Empty;
+
+        /// <summary>
+        /// Título do documento
+        /// </summary>
+        public string Title { get; set; } = string.Empty;
+
+        /// <summary>
+        /// Conteúdo completo do documento
+        /// </summary>
+        public string Content { get; set; } = string.Empty;
+
+        /// <summary>
+        /// ID do projeto ao qual pertence
+        /// </summary>
+        public string ProjectId { get; set; } = string.Empty;
+
+        /// <summary>
+        /// Score de similaridade (0.0 a 1.0, onde 1.0 é idêntico)
+        /// </summary>
+        public double Score { get; set; }
+
+        /// <summary>
+        /// Embedding vetorial (opcional - nem sempre retornado por performance)
+        /// </summary>
+        public double[]? Embedding { get; set; }
+
+        /// <summary>
+        /// Metadados adicionais (tags, categoria, autor, etc.)
+        /// </summary>
+        public Dictionary<string, object>? Metadata { get; set; }
+
+        /// <summary>
+        /// Data de criação do documento
+        /// </summary>
+        public DateTime CreatedAt { get; set; }
+
+        /// <summary>
+        /// Data da última atualização
+        /// </summary>
+        public DateTime UpdatedAt { get; set; }
+
+        // ========================================
+        // INFORMAÇÕES DO PROVIDER
+        // ========================================
+
+        /// <summary>
+        /// Nome do provider que retornou este resultado (MongoDB, Qdrant, etc.)
+        /// </summary>
+        public string Provider { get; set; } = string.Empty;
+
+        /// <summary>
+        /// Informações específicas do provider (índices, shards, etc.)
+        /// </summary>
+        public Dictionary<string, object>? ProviderSpecific { get; set; }
+
+        // ========================================
+        // MÉTODOS DE CONVENIÊNCIA
+        // ========================================
+
+        /// <summary>
+        /// Preview do conteúdo (primeiros N caracteres)
+        /// </summary>
+        public string GetContentPreview(int maxLength = 200)
+        {
+            if (string.IsNullOrEmpty(Content))
+                return string.Empty;
+
+            if (Content.Length <= maxLength)
+                return Content;
+
+            return Content.Substring(0, maxLength) + "...";
+        }
+
+        /// <summary>
+        /// Score formatado como percentual
+        /// </summary>
+        public string GetScorePercentage()
+        {
+            return $"{Score:P1}"; // Ex: "85.3%"
+        }
+
+        /// <summary>
+        /// Indica se é um resultado relevante (score alto)
+        /// </summary>
+        public bool IsHighRelevance(double threshold = 0.7)
+        {
+            return Score >= threshold;
+        }
+
+        /// <summary>
+        /// Converte para o modelo atual do sistema (compatibilidade)
+        /// </summary>
+        public TextoComEmbedding ToTextoComEmbedding()
+        {
+            return new TextoComEmbedding
+            {
+                Id = Id,
+                Titulo = Title,
+                Conteudo = Content,
+                ProjetoId = ProjectId,
+                Embedding = Embedding
+            };
+        }
+
+        /// <summary>
+        /// Converte do modelo atual do sistema
+        /// </summary>
+        public static VectorSearchResult FromTextoComEmbedding(
+            TextoComEmbedding texto,
+            double score = 1.0,
+            string provider = "Unknown")
+        {
+            return new VectorSearchResult
+            {
+                Id = texto.Id,
+                Title = texto.Titulo,
+                Content = texto.Conteudo,
+                ProjectId = texto.ProjetoId,
+                Score = score,
+                Embedding = texto.Embedding,
+                Provider = provider,
+                CreatedAt = DateTime.UtcNow,
+                UpdatedAt = DateTime.UtcNow
+            };
+        }
+
+        public override string ToString()
+        {
+            return $"{Title} (Score: {GetScorePercentage()}, Provider: {Provider})";
+        }
+    }
+}

Program.cs

@@ -3,9 +3,18 @@ using ChatApi.Data;
 using ChatApi.Middlewares;
 using ChatApi.Services.Crypt;
 using ChatApi.Settings;
+using ChatRAG.Contracts.VectorSearch;
 using ChatRAG.Data;
+using ChatRAG.Extensions;
 using ChatRAG.Services;
+using ChatRAG.Services.Confidence;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.PromptConfiguration;
 using ChatRAG.Services.ResponseService;
+using ChatRAG.Services.SearchVectors;
+using ChatRAG.Services.TextServices;
+using ChatRAG.Settings;
+using ChatRAG.Settings.ChatRAG.Configuration;
 using Microsoft.AspNetCore.Authentication.JwtBearer;
 using Microsoft.AspNetCore.Http.Features;
 using Microsoft.AspNetCore.Server.Kestrel.Core;
@@ -16,6 +25,7 @@ using Microsoft.SemanticKernel;
 using System.Text;
 using static OllamaSharp.OllamaApiClient;
 using static System.Net.Mime.MediaTypeNames;
+using static System.Net.WebRequestMethods;
 
 #pragma warning disable SKEXP0010 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
 
@@ -69,28 +79,134 @@ builder.Services.AddSwaggerGen(c =>
     });
 });
 
-builder.Services.Configure<DomvsDatabaseSettings>(
-builder.Configuration.GetSection("DomvsDatabase"));
+builder.Services.Configure<ConfidenceSettings>(
+builder.Configuration.GetSection("Confidence"));
 
-builder.Services.Configure<ChatRHSettings>(
-builder.Configuration.GetSection("ChatRHSettings"));
+builder.Services.Configure<ConfidenceAwareSettings>(
+builder.Configuration.GetSection("ConfidenceAware"));
+
+
+//builder.Services.AddScoped<IVectorSearchService, MongoVectorSearchService>();
+builder.Services.AddScoped<QdrantVectorSearchService>();
+builder.Services.AddScoped<MongoVectorSearchService>();
+builder.Services.AddScoped<ChromaVectorSearchService>();
+
+builder.Services.AddVectorDatabase(builder.Configuration);
+
+builder.Services.AddScoped<IVectorSearchService>(provider =>
+{
+    var useQdrant = builder.Configuration["Features:UseQdrant"] == "true";
+    var factory = provider.GetRequiredService<IVectorDatabaseFactory>();
+    return factory.CreateVectorSearchService();
+});
+
+builder.Services.AddScoped<QdrantProjectDataRepository>();
+builder.Services.AddScoped<MongoProjectDataRepository>();
+builder.Services.AddScoped<ChromaProjectDataRepository>();
+
+builder.Services.AddScoped<IProjectDataRepository>(provider =>
+{
+    var database = builder.Configuration["VectorDatabase:Provider"];
+    if (string.IsNullOrEmpty(database))
+    {
+        throw new InvalidOperationException("VectorDatabase:Provider is not configured.");
+    }
+    else if (database.Equals("Qdrant", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<QdrantProjectDataRepository>();
+    }
+    else if (database.Equals("MongoDB", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<MongoProjectDataRepository>();
+    }
+    else if (database.Equals("Chroma", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<ChromaProjectDataRepository>();
+    }
+    return provider.GetRequiredService<MongoProjectDataRepository>();
+});
+
+builder.Services.AddScoped<QdrantTextDataService>();
+builder.Services.AddScoped<MongoTextDataService>();
+builder.Services.AddScoped<ChromaTextDataService>();
+
+builder.Services.AddScoped<ITextDataService>(provider =>
+{
+    var database = builder.Configuration["VectorDatabase:Provider"];
+    if (string.IsNullOrEmpty(database))
+    {
+        throw new InvalidOperationException("VectorDatabase:Provider is not configured.");
+    }
+    else if (database.Equals("Qdrant", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<QdrantTextDataService>();
+    }
+    else if (database.Equals("MongoDB", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<MongoTextDataService>();
+    }
+    else if (database.Equals("Chroma", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<ChromaTextDataService>();
+    }
+    return provider.GetRequiredService<MongoTextDataService>();
+});
 
 builder.Services.AddSingleton<ChatHistoryService>();
 builder.Services.AddScoped<TextDataRepository>();
-builder.Services.AddScoped<ProjectDataRepository>();
 builder.Services.AddSingleton<TextFilter>();
 
-builder.Services.AddScoped<IResponseService, ResponseRAGService>();
+//builder.Services.AddScoped<IResponseService, ResponseRAGService>();
+builder.Services.AddScoped<ResponseRAGService>();
+builder.Services.AddScoped<HierarchicalRAGService>();
+
+builder.Services.AddScoped<IResponseService>(provider =>
+{
+    var configuration = provider.GetService<IConfiguration>();
+    var useHierarchical = configuration?.GetValue<bool>("Features:UseHierarchicalRAG") ?? false;
+    var useConfidence = configuration?.GetValue<bool>("Features:UseConfidenceAwareRAG") ?? false;
+
+    return useConfidence && useHierarchical
+        ? provider.GetRequiredService<ConfidenceAwareRAGService>()
+        : useHierarchical        
+        ? provider.GetRequiredService<HierarchicalRAGService>()
+        : provider.GetRequiredService<ResponseRAGService>();
+});
+
 builder.Services.AddTransient<UserDataRepository>();
 builder.Services.AddTransient<TextData>();
 builder.Services.AddSingleton<CryptUtil>();
 
+// Registrar serviços de confiança
+builder.Services.AddScoped<ConfidenceVerifier>();
+builder.Services.AddSingleton<PromptConfigurationService>();
+
+// Registrar ConfidenceAwareRAGService
+builder.Services.AddScoped<ConfidenceAwareRAGService>();
+
 //builder.Services.AddOllamaChatCompletion("phi3.5", new Uri("http://localhost:11435"));
 //builder.Services.AddOllamaChatCompletion("tinydolphin", new Uri("http://localhost:11435"));
 //var apiClient = new OllamaApiClient(new Uri("http://localhost:11435"), "tinydolphin");
 
 //Olllama 
-builder.Services.AddOllamaChatCompletion("llama3.2", new Uri("http://localhost:11434"));
+//Desktop
+var key = "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";
+//uilder.Services.AddOllamaChatCompletion("llama3.2", new Uri("http://localhost:11434"));
+//var model = "llama-3.3-70b-versatile";
+var model = "llama-3.1-8b-instant";
+//var model = "meta-llama/llama-guard-4-12b";
+//var url = "https://api.groq.com/openai/v1/chat/completions"; // Adicione o /v1/openai
+var url = "https://api.groq.com/openai/v1"; 
+builder.Services.AddOpenAIChatCompletion(model, new Uri(url), key);
+
+//Notebook
+//var model = "meta-llama/Llama-3.2-3B-Instruct";
+//var url = "https://api.deepinfra.com/v1/openai"; // Adicione o /v1/openai
+//builder.Services.AddOpenAIChatCompletion(model, new Uri(url), "HedaR4yPrp9N2XSHfwdZjpZvPIxejPFK");
+
+//builder.Services.AddOllamaChatCompletion("llama3.2:3b", new Uri("http://localhost:11435"));
+//builder.Services.AddOllamaChatCompletion("llama3.2:1b", new Uri("http://localhost:11435"));
+
 
 //builder.Services.AddOllamaChatCompletion("tinydolphin", new Uri("http://localhost:11435"));
 //builder.Services.AddOllamaChatCompletion("tinyllama", new Uri("http://localhost:11435"));
@@ -103,7 +219,13 @@ builder.Services.AddOllamaChatCompletion("llama3.2", new Uri("http://localhost:1
 //builder.Services.AddOllamaChatCompletion("llama3.1:latest", new Uri("http://192.168.0.150:11434"));
 
 //builder.Services.AddOllamaTextEmbeddingGeneration("all-minilm", new Uri("http://192.168.0.150:11434"));
-builder.Services.AddOllamaTextEmbeddingGeneration("all-minilm", new Uri("http://localhost:11434"));
+
+//Desktop
+//builder.Services.AddOllamaTextEmbeddingGeneration("all-minilm", new Uri("http://localhost:11434"));
+//Notebook
+builder.Services.AddOllamaTextEmbeddingGeneration("all-minilm", new Uri("http://localhost:11435"));
+
+
 //builder.Services.AddOllamaChatCompletion("phi3.5", new Uri("http://localhost:11435"));
 //builder.Services.AddOpenAIChatCompletion("gpt-4o-mini", "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");
 //builder.Services.AddGoogleAIGeminiChatCompletion("gemini-1.5-flash-latest", "AIzaSyDKBMX5yW77vxJFVJVE-5VLxlQRxCepck8");

Services/Confidence/ConfidenceVerifier.cs

@@ -0,0 +1,389 @@
+using ChatRAG.Models;
+using ChatRAG.Services.ResponseService;
+using ChatRAG.Settings;
+using Microsoft.Extensions.Options;
+
+namespace ChatRAG.Services.Confidence
+{
+    /// <summary>
+    /// Verifica se o RAG deve responder baseado na confiança dos resultados
+    /// </summary>
+    public class ConfidenceVerifier
+    {
+        private readonly ILogger<ConfidenceVerifier> _logger;
+        private readonly ConfidenceSettings _settings;
+
+        public ConfidenceVerifier(
+            ILogger<ConfidenceVerifier> logger,
+            IOptions<ConfidenceSettings> settings)
+        {
+            _logger = logger;
+            _settings = settings.Value;
+        }
+
+        /// <summary>
+        /// Verifica se deve responder baseado na análise, resultados e contexto
+        /// </summary>
+        public ConfidenceResult VerifyConfidence(
+            QueryAnalysis analysis,
+            List<VectorSearchResult> results,
+            HierarchicalContext context,
+            bool strictMode = true,
+            string language = "pt")
+        {
+            var strategy = analysis.Strategy?.ToLower() ?? "specific";
+            var thresholds = GetThresholds(strategy, strictMode);
+
+            _logger.LogInformation("Verificando confiança - Estratégia: {Strategy}, Modo Restrito: {StrictMode}, Idioma: {Language}",
+                strategy, strictMode, language);
+
+            // Calcular métricas de confiança
+            var metrics = CalculateConfidenceMetrics(results, context, analysis);
+
+            // Verificar se deve responder baseado na estratégia
+            var shouldRespond = ShouldRespond(strategy, metrics, thresholds);
+
+            var result = new ConfidenceResult
+            {
+                ShouldRespond = shouldRespond,
+                ConfidenceScore = metrics.OverallScore,
+                Strategy = strategy,
+                Metrics = metrics,
+                Reason = GenerateReason(shouldRespond, strategy, metrics, thresholds, language),
+                SuggestedResponse = shouldRespond ? null : GenerateFallbackResponse(strategy, metrics, language)
+            };
+
+            _logger.LogInformation("Resultado da confiança: {ShouldRespond} (Score: {ConfidenceScore:P1}, Estratégia: {Strategy})",
+                result.ShouldRespond, result.ConfidenceScore, strategy);
+
+            return result;
+        }
+
+        /// <summary>
+        /// Calcula métricas detalhadas de confiança
+        /// </summary>
+        private ConfidenceMetrics CalculateConfidenceMetrics(
+            List<VectorSearchResult> results,
+            HierarchicalContext context,
+            QueryAnalysis analysis)
+        {
+            var relevantResults = results.Where(r => r.Score >= 0.3).ToList();
+            var highQualityResults = results.Where(r => r.Score >= 0.6).ToList();
+
+            var metrics = new ConfidenceMetrics
+            {
+                TotalDocuments = results.Count,
+                RelevantDocuments = relevantResults.Count,
+                HighQualityDocuments = highQualityResults.Count,
+                AverageScore = results.Any() ? results.Average(r => r.Score) : 0,
+                MaxScore = results.Any() ? results.Max(r => r.Score) : 0,
+                MinScore = results.Any() ? results.Min(r => r.Score) : 0,
+                ContextLength = context.CombinedContext?.Length ?? 0,
+                StepsExecuted = context.Steps.Count,
+                HasSpecificContent = HasSpecificContent(results, analysis),
+                OverallScore = CalculateOverallScore(results, context, analysis)
+            };
+
+            // Métricas adicionais
+            metrics.ScoreVariance = CalculateScoreVariance(results);
+            metrics.ContentDiversity = CalculateContentDiversity(results);
+            metrics.ConceptCoverage = CalculateConceptCoverage(results, analysis);
+
+            return metrics;
+        }
+
+        /// <summary>
+        /// Verifica se há conteúdo específico relacionado aos conceitos da query
+        /// </summary>
+        private bool HasSpecificContent(List<VectorSearchResult> results, QueryAnalysis analysis)
+        {
+            if (!analysis.Concepts?.Any() == true)
+                return results.Any(); // Se não há conceitos específicos, qualquer resultado serve
+
+            var combinedContent = string.Join(" ", results.Select(r => $"{r.Title} {r.Content}")).ToLower();
+            var conceptsFound = analysis.Concepts.Count(concept =>
+                combinedContent.Contains(concept.ToLower()));
+
+            var minConceptsRequired = Math.Max(1, Math.Min(2, analysis.Concepts.Length));
+            return conceptsFound >= minConceptsRequired;
+        }
+
+        /// <summary>
+        /// Calcula score geral considerando múltiplos fatores
+        /// </summary>
+        private double CalculateOverallScore(List<VectorSearchResult> results, HierarchicalContext context, QueryAnalysis analysis)
+        {
+            if (!results.Any()) return 0;
+
+            // Pesos para diferentes fatores
+            const double scoreWeight = 0.35;        // Qualidade dos scores
+            const double countWeight = 0.25;        // Quantidade de documentos
+            const double contextWeight = 0.20;      // Tamanho do contexto
+            const double diversityWeight = 0.10;    // Diversidade do conteúdo
+            const double conceptWeight = 0.10;      // Cobertura de conceitos
+
+            // Score baseado na qualidade dos resultados
+            var avgScore = results.Average(r => r.Score);
+            var maxScore = results.Max(r => r.Score);
+            var qualityScore = (avgScore * 0.7) + (maxScore * 0.3); // Média ponderada
+
+            // Score baseado na quantidade (com saturação)
+            var countScore = Math.Min(1.0, results.Count / 5.0);
+
+            // Score baseado no tamanho do contexto (com saturação)
+            var contextScore = Math.Min(1.0, (context.CombinedContext?.Length ?? 0) / 2000.0);
+
+            // Score baseado na diversidade do conteúdo
+            var diversityScore = CalculateContentDiversity(results);
+
+            // Score baseado na cobertura de conceitos
+            var conceptScore = CalculateConceptCoverage(results, analysis);
+
+            var overallScore = (qualityScore * scoreWeight) +
+                              (countScore * countWeight) +
+                              (contextScore * contextWeight) +
+                              (diversityScore * diversityWeight) +
+                              (conceptScore * conceptWeight);
+
+            return Math.Min(1.0, overallScore);
+        }
+
+        /// <summary>
+        /// Calcula variância dos scores para medir consistência
+        /// </summary>
+        private double CalculateScoreVariance(List<VectorSearchResult> results)
+        {
+            if (results.Count < 2) return 0;
+
+            var mean = results.Average(r => r.Score);
+            var variance = results.Average(r => Math.Pow(r.Score - mean, 2));
+
+            // Normalizar para 0-1 (menor variância = melhor)
+            return Math.Max(0, 1 - (variance * 4)); // Multiplica por 4 para normalizar
+        }
+
+        /// <summary>
+        /// Calcula diversidade do conteúdo (documentos diferentes)
+        /// </summary>
+        private double CalculateContentDiversity(List<VectorSearchResult> results)
+        {
+            if (!results.Any()) return 0;
+
+            // Simples heurística: títulos únicos / total
+            var uniqueTitles = results.Select(r => r.Title?.ToLower() ?? "").Distinct().Count();
+            return Math.Min(1.0, (double)uniqueTitles / results.Count);
+        }
+
+        /// <summary>
+        /// Calcula cobertura dos conceitos da query
+        /// </summary>
+        private double CalculateConceptCoverage(List<VectorSearchResult> results, QueryAnalysis analysis)
+        {
+            if (!analysis.Concepts?.Any() == true) return 1.0; // Se não há conceitos, assume cobertura total
+
+            var combinedContent = string.Join(" ", results.Select(r => $"{r.Title} {r.Content}")).ToLower();
+            var conceptsFound = analysis.Concepts.Count(concept =>
+                combinedContent.Contains(concept.ToLower()));
+
+            return (double)conceptsFound / analysis.Concepts.Length;
+        }
+
+        /// <summary>
+        /// Decide se deve responder baseado na estratégia e métricas
+        /// </summary>
+        private bool ShouldRespond(string strategy, ConfidenceMetrics metrics, ConfidenceThresholds thresholds)
+        {
+            return strategy switch
+            {
+                "overview" => ShouldRespondOverview(metrics, thresholds),
+                "specific" => ShouldRespondSpecific(metrics, thresholds),
+                "detailed" => ShouldRespondDetailed(metrics, thresholds),
+                _ => ShouldRespondSpecific(metrics, thresholds) // Default para specific
+            };
+        }
+
+        /// <summary>
+        /// Lógica específica para estratégia Overview
+        /// </summary>
+        private bool ShouldRespondOverview(ConfidenceMetrics metrics, ConfidenceThresholds thresholds)
+        {
+            // Para overview, precisamos de quantidade e contexto amplo
+            return metrics.TotalDocuments >= thresholds.MinDocuments &&
+                   metrics.ContextLength >= thresholds.MinContextLength &&
+                   metrics.OverallScore >= thresholds.MinOverallScore &&
+                   (metrics.RelevantDocuments >= thresholds.MinRelevantDocuments || metrics.TotalDocuments >= 10); // Flexibilidade para projetos grandes
+        }
+
+        /// <summary>
+        /// Lógica específica para estratégia Specific
+        /// </summary>
+        private bool ShouldRespondSpecific(ConfidenceMetrics metrics, ConfidenceThresholds thresholds)
+        {
+            // Para specific, precisamos de relevância e qualidade
+            return metrics.RelevantDocuments >= thresholds.MinRelevantDocuments &&
+                   metrics.MaxScore >= thresholds.MinMaxScore &&
+                   metrics.OverallScore >= thresholds.MinOverallScore &&
+                   metrics.HasSpecificContent;
+        }
+
+        /// <summary>
+        /// Lógica específica para estratégia Detailed
+        /// </summary>
+        private bool ShouldRespondDetailed(ConfidenceMetrics metrics, ConfidenceThresholds thresholds)
+        {
+            // Para detailed, precisamos de alta qualidade e cobertura
+            return metrics.HighQualityDocuments >= thresholds.MinHighQualityDocuments &&
+                   metrics.AverageScore >= thresholds.MinAverageScore &&
+                   metrics.HasSpecificContent &&
+                   metrics.OverallScore >= thresholds.MinOverallScore &&
+                   metrics.ConceptCoverage >= 0.5; // Pelo menos 50% dos conceitos cobertos
+        }
+
+        /// <summary>
+        /// Obtém thresholds ajustados para modo restrito/relaxado
+        /// </summary>
+        private ConfidenceThresholds GetThresholds(string strategy, bool strictMode)
+        {
+            if (!_settings.Thresholds.ContainsKey(strategy))
+            {
+                _logger.LogWarning("Estratégia '{Strategy}' não encontrada, usando 'specific'", strategy);
+                strategy = "specific";
+            }
+
+            var baseThresholds = _settings.Thresholds[strategy];
+
+            if (!strictMode)
+            {
+                // Modo relaxado: reduz os thresholds
+                return new ConfidenceThresholds
+                {
+                    MinDocuments = Math.Max(1, baseThresholds.MinDocuments - 2),
+                    MinRelevantDocuments = Math.Max(1, baseThresholds.MinRelevantDocuments - 1),
+                    MinHighQualityDocuments = Math.Max(0, baseThresholds.MinHighQualityDocuments - 1),
+                    MinContextLength = Math.Max(100, baseThresholds.MinContextLength - 500),
+                    MinOverallScore = Math.Max(0.1, baseThresholds.MinOverallScore - 0.15),
+                    MinMaxScore = Math.Max(0.2, baseThresholds.MinMaxScore - 0.15),
+                    MinAverageScore = Math.Max(0.2, baseThresholds.MinAverageScore - 0.15)
+                };
+            }
+
+            return baseThresholds;
+        }
+
+        /// <summary>
+        /// Gera explicação do motivo da decisão
+        /// </summary>
+        private string GenerateReason(bool shouldRespond, string strategy, ConfidenceMetrics metrics, ConfidenceThresholds thresholds, string language)
+        {
+            if (shouldRespond)
+            {
+                return language == "en"
+                    ? $"Sufficient confidence for '{strategy}' strategy - Score: {metrics.OverallScore:P1}, Docs: {metrics.RelevantDocuments}/{metrics.TotalDocuments}"
+                    : $"Confiança suficiente para estratégia '{strategy}' - Score: {metrics.OverallScore:P1}, Docs: {metrics.RelevantDocuments}/{metrics.TotalDocuments}";
+            }
+
+            var issues = new List<string>();
+
+            if (metrics.TotalDocuments < thresholds.MinDocuments)
+            {
+                var msg = language == "en"
+                    ? $"few documents ({metrics.TotalDocuments} < {thresholds.MinDocuments})"
+                    : $"poucos documentos ({metrics.TotalDocuments} < {thresholds.MinDocuments})";
+                issues.Add(msg);
+            }
+
+            if (metrics.RelevantDocuments < thresholds.MinRelevantDocuments)
+            {
+                var msg = language == "en"
+                    ? $"few relevant documents ({metrics.RelevantDocuments} < {thresholds.MinRelevantDocuments})"
+                    : $"poucos documentos relevantes ({metrics.RelevantDocuments} < {thresholds.MinRelevantDocuments})";
+                issues.Add(msg);
+            }
+
+            if (metrics.OverallScore < thresholds.MinOverallScore)
+            {
+                var msg = language == "en"
+                    ? $"low overall score ({metrics.OverallScore:P1} < {thresholds.MinOverallScore:P1})"
+                    : $"score geral baixo ({metrics.OverallScore:P1} < {thresholds.MinOverallScore:P1})";
+                issues.Add(msg);
+            }
+
+            if (!metrics.HasSpecificContent)
+            {
+                var msg = language == "en" ? "no specific content found" : "conteúdo específico não encontrado";
+                issues.Add(msg);
+            }
+
+            var prefix = language == "en" ? "Insufficient confidence: " : "Confiança insuficiente: ";
+            return prefix + string.Join(", ", issues);
+        }
+
+        /// <summary>
+        /// Gera resposta de fallback apropriada
+        /// </summary>
+        private string GenerateFallbackResponse(string strategy, ConfidenceMetrics metrics, string language)
+        {
+            if (!_settings.FallbackMessages.ContainsKey(language))
+            {
+                language = "pt"; // Fallback para português
+            }
+
+            var messages = _settings.FallbackMessages[language];
+
+            // Escolher mensagem baseada no problema principal
+            if (metrics.TotalDocuments == 0)
+            {
+                return messages.NoDocuments;
+            }
+
+            if (metrics.RelevantDocuments == 0)
+            {
+                return messages.NoRelevantDocuments;
+            }
+
+            return strategy switch
+            {
+                "overview" => messages.InsufficientOverview,
+                "specific" => messages.InsufficientSpecific,
+                "detailed" => messages.InsufficientDetailed,
+                _ => messages.Generic
+            };
+        }
+    }
+
+    /// <summary>
+    /// Resultado da verificação de confiança
+    /// </summary>
+    public class ConfidenceResult
+    {
+        public bool ShouldRespond { get; set; }
+        public double ConfidenceScore { get; set; }
+        public string Strategy { get; set; } = "";
+        public ConfidenceMetrics Metrics { get; set; } = new();
+        public string Reason { get; set; } = "";
+        public string? SuggestedResponse { get; set; }
+    }
+
+    /// <summary>
+    /// Métricas detalhadas de confiança
+    /// </summary>
+    public class ConfidenceMetrics
+    {
+        // Métricas básicas
+        public int TotalDocuments { get; set; }
+        public int RelevantDocuments { get; set; }
+        public int HighQualityDocuments { get; set; }
+        public double AverageScore { get; set; }
+        public double MaxScore { get; set; }
+        public double MinScore { get; set; }
+        public int ContextLength { get; set; }
+        public int StepsExecuted { get; set; }
+        public bool HasSpecificContent { get; set; }
+        public double OverallScore { get; set; }
+
+        // Métricas avançadas
+        public double ScoreVariance { get; set; }
+        public double ContentDiversity { get; set; }
+        public double ConceptCoverage { get; set; }
+    }
+}

Services/Contracts/IProjectDataRepository.cs

@@ -0,0 +1,14 @@
+using ChatRAG.Models;
+
+namespace ChatRAG.Services.Contracts
+{
+    public interface IProjectDataRepository
+    {
+        Task<List<Project>> GetAsync();
+        Task<Project?> GetAsync(string id);
+        Task CreateAsync(Project newProject);
+        Task UpdateAsync(string id, Project updatedProject);
+        Task SaveAsync(Project project);
+        Task RemoveAsync(string id);
+    }
+}

Services/Contracts/IResponseService.cs

@@ -1,9 +1,10 @@
 using ChatApi.Models;
 
-namespace ChatRAG.Services.ResponseService
+namespace ChatRAG.Services.Contracts
 {
     public interface IResponseService
     {
         Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question);
+        Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question, string language = "pt");
     }
 }

Services/Contracts/IResponseServiceExtended.cs

@@ -0,0 +1,17 @@
+using ChatApi.Models;
+using ChatRAG.Models;
+
+namespace ChatRAG.Services.Contracts
+{
+    public interface IResponseServiceExtended : IResponseService
+    {
+        Task<ResponseResult> GetResponseDetailed(
+            UserData userData,
+            string projectId,
+            string sessionId,
+            string question,
+            ResponseOptions? options = null);
+
+        Task<ResponseStats> GetStatsAsync();
+    }
+}

Services/Contracts/ITextDataService.cs

@@ -0,0 +1,143 @@
+using ChatRAG.Models;
+
+namespace ChatRAG.Services.Contracts
+{
+    /// <summary>
+    /// Interface unificada para operações de documentos de texto.
+    /// Permite alternar entre MongoDB, Qdrant, ou outros providers sem quebrar código.
+    /// </summary>
+    public interface ITextDataService
+    {
+        // ========================================
+        // MÉTODOS ORIGINAIS (compatibilidade com TextData.cs atual)
+        // ========================================
+
+        /// <summary>
+        /// Salva texto no banco (método original do seu TextData.cs)
+        /// </summary>
+        /// <param name="titulo">Título do documento</param>
+        /// <param name="texto">Conteúdo do documento</param>
+        /// <param name="projectId">ID do projeto</param>
+        Task SalvarNoMongoDB(string titulo, string texto, string projectId);
+
+        /// <summary>
+        /// Salva ou atualiza texto com ID específico (método original)
+        /// </summary>
+        /// <param name="id">ID do documento (null para criar novo)</param>
+        /// <param name="titulo">Título do documento</param>
+        /// <param name="texto">Conteúdo do documento</param>
+        /// <param name="projectId">ID do projeto</param>
+        Task SalvarNoMongoDB(string? id, string titulo, string texto, string projectId);
+
+        /// <summary>
+        /// Processa texto completo dividindo por seções (método original)
+        /// </summary>
+        /// <param name="textoCompleto">Texto com divisões marcadas por **</param>
+        /// <param name="projectId">ID do projeto</param>
+        Task SalvarTextoComEmbeddingNoMongoDB(string textoCompleto, string projectId);
+
+        /// <summary>
+        /// Recupera todos os documentos (método original)
+        /// </summary>
+        /// <returns>Lista de todos os documentos</returns>
+        Task<IEnumerable<TextoComEmbedding>> GetAll();
+
+        /// <summary>
+        /// Recupera documentos por projeto (método original)
+        /// </summary>
+        /// <param name="projectId">ID do projeto</param>
+        /// <returns>Lista de documentos do projeto</returns>
+        Task<IEnumerable<TextoComEmbedding>> GetByPorjectId(string projectId);
+
+        /// <summary>
+        /// Recupera documento por ID (método original)
+        /// </summary>
+        /// <param name="id">ID do documento</param>
+        /// <returns>Documento ou null se não encontrado</returns>
+        Task<TextoComEmbedding> GetById(string id);
+
+        // ========================================
+        // MÉTODOS NOVOS (interface moderna e unificada)
+        // ========================================
+
+        /// <summary>
+        /// Salva documento usando modelo unificado
+        /// </summary>
+        /// <param name="document">Dados do documento</param>
+        /// <returns>ID do documento criado</returns>
+        Task<string> SaveDocumentAsync(DocumentInput document);
+
+        /// <summary>
+        /// Atualiza documento existente
+        /// </summary>
+        /// <param name="id">ID do documento</param>
+        /// <param name="document">Novos dados do documento</param>
+        Task UpdateDocumentAsync(string id, DocumentInput document);
+
+        /// <summary>
+        /// Remove documento
+        /// </summary>
+        /// <param name="id">ID do documento</param>
+        Task DeleteDocumentAsync(string id);
+
+        /// <summary>
+        /// Verifica se documento existe
+        /// </summary>
+        /// <param name="id">ID do documento</param>
+        /// <returns>True se existe, False caso contrário</returns>
+        Task<bool> DocumentExistsAsync(string id);
+
+        /// <summary>
+        /// Recupera documento por ID (formato moderno)
+        /// </summary>
+        /// <param name="id">ID do documento</param>
+        /// <returns>Documento ou null se não encontrado</returns>
+        Task<DocumentOutput?> GetDocumentAsync(string id);
+
+        /// <summary>
+        /// Lista documentos por projeto (formato moderno)
+        /// </summary>
+        /// <param name="projectId">ID do projeto</param>
+        /// <returns>Lista de documentos do projeto</returns>
+        Task<List<DocumentOutput>> GetDocumentsByProjectAsync(string projectId);
+
+        /// <summary>
+        /// Conta documentos
+        /// </summary>
+        /// <param name="projectId">Filtrar por projeto (opcional)</param>
+        /// <returns>Número de documentos</returns>
+        Task<int> GetDocumentCountAsync(string? projectId = null);
+
+        // ========================================
+        // OPERAÇÕES EM LOTE
+        // ========================================
+
+        /// <summary>
+        /// Salva múltiplos documentos de uma vez
+        /// </summary>
+        /// <param name="documents">Lista de documentos</param>
+        /// <returns>Lista de IDs dos documentos criados</returns>
+        Task<List<string>> SaveDocumentsBatchAsync(List<DocumentInput> documents);
+
+        /// <summary>
+        /// Remove múltiplos documentos de uma vez
+        /// </summary>
+        /// <param name="ids">Lista de IDs para remover</param>
+        Task DeleteDocumentsBatchAsync(List<string> ids);
+
+        // ========================================
+        // INFORMAÇÕES DO PROVIDER
+        // ========================================
+
+        /// <summary>
+        /// Nome do provider (MongoDB, Qdrant, etc.)
+        /// </summary>
+        string ProviderName { get; }
+
+        /// <summary>
+        /// Estatísticas e métricas do provider
+        /// </summary>
+        /// <returns>Informações sobre performance, saúde, etc.</returns>
+        Task<Dictionary<string, object>> GetProviderStatsAsync();
+    }
+}

Services/Contracts/IVectorDatabaseFactory.cs

@@ -0,0 +1,14 @@
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Settings.ChatRAG.Configuration;
+
+namespace ChatRAG.Services.Contracts
+{
+    public interface IVectorDatabaseFactory
+    {
+        IVectorSearchService CreateVectorSearchService();
+        ITextDataService CreateTextDataService();
+        IResponseService CreateResponseService();
+        string GetActiveProvider();
+        VectorDatabaseSettings GetSettings();
+    }
+}

Services/Contracts/IVectorSearchService.cs

@@ -0,0 +1,138 @@
+using ChatRAG.Models;
+using Microsoft.Extensions.VectorData;
+
+namespace ChatRAG.Contracts.VectorSearch
+{
+    /// <summary>
+    /// Interface unificada para operações de busca vetorial.
+    /// Pode ser implementada por MongoDB, Qdrant, Pinecone, etc.
+    /// </summary>
+    public interface IVectorSearchService
+    {
+        // ========================================
+        // BUSCA VETORIAL
+        // ========================================
+
+        /// <summary>
+        /// Busca documentos similares usando embedding vetorial
+        /// </summary>
+        /// <param name="queryEmbedding">Embedding da query (ex: 1536 dimensões para OpenAI)</param>
+        /// <param name="projectId">Filtrar por projeto específico (opcional)</param>
+        /// <param name="threshold">Score mínimo de similaridade (0.0 a 1.0)</param>
+        /// <param name="limit">Número máximo de resultados</param>
+        /// <param name="filters">Filtros adicionais (metadata, data, etc.)</param>
+        /// <returns>Lista de documentos ordenados por similaridade</returns>
+        Task<List<VectorSearchResult>> SearchSimilarAsync(
+            double[] queryEmbedding,
+            string? projectId = null,
+            double threshold = 0.3,
+            int limit = 5,
+            Dictionary<string, object>? filters = null);
+
+        /// <summary>
+        /// Busca adaptativa - relaxa threshold se não encontrar resultados suficientes
+        /// (Implementa a mesma lógica do seu ResponseRAGService atual)
+        /// </summary>
+        /// <param name="queryEmbedding">Embedding da query</param>
+        /// <param name="projectId">ID do projeto</param>
+        /// <param name="minThreshold">Threshold inicial (será reduzido se necessário)</param>
+        /// <param name="limit">Número máximo de resultados</param>
+        /// <returns>Lista de documentos com busca adaptativa</returns>
+        Task<List<VectorSearchResult>> SearchSimilarDynamicAsync(
+            double[] queryEmbedding,
+            string projectId,
+            double minThreshold = 0.5,
+            int limit = 5);
+
+        // ========================================
+        // CRUD DE DOCUMENTOS
+        // ========================================
+
+        /// <summary>
+        /// Adiciona um novo documento com embedding
+        /// </summary>
+        /// <param name="title">Título do documento</param>
+        /// <param name="content">Conteúdo do documento</param>
+        /// <param name="projectId">ID do projeto</param>
+        /// <param name="embedding">Embedding pré-calculado</param>
+        /// <param name="metadata">Metadados adicionais (tags, data, autor, etc.)</param>
+        /// <returns>ID do documento criado</returns>
+        Task<string> AddDocumentAsync(
+            string title,
+            string content,
+            string projectId,
+            double[] embedding,
+            Dictionary<string, object>? metadata = null);
+
+        /// <summary>
+        /// Atualiza um documento existente
+        /// </summary>
+        /// <param name="id">ID do documento</param>
+        /// <param name="title">Novo título</param>
+        /// <param name="content">Novo conteúdo</param>
+        /// <param name="projectId">ID do projeto</param>
+        /// <param name="embedding">Novo embedding</param>
+        /// <param name="metadata">Novos metadados</param>
+        Task UpdateDocumentAsync(
+            string id,
+            string title,
+            string content,
+            string projectId,
+            double[] embedding,
+            Dictionary<string, object>? metadata = null);
+
+        /// <summary>
+        /// Remove um documento
+        /// </summary>
+        /// <param name="id">ID do documento</param>
+        Task DeleteDocumentAsync(string id);
+
+        // ========================================
+        // CONSULTAS AUXILIARES
+        // ========================================
+
+        /// <summary>
+        /// Verifica se um documento existe
+        /// </summary>
+        /// <param name="id">ID do documento</param>
+        /// <returns>True se existe, False caso contrário</returns>
+        Task<bool> DocumentExistsAsync(string id);
+
+        /// <summary>
+        /// Recupera um documento específico por ID
+        /// </summary>
+        /// <param name="id">ID do documento</param>
+        /// <returns>Documento ou null se não encontrado</returns>
+        Task<VectorSearchResult?> GetDocumentAsync(string id);
+
+        /// <summary>
+        /// Lista todos os documentos de um projeto
+        /// </summary>
+        /// <param name="projectId">ID do projeto</param>
+        /// <returns>Lista de documentos do projeto</returns>
+        Task<List<VectorSearchResult>> GetDocumentsByProjectAsync(string projectId);
+
+        /// <summary>
+        /// Conta total de documentos
+        /// </summary>
+        /// <param name="projectId">Filtrar por projeto (opcional)</param>
+        /// <returns>Número de documentos</returns>
+        Task<int> GetDocumentCountAsync(string? projectId = null);
+
+        // ========================================
+        // HEALTH CHECK E MÉTRICAS
+        // ========================================
+
+        /// <summary>
+        /// Verifica se o serviço está saudável
+        /// </summary>
+        /// <returns>True se está funcionando, False caso contrário</returns>
+        Task<bool> IsHealthyAsync();
+
+        /// <summary>
+        /// Retorna estatísticas e métricas do provider
+        /// </summary>
+        /// <returns>Dicionário com estatísticas (documentos, performance, etc.)</returns>
+        Task<Dictionary<string, object>> GetStatsAsync();
+    }
+}

Services/PromptConfiguration/PromptConfigurationService.cs

@@ -0,0 +1,753 @@
+using System.Text.Json;
+using System.Text.RegularExpressions;
+using Microsoft.Extensions.Options;
+using ChatRAG.Services.Confidence;
+using ChatRAG.Settings;
+using Microsoft.Extensions.Configuration;
+
+namespace ChatRAG.Services.PromptConfiguration
+{
+    /// <summary>
+    /// Serviço para configuração e carregamento de prompts por domínio e idioma
+    /// </summary>
+    public class PromptConfigurationService
+    {
+        private readonly ILogger<PromptConfigurationService> _logger;
+        private readonly string _configurationPath;
+        private readonly LanguageSettings _languageSettings;
+        private readonly CacheSettings _cacheSettings;
+
+        private Dictionary<string, DomainPromptConfig> _domainConfigs = new();
+        private BasePromptConfig _baseConfig = new();
+        private readonly Dictionary<string, DateTime> _fileLastModified = new();
+        private readonly object _lockObject = new object();
+
+        public PromptConfigurationService(
+            ILogger<PromptConfigurationService> logger,
+            IConfiguration configuration,
+            IOptions<ConfidenceAwareSettings> settings)
+        {
+            _logger = logger;
+            _configurationPath = configuration["PromptConfiguration:Path"] ?? "Configuration/Prompts";
+            _languageSettings = settings.Value.Languages;
+            _cacheSettings = settings.Value.Cache;
+
+            // Carregar configurações na inicialização
+            _ = Task.Run(LoadConfigurations);
+        }
+
+        /// <summary>
+        /// Obtém prompts configurados para um domínio e idioma específicos
+        /// </summary>
+        public PromptTemplates GetPrompts(string? domain = null, string language = "pt")
+        {
+            // Verificar se precisa recarregar arquivos (se habilitado)
+            if (_cacheSettings.AutoReloadOnFileChange)
+            {
+                CheckForFileChanges();
+            }
+
+            // Detectar idioma se auto-detecção estiver habilitada
+            var detectedLanguage = _languageSettings.AutoDetectLanguage
+                ? DetectOrValidateLanguage(language)
+                : language;
+
+            var domainConfig = domain != null && _domainConfigs.ContainsKey(domain)
+                ? _domainConfigs[domain]
+                : null;
+
+            return new PromptTemplates
+            {
+                QueryAnalysis = GetPrompt("QueryAnalysis", domainConfig, detectedLanguage),
+                Overview = GetPrompt("Overview", domainConfig, detectedLanguage),
+                Specific = GetPrompt("Specific", domainConfig, detectedLanguage),
+                Detailed = GetPrompt("Detailed", domainConfig, detectedLanguage),
+                Response = GetPrompt("Response", domainConfig, detectedLanguage),
+                Summary = GetPrompt("Summary", domainConfig, detectedLanguage),
+                GapAnalysis = GetPrompt("GapAnalysis", domainConfig, detectedLanguage)
+            };
+        }
+
+        /// <summary>
+        /// Detecta o domínio baseado na pergunta e descrição do projeto
+        /// </summary>
+        public string? DetectDomain(string question, string? projectDescription = null)
+        {
+            var content = $"{question} {projectDescription}".ToLower();
+            var domainScores = new Dictionary<string, int>();
+
+            foreach (var (domain, config) in _domainConfigs)
+            {
+                var score = 0;
+
+                // Pontuação por palavras-chave (peso 2)
+                foreach (var keyword in config.Keywords)
+                {
+                    if (content.Contains(keyword.ToLower()))
+                    {
+                        score += 2;
+                    }
+                }
+
+                // Pontuação por conceitos (peso 1)
+                foreach (var concept in config.Concepts)
+                {
+                    if (content.Contains(concept.ToLower()))
+                    {
+                        score += 1;
+                    }
+                }
+
+                if (score > 0)
+                {
+                    domainScores[domain] = score;
+                }
+            }
+
+            if (domainScores.Any())
+            {
+                var bestDomain = domainScores.OrderByDescending(x => x.Value).First();
+                _logger.LogDebug("Domínio detectado: {Domain} com score {Score}", bestDomain.Key, bestDomain.Value);
+                return bestDomain.Key;
+            }
+
+            _logger.LogDebug("Nenhum domínio detectado, usando padrão");
+            return null;
+        }
+
+        /// <summary>
+        /// Detecta o idioma da pergunta
+        /// </summary>
+        public string DetectLanguage(string question)
+        {
+            if (string.IsNullOrWhiteSpace(question))
+                return _languageSettings.DefaultLanguage;
+
+            var languageScores = new Dictionary<string, int>();
+            var words = Regex.Split(question.ToLower(), @"\W+")
+                .Where(w => w.Length > 2)
+                .ToList();
+
+            foreach (var (language, keywords) in _languageSettings.LanguageKeywords)
+            {
+                var score = words.Count(word => keywords.Contains(word));
+                if (score > 0)
+                {
+                    languageScores[language] = score;
+                }
+            }
+
+            if (languageScores.Any())
+            {
+                var detectedLanguage = languageScores.OrderByDescending(x => x.Value).First().Key;
+                _logger.LogDebug("Idioma detectado: {Language}", detectedLanguage);
+                return detectedLanguage;
+            }
+
+            _logger.LogDebug("Idioma não detectado, usando padrão: {DefaultLanguage}", _languageSettings.DefaultLanguage);
+            return _languageSettings.DefaultLanguage;
+        }
+
+        /// <summary>
+        /// Lista domínios disponíveis
+        /// </summary>
+        public List<string> GetAvailableDomains()
+        {
+            return _domainConfigs.Keys.ToList();
+        }
+
+        /// <summary>
+        /// Lista idiomas suportados
+        /// </summary>
+        public List<string> GetSupportedLanguages()
+        {
+            return _languageSettings.SupportedLanguages;
+        }
+
+        /// <summary>
+        /// Força recarregamento das configurações
+        /// </summary>
+        public async Task ReloadConfigurations()
+        {
+            await LoadConfigurations();
+        }
+
+        // === MÉTODOS PRIVADOS ===
+
+        private void LoadBaseConfigurationSync()
+        {
+            var basePath = Path.Combine(_configurationPath, "base-prompts.json");
+
+            if (File.Exists(basePath))
+            {
+                try
+                {
+                    var json = File.ReadAllText(basePath);
+                    _baseConfig = JsonSerializer.Deserialize<BasePromptConfig>(json) ?? new BasePromptConfig();
+                    _fileLastModified[basePath] = File.GetLastWriteTime(basePath);
+                    _logger.LogDebug("Configuração base carregada de {Path}", basePath);
+                }
+                catch (Exception ex)
+                {
+                    _logger.LogError(ex, "Erro ao carregar configuração base de {Path}", basePath);
+                    _baseConfig = GetDefaultBaseConfig();
+                }
+            }
+            else
+            {
+                _logger.LogInformation("Arquivo base não encontrado, criando padrão em {Path}", basePath);
+                _baseConfig = GetDefaultBaseConfig();
+                SaveBaseConfigurationSync(basePath);
+            }
+        }
+
+        private void LoadDomainConfigurationsSync()
+        {
+            var domainsPath = Path.Combine(_configurationPath, "Domains");
+
+            if (!Directory.Exists(domainsPath))
+            {
+                _logger.LogInformation("Pasta de domínios não encontrada, criando em {Path}", domainsPath);
+                Directory.CreateDirectory(domainsPath);
+                CreateDefaultDomainConfigurationsSync(domainsPath);
+            }
+
+            var domainFiles = Directory.GetFiles(domainsPath, "*.json");
+            var loadedDomains = new Dictionary<string, DomainPromptConfig>();
+
+            foreach (var file in domainFiles)
+            {
+                try
+                {
+                    var json = File.ReadAllText(file);
+                    var config = JsonSerializer.Deserialize<DomainPromptConfig>(json);
+                    if (config != null)
+                    {
+                        var domainName = Path.GetFileNameWithoutExtension(file);
+                        loadedDomains[domainName] = config;
+                        _fileLastModified[file] = File.GetLastWriteTime(file);
+                        _logger.LogDebug("Domínio {Domain} carregado de {File}", domainName, file);
+                    }
+                }
+                catch (Exception ex)
+                {
+                    _logger.LogWarning(ex, "Erro ao carregar configuração do domínio: {File}", file);
+                }
+            }
+
+            _domainConfigs = loadedDomains;
+        }
+
+        private void CheckForFileChanges()
+        {
+            if (!_cacheSettings.AutoReloadOnFileChange) return;
+
+            var needsReload = false;
+            var filesToCheck = new List<string> { Path.Combine(_configurationPath, "base-prompts.json") };
+
+            var domainsPath = Path.Combine(_configurationPath, "Domains");
+            if (Directory.Exists(domainsPath))
+            {
+                filesToCheck.AddRange(Directory.GetFiles(domainsPath, "*.json"));
+            }
+
+            foreach (var file in filesToCheck)
+            {
+                if (File.Exists(file))
+                {
+                    var lastModified = File.GetLastWriteTime(file);
+                    if (!_fileLastModified.ContainsKey(file) || _fileLastModified[file] < lastModified)
+                    {
+                        _logger.LogInformation("Arquivo modificado detectado: {File}", file);
+                        needsReload = true;
+                        break;
+                    }
+                }
+            }
+
+            if (needsReload)
+            {
+                _ = Task.Run(LoadConfigurations);
+            }
+        }
+
+        private string DetectOrValidateLanguage(string language)
+        {
+            // Se o idioma é suportado, usar ele
+            if (_languageSettings.SupportedLanguages.Contains(language))
+            {
+                return language;
+            }
+
+            _logger.LogWarning("Idioma não suportado: {Language}, usando padrão: {DefaultLanguage}",
+                language, _languageSettings.DefaultLanguage);
+            return _languageSettings.DefaultLanguage;
+        }
+
+        private string GetPrompt(string promptType, DomainPromptConfig? domainConfig, string language)
+        {
+            // 1. Tentar buscar no domínio específico e idioma específico
+            if (domainConfig?.Prompts.ContainsKey(language) == true &&
+                domainConfig.Prompts[language].ContainsKey(promptType))
+            {
+                return domainConfig.Prompts[language][promptType];
+            }
+
+            // 2. Tentar buscar no domínio específico no idioma padrão
+            if (domainConfig?.Prompts.ContainsKey(_languageSettings.DefaultLanguage) == true &&
+                domainConfig.Prompts[_languageSettings.DefaultLanguage].ContainsKey(promptType))
+            {
+                var prompt = domainConfig.Prompts[_languageSettings.DefaultLanguage][promptType];
+                return _languageSettings.AlwaysRespondInRequestedLanguage && language != _languageSettings.DefaultLanguage
+                    ? AddLanguageInstruction(prompt, language)
+                    : prompt;
+            }
+
+            // 3. Fallback para configuração base no idioma solicitado
+            if (_baseConfig.Prompts.ContainsKey(language) &&
+                _baseConfig.Prompts[language].ContainsKey(promptType))
+            {
+                return _baseConfig.Prompts[language][promptType];
+            }
+
+            // 4. Fallback para configuração base no idioma padrão
+            if (_baseConfig.Prompts.ContainsKey(_languageSettings.DefaultLanguage) &&
+                _baseConfig.Prompts[_languageSettings.DefaultLanguage].ContainsKey(promptType))
+            {
+                var prompt = _baseConfig.Prompts[_languageSettings.DefaultLanguage][promptType];
+                return _languageSettings.AlwaysRespondInRequestedLanguage && language != _languageSettings.DefaultLanguage
+                    ? AddLanguageInstruction(prompt, language)
+                    : prompt;
+            }
+
+            // 5. Fallback final
+            return GetFallbackPrompt(promptType, language);
+        }
+
+        private string AddLanguageInstruction(string prompt, string targetLanguage)
+        {
+            var instruction = targetLanguage switch
+            {
+                "en" => "\n\nIMPORTANT: Respond in English.",
+                "pt" => "\n\nIMPORTANTE: Responda em português.",
+                _ => $"\n\nIMPORTANT: Respond in {targetLanguage}."
+            };
+
+            return prompt + instruction;
+        }
+
+        private void SaveBaseConfigurationSync(string basePath)
+        {
+            try
+            {
+                Directory.CreateDirectory(Path.GetDirectoryName(basePath)!);
+
+                var options = new JsonSerializerOptions
+                {
+                    WriteIndented = true,
+                    Encoder = System.Text.Encodings.Web.JavaScriptEncoder.UnsafeRelaxedJsonEscaping
+                };
+
+                var json = JsonSerializer.Serialize(_baseConfig, options);
+                File.WriteAllText(basePath, json);
+                _logger.LogInformation("Configuração base salva em {Path}", basePath);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar configuração base em {Path}", basePath);
+            }
+        }
+
+        private void CreateDefaultDomainConfigurationsSync(string domainsPath)
+        {
+            var domains = new Dictionary<string, DomainPromptConfig>
+            {
+                ["TI"] = GetTIDomainConfig(),
+                ["RH"] = GetRHDomainConfig(),
+                ["Financeiro"] = GetFinanceiroDomainConfig(),
+                ["QA"] = GetQADomainConfig()
+            };
+
+            var options = new JsonSerializerOptions
+            {
+                WriteIndented = true,
+                Encoder = System.Text.Encodings.Web.JavaScriptEncoder.UnsafeRelaxedJsonEscaping
+            };
+
+            foreach (var (domain, config) in domains)
+            {
+                try
+                {
+                    var filePath = Path.Combine(domainsPath, $"{domain}.json");
+                    var json = JsonSerializer.Serialize(config, options);
+                    File.WriteAllText(filePath, json);
+                    _logger.LogInformation("Configuração de domínio {Domain} criada em {Path}", domain, filePath);
+                }
+                catch (Exception ex)
+                {
+                    _logger.LogError(ex, "Erro ao criar configuração do domínio {Domain}", domain);
+                }
+            }
+        }
+
+        private BasePromptConfig GetDefaultBaseConfig()
+        {
+            return new BasePromptConfig
+            {
+                Prompts = new Dictionary<string, Dictionary<string, string>>
+                {
+                    ["pt"] = new Dictionary<string, string>
+                    {
+                        ["QueryAnalysis"] = @"Analise esta pergunta e classifique com precisão:
+                                                PERGUNTA: ""{0}""
+
+                                                Responda APENAS no formato JSON:
+                                                {{
+                                                    ""strategy"": ""overview|specific|detailed"",
+                                                    ""complexity"": ""simple|medium|complex"",
+                                                    ""scope"": ""global|filtered|targeted"",
+                                                    ""concepts"": [""conceito1"", ""conceito2""],
+                                                    ""needs_hierarchy"": true|false
+                                                }}
+
+                                                DEFINIÇÕES PRECISAS:
+                                                STRATEGY:
+                                                - overview: Pergunta sobre o PROJETO COMO UM TODO
+                                                - specific: Pergunta sobre MÓDULO/FUNCIONALIDADE ESPECÍFICA  
+                                                - detailed: Pergunta técnica específica que precisa de CONTEXTO PROFUNDO",
+
+                                                                        ["Response"] = @"Você é um especialista em análise de software e QA.
+
+                                                PROJETO: {0}
+                                                PERGUNTA: ""{1}""
+                                                CONTEXTO HIERÁRQUICO: {2}
+                                                ETAPAS EXECUTADAS: {3}
+
+                                                Responda à pergunta de forma precisa e estruturada, aproveitando todo o contexto hierárquico coletado.",
+
+                                                                        ["Summary"] = @"Resuma os pontos principais destes documentos sobre {0}:
+
+                                                {1}
+
+                                                Responda apenas com uma lista concisa dos pontos mais importantes:",
+
+                        ["GapAnalysis"] = @"Baseado na pergunta e contexto atual, identifique que informações ainda faltam para uma resposta completa.
+
+                                            PERGUNTA: {0}
+                                            CONTEXTO ATUAL: {1}
+
+                                            Responda APENAS com palavras-chave dos conceitos/informações que ainda faltam, separados por vírgula.
+                                            Se o contexto for suficiente, responda 'SUFICIENTE'."
+                    },
+                    ["en"] = new Dictionary<string, string>
+                    {
+                        ["QueryAnalysis"] = @"Analyze this question and classify precisely:
+                                            QUESTION: ""{0}""
+
+                                            Answer ONLY in JSON format:
+                                            {{
+                                                ""strategy"": ""overview|specific|detailed"",
+                                                ""complexity"": ""simple|medium|complex"",
+                                                ""scope"": ""global|filtered|targeted"",
+                                                ""concepts"": [""concept1"", ""concept2""],
+                                                ""needs_hierarchy"": true|false
+                                            }}
+
+                                            PRECISE DEFINITIONS:
+                                            STRATEGY:
+                                            - overview: Question about the PROJECT AS A WHOLE
+                                            - specific: Question about SPECIFIC MODULE/FUNCTIONALITY
+                                            - detailed: Technical specific question needing DEEP CONTEXT",
+
+                                                                    ["Response"] = @"You are a software analysis and QA expert.
+
+                                            PROJECT: {0}
+                                            QUESTION: ""{1}""
+                                            HIERARCHICAL CONTEXT: {2}
+                                            EXECUTED STEPS: {3}
+
+                                            Answer the question precisely and structured, leveraging all the hierarchical context collected.",
+
+                                                                    ["Summary"] = @"Summarize the main points of these documents about {0}:
+
+                                            {1}
+
+                                            Answer only with a concise list of the most important points:",
+
+                        ["GapAnalysis"] = @"Based on the question and current context, identify what information is still missing for a complete answer.
+
+                                            QUESTION: {0}
+                                            CURRENT CONTEXT: {1}
+
+                                            Answer ONLY with keywords of missing concepts/information, separated by commas.
+                                            If the context is sufficient, answer 'SUFFICIENT'."
+                    }
+                }
+            };
+        }
+
+        private DomainPromptConfig GetTIDomainConfig()
+        {
+            return new DomainPromptConfig
+            {
+                Name = "Tecnologia da Informação",
+                Description = "Configurações para projetos de TI e desenvolvimento de software",
+                Keywords = ["api", "backend", "frontend", "database", "arquitetura", "código", "classe", "método", "endpoint", "sistema", "software"],
+                Concepts = ["mvc", "rest", "microservices", "clean architecture", "design patterns", "authentication", "authorization", "crud"],
+                Prompts = new Dictionary<string, Dictionary<string, string>>
+                {
+                    ["pt"] = new Dictionary<string, string>
+                    {
+                        ["Response"] = @"Você é um especialista em desenvolvimento de software e arquitetura de sistemas.
+
+                                        PROJETO TÉCNICO: {0}
+                                        PERGUNTA TÉCNICA: ""{1}""
+                                        CONTEXTO TÉCNICO: {2}
+                                        ANÁLISE REALIZADA: {3}
+
+                                        Responda com foco técnico, incluindo:
+                                        - Implementação prática
+                                        - Boas práticas de código
+                                        - Considerações de arquitetura
+                                        - Exemplos de código quando relevante
+
+                                        Seja preciso e técnico na resposta."
+                    },
+                    ["en"] = new Dictionary<string, string>
+                    {
+                        ["Response"] = @"You are a software development and system architecture expert.
+
+                                        TECHNICAL PROJECT: {0}
+                                        TECHNICAL QUESTION: ""{1}""
+                                        TECHNICAL CONTEXT: {2}
+                                        ANALYSIS PERFORMED: {3}
+
+                                        Answer with technical focus, including:
+                                        - Practical implementation
+                                        - Code best practices
+                                        - Architecture considerations
+                                        - Code examples when relevant
+
+                                        Be precise and technical in your response."
+                    }
+                }
+            };
+        }
+
+        private DomainPromptConfig GetRHDomainConfig()
+        {
+            return new DomainPromptConfig
+            {
+                Name = "Recursos Humanos",
+                Description = "Configurações para projetos de RH e gestão de pessoas",
+                Keywords = ["funcionário", "colaborador", "cargo", "departamento", "folha", "benefícios", "treinamento", "employee", "hr"],
+                Concepts = ["gestão de pessoas", "recrutamento", "seleção", "avaliação", "desenvolvimento", "human resources"],
+                Prompts = new Dictionary<string, Dictionary<string, string>>
+                {
+                    ["pt"] = new Dictionary<string, string>
+                    {
+                        ["Response"] = @"Você é um especialista em Recursos Humanos e gestão de pessoas.
+
+                                        SISTEMA DE RH: {0}
+                                        PERGUNTA: ""{1}""
+                                        CONTEXTO: {2}
+                                        PROCESSOS ANALISADOS: {3}
+
+                                        Responda considerando:
+                                        - Políticas de RH
+                                        - Fluxos de trabalho
+                                        - Compliance e regulamentações
+                                        - Melhores práticas em gestão de pessoas
+
+                                        Seja claro e prático nas recomendações."
+                    },
+                    ["en"] = new Dictionary<string, string>
+                    {
+                        ["Response"] = @"You are a Human Resources and people management expert.
+
+                                        HR SYSTEM: {0}
+                                        QUESTION: ""{1}""
+                                        CONTEXT: {2}
+                                        ANALYZED PROCESSES: {3}
+
+                                        Answer considering:
+                                        - HR policies
+                                        - Workflows
+                                        - Compliance and regulations
+                                        - Best practices in people management
+
+                                        Be clear and practical in recommendations."
+                    }
+                }
+            };
+        }
+
+        private DomainPromptConfig GetFinanceiroDomainConfig()
+        {
+            return new DomainPromptConfig
+            {
+                Name = "Financeiro",
+                Description = "Configurações para projetos financeiros e contábeis",
+                Keywords = ["financeiro", "contábil", "faturamento", "cobrança", "pagamento", "receita", "despesa", "financial", "accounting"],
+                Concepts = ["fluxo de caixa", "conciliação", "relatórios financeiros", "impostos", "audit trail", "cash flow"],
+                Prompts = new Dictionary<string, Dictionary<string, string>>
+                {
+                    ["pt"] = new Dictionary<string, string>
+                    {
+                        ["Response"] = @"Você é um especialista em sistemas financeiros e contabilidade.
+
+                                            SISTEMA FINANCEIRO: {0}
+                                            PERGUNTA: ""{1}""
+                                            CONTEXTO FINANCEIRO: {2}
+                                            ANÁLISE REALIZADA: {3}
+
+                                            Responda considerando:
+                                            - Controles financeiros
+                                            - Auditoria e compliance
+                                            - Fluxos de aprovação
+                                            - Relatórios gerenciais
+                                            - Segurança de dados financeiros
+
+                                            Seja preciso e considere aspectos regulatórios."
+                    },
+                    ["en"] = new Dictionary<string, string>
+                    {
+                        ["Response"] = @"You are a financial systems and accounting expert.
+
+                                        FINANCIAL SYSTEM: {0}
+                                        QUESTION: ""{1}""
+                                        FINANCIAL CONTEXT: {2}
+                                        ANALYSIS PERFORMED: {3}
+
+                                        Answer considering:
+                                        - Financial controls
+                                        - Audit and compliance
+                                        - Approval workflows
+                                        - Management reports
+                                        - Financial data security
+
+                                        Be precise and consider regulatory aspects."
+                    }
+                }
+            };
+        }
+
+        private DomainPromptConfig GetQADomainConfig()
+        {
+            return new DomainPromptConfig
+            {
+                Name = "Quality Assurance",
+                Description = "Configurações para projetos de QA e testes",
+                Keywords = ["teste", "qa", "qualidade", "bug", "defeito", "validação", "verificação", "quality", "testing"],
+                Concepts = ["test cases", "automation", "regression", "performance", "security testing", "casos de teste"],
+                Prompts = new Dictionary<string, Dictionary<string, string>>
+                {
+                    ["pt"] = new Dictionary<string, string>
+                    {
+                        ["Response"] = @"Você é um especialista em Quality Assurance e testes de software.
+
+                                        PROJETO: {0}
+                                        PERGUNTA DE QA: ""{1}""
+                                        CONTEXTO DE TESTES: {2}
+                                        ANÁLISE EXECUTADA: {3}
+
+                                        Responda com foco em:
+                                        - Estratégias de teste
+                                        - Casos de teste específicos
+                                        - Automação e ferramentas
+                                        - Critérios de aceitação
+                                        - Cobertura de testes
+
+                                        Seja detalhado e metodológico na abordagem."
+                    },
+                    ["en"] = new Dictionary<string, string>
+                    {
+                        ["Response"] = @"You are a Quality Assurance and software testing expert.
+
+                                        PROJECT: {0}
+                                        QA QUESTION: ""{1}""
+                                        TESTING CONTEXT: {2}
+                                        ANALYSIS EXECUTED: {3}
+
+                                        Answer focusing on:
+                                        - Testing strategies
+                                        - Specific test cases
+                                        - Automation and tools
+                                        - Acceptance criteria
+                                        - Test coverage
+
+                                        Be detailed and methodical in your approach."
+                    }
+                }
+            };
+        }
+
+        private string GetFallbackPrompt(string promptType, string language)
+        {
+            return language == "en" ? promptType switch
+            {
+                "QueryAnalysis" => "Analyze the question: {0}",
+                "Response" => "Answer based on context: {2}",
+                "Summary" => "Summarize: {1}",
+                "GapAnalysis" => "Identify gaps for: {0}",
+                _ => "Process the request: {0}"
+            } : promptType switch
+            {
+                "QueryAnalysis" => "Analise a pergunta: {0}",
+                "Response" => "Responda baseado no contexto: {2}",
+                "Summary" => "Resuma: {1}",
+                "GapAnalysis" => "Identifique lacunas para: {0}",
+                _ => "Processe a solicitação: {0}"
+            };
+        }
+
+        /// Carrega todas as configurações de prompts
+        /// </summary>
+        public async Task LoadConfigurations()
+        {
+            lock (_lockObject)
+            {
+                try
+                {
+                    LoadBaseConfigurationSync();
+                    LoadDomainConfigurationsSync();
+                    _logger.LogInformation("Carregados {DomainCount} domínios de prompt em {ConfigPath}",
+                        _domainConfigs.Count, _configurationPath);
+                }
+                catch (Exception ex)
+                {
+                    _logger.LogError(ex, "Erro ao carregar configurações de prompt");
+                }
+            }
+        }
+
+        /// <summary>
+    }
+
+    // === MODELOS DE DADOS ===
+
+    public class PromptTemplates
+    {
+        public string QueryAnalysis { get; set; } = "";
+        public string Overview { get; set; } = "";
+        public string Specific { get; set; } = "";
+        public string Detailed { get; set; } = "";
+        public string Response { get; set; } = "";
+        public string Summary { get; set; } = "";
+        public string GapAnalysis { get; set; } = "";
+    }
+
+    public class BasePromptConfig
+    {
+        public Dictionary<string, Dictionary<string, string>> Prompts { get; set; } = new();
+    }
+
+    public class DomainPromptConfig
+    {
+        public string Name { get; set; } = "";
+        public string Description { get; set; } = "";
+        public List<string> Keywords { get; set; } = new();
+        public List<string> Concepts { get; set; } = new();
+        public Dictionary<string, Dictionary<string, string>> Prompts { get; set; } = new();
+    }
+}

Services/ResponseService/0vwtdxh2.jyi~

@@ -0,0 +1,375 @@
+using ChatApi;
+using ChatApi.Models;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.ChatCompletion;
+using Microsoft.SemanticKernel.Connectors.OpenAI;
+using Microsoft.SemanticKernel.Embeddings;
+
+#pragma warning disable SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+namespace ChatRAG.Services.ResponseService
+{
+    public class HierarchicalRAGService : IResponseService
+    {
+        private readonly ChatHistoryService _chatHistoryService;
+        private readonly Kernel _kernel;
+        private readonly TextFilter _textFilter;
+        private readonly ProjectDataRepository _projectDataRepository;
+        private readonly IChatCompletionService _chatCompletionService;
+        private readonly IVectorSearchService _vectorSearchService;
+        private readonly ILogger<HierarchicalRAGService> _logger;
+
+        public HierarchicalRAGService(
+            ChatHistoryService chatHistoryService,
+            Kernel kernel,
+            TextFilter textFilter,
+            ProjectDataRepository projectDataRepository,
+            IChatCompletionService chatCompletionService,
+            IVectorSearchService vectorSearchService,
+            ILogger<HierarchicalRAGService> logger)
+        {
+            _chatHistoryService = chatHistoryService;
+            _kernel = kernel;
+            _textFilter = textFilter;
+            _projectDataRepository = projectDataRepository;
+            _chatCompletionService = chatCompletionService;
+            _vectorSearchService = vectorSearchService;
+            _logger = logger;
+        }
+
+        public async Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question, string language = "pt")
+        {
+            var stopWatch = new System.Diagnostics.Stopwatch();
+            stopWatch.Start();
+
+            try
+            {
+                // 1. Análise da query para determinar estratégia
+                var queryAnalysis = await AnalyzeQuery(question, language);
+                _logger.LogInformation("Query Analysis: {Strategy}, Complexity: {Complexity}",
+                    queryAnalysis.Strategy, queryAnalysis.Complexity);
+
+                // 2. Execução hierárquica baseada na análise
+                var context = await ExecuteHierarchicalSearch(question, projectId, queryAnalysis);
+
+                // 3. Geração da resposta final
+                var response = await GenerateResponse(question, projectId, context, sessionId, language);
+
+                stopWatch.Stop();
+                return $"{response}\n\nTempo: {stopWatch.ElapsedMilliseconds / 1000}s\nEtapas: {context.Steps.Count}";
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro no RAG Hierárquico");
+                stopWatch.Stop();
+                return $"Erro: {ex.Message}\nTempo: {stopWatch.ElapsedMilliseconds / 1000}s";
+            }
+        }
+
+        private async Task<QueryAnalysis> AnalyzeQuery(string question, string language)
+        {
+            var analysisPrompt = language == "pt" ?
+                @"Analise esta pergunta e classifique:
+                PERGUNTA: ""{0}""
+                
+                Responda APENAS no formato JSON:
+                {{
+                    ""strategy"": ""overview|specific|detailed"",
+                    ""complexity"": ""simple|medium|complex"",
+                    ""scope"": ""global|filtered|targeted"",
+                    ""concepts"": [""conceito1"", ""conceito2""],
+                    ""needs_hierarchy"": true|false
+                }}
+                
+                REGRAS:
+                - overview: pergunta sobre projeto inteiro
+                - specific: pergunta sobre módulo/funcionalidade específica  
+                - detailed: pergunta técnica que precisa de contexto profundo
+                - needs_hierarchy: true se precisar de múltiplas buscas" :
+
+                @"Analyze this question and classify:
+                QUESTION: ""{0}""
+                
+                Answer ONLY in JSON format:
+                {{
+                    ""strategy"": ""overview|specific|detailed"",
+                    ""complexity"": ""simple|medium|complex"",
+                    ""scope"": ""global|filtered|targeted"",
+                    ""concepts"": [""concept1"", ""concept2""],
+                    ""needs_hierarchy"": true|false
+                }}
+                
+                RULES:
+                - overview: question about entire project
+                - specific: question about specific module/functionality
+                - detailed: technical question needing deep context
+                - needs_hierarchy: true if needs multiple searches";
+
+            var prompt = string.Format(analysisPrompt, question);
+
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.1,
+                MaxTokens = 200
+            };
+
+            var response = await _chatCompletionService.GetChatMessageContentAsync(prompt, executionSettings);
+
+            try
+            {
+                var jsonResponse = response.Content?.Trim() ?? "{}";
+
+                // Extrair JSON se vier com texto extra
+                var startIndex = jsonResponse.IndexOf('{');
+                var endIndex = jsonResponse.LastIndexOf('}');
+                if (startIndex >= 0 && endIndex >= startIndex)
+                {
+                    jsonResponse = jsonResponse.Substring(startIndex, endIndex - startIndex + 1);
+                }
+
+                var analysis = System.Text.Json.JsonSerializer.Deserialize<QueryAnalysis>(jsonResponse);
+                return analysis ?? new QueryAnalysis { Strategy = "specific", Complexity = "medium" };
+            }
+            catch (Exception ex)
+            {
+                _logger.LogWarning(ex, "Erro ao parsear análise da query, usando padrão");
+                return new QueryAnalysis { Strategy = "specific", Complexity = "medium" };
+            }
+        }
+
+        private async Task<HierarchicalContext> ExecuteHierarchicalSearch(string question, string projectId, QueryAnalysis analysis)
+        {
+            var context = new HierarchicalContext();
+            var embeddingService = _kernel.GetRequiredService<ITextEmbeddingGenerationService>();
+
+            switch (analysis.Strategy)
+            {
+                case "overview":
+                    await ExecuteOverviewStrategy(context, question, projectId, embeddingService);
+                    break;
+
+                case "detailed":
+                    await ExecuteDetailedStrategy(context, question, projectId, embeddingService, analysis);
+                    break;
+
+                default: // specific
+                    await ExecuteSpecificStrategy(context, question, projectId, embeddingService);
+                    break;
+            }
+
+            return context;
+        }
+
+        private async Task ExecuteOverviewStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            // Etapa 1: Buscar resumos/títulos primeiro
+            context.AddStep("Buscando visão geral do projeto");
+            var overviewResults = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+
+            // Etapa 2: Identificar documentos principais baseado na pergunta
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+            context.AddStep("Identificando documentos relevantes");
+            var relevantDocs = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.3, 5);
+
+            context.CombinedContext = $"VISÃO GERAL DO PROJETO:\n{FormatResults(overviewResults.Take(3))}\n\nDOCUMENTOS RELEVANTES:\n{FormatResults(relevantDocs)}";
+        }
+
+        private async Task ExecuteSpecificStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            // Etapa 1: Busca inicial por similaridade
+            context.AddStep("Busca inicial por similaridade");
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+            var initialResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.4, 3);
+
+            if (initialResults.Any())
+            {
+                context.AddStep("Expandindo contexto com documentos relacionados");
+
+                // Etapa 2: Expandir com contexto relacionado
+                var expandedContext = await ExpandContext(initialResults, projectId, embeddingService);
+                context.CombinedContext = $"CONTEXTO PRINCIPAL:\n{FormatResults(initialResults)}\n\nCONTEXTO EXPANDIDO:\n{FormatResults(expandedContext)}";
+            }
+            else
+            {
+                context.AddStep("Fallback para busca ampla");
+                var fallbackResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.2, 5);
+                context.CombinedContext = FormatResults(fallbackResults);
+            }
+        }
+
+        private async Task ExecuteDetailedStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService, QueryAnalysis analysis)
+        {
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+            // Etapa 1: Busca conceitual baseada nos conceitos identificados
+            context.AddStep("Busca conceitual inicial");
+            var conceptualResults = new List<VectorSearchResult>();
+
+            if (analysis.Concepts?.Any() == true)
+            {
+                foreach (var concept in analysis.Concepts)
+                {
+                    var conceptEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(concept));
+                    var conceptArray = conceptEmbedding.ToArray().Select(e => (double)e).ToArray();
+                    var conceptResults = await _vectorSearchService.SearchSimilarAsync(conceptArray, projectId, 0.3, 2);
+                    conceptualResults.AddRange(conceptResults);
+                }
+            }
+
+            // Etapa 2: Busca direta pela pergunta
+            context.AddStep("Busca direta pela pergunta");
+            var directResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.3, 3);
+
+            // Etapa 3: Síntese intermediária para identificar lacunas
+            context.AddStep("Identificando lacunas de conhecimento");
+            var intermediateContext = FormatResults(conceptualResults.Concat(directResults).DistinctBy(r => r.Id));
+            var gaps = await IdentifyKnowledgeGaps(question, intermediateContext);
+
+            // Etapa 4: Busca complementar baseada nas lacunas
+            if (!string.IsNullOrEmpty(gaps))
+            {
+                context.AddStep("Preenchendo lacunas de conhecimento");
+                var gapEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(gaps));
+                var gapArray = gapEmbedding.ToArray().Select(e => (double)e).ToArray();
+                var gapResults = await _vectorSearchService.SearchSimilarAsync(gapArray, projectId, 0.25, 2);
+
+                context.CombinedContext = $"CONTEXTO CONCEITUAL:\n{FormatResults(conceptualResults)}\n\nCONTEXTO DIRETO:\n{FormatResults(directResults)}\n\nCONTEXTO COMPLEMENTAR:\n{FormatResults(gapResults)}";
+            }
+            else
+            {
+                context.CombinedContext = $"CONTEXTO CONCEITUAL:\n{FormatResults(conceptualResults)}\n\nCONTEXTO DIRETO:\n{FormatResults(directResults)}";
+            }
+        }
+
+        private async Task<List<VectorSearchResult>> ExpandContext(List<VectorSearchResult> initialResults, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            var expandedResults = new List<VectorSearchResult>();
+
+            // Para cada resultado inicial, buscar documentos relacionados
+            foreach (var result in initialResults.Take(2)) // Limitar para evitar explosão de contexto
+            {
+                var resultEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(result.Content));
+                var embeddingArray = resultEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+                var relatedDocs = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.4, 2);
+                expandedResults.AddRange(relatedDocs.Where(r => !initialResults.Any(ir => ir.Id == r.Id)));
+            }
+
+            return expandedResults.DistinctBy(r => r.Id).ToList();
+        }
+
+        private async Task<string> IdentifyKnowledgeGaps(string question, string currentContext)
+        {
+            var gapPrompt = @"Baseado na pergunta e contexto atual, identifique que informações ainda faltam para uma resposta completa.
+            
+            PERGUNTA: {0}
+            CONTEXTO ATUAL: {1}
+            
+            Responda APENAS com palavras-chave dos conceitos/informações que ainda faltam, separados por vírgula.
+            Se o contexto for suficiente, responda 'SUFICIENTE'.";
+
+            var prompt = string.Format(gapPrompt, question, currentContext.Substring(0, Math.Min(1000, currentContext.Length)));
+
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.2,
+                MaxTokens = 100
+            };
+
+            var response = await _chatCompletionService.GetChatMessageContentAsync(prompt, executionSettings);
+            var gaps = response.Content?.Trim() ?? "";
+
+            return gaps.Equals("SUFICIENTE", StringComparison.OrdinalIgnoreCase) ? "" : gaps;
+        }
+
+        private async Task<string> GenerateResponse(string question, string projectId, HierarchicalContext context, string sessionId, string language)
+        {
+            var projectData = await _projectDataRepository.GetAsync(projectId);
+            var project = $"Nome: {projectData.Nome} \n\n Descrição:{projectData.Descricao}";
+
+            var prompt = language == "pt" ?
+                @"Você é um especialista em análise de software e QA.
+                
+                PROJETO: {0}
+                PERGUNTA: ""{1}""
+                CONTEXTO HIERÁRQUICO: {2}
+                ETAPAS EXECUTADAS: {3}
+                
+                Responda à pergunta de forma precisa e estruturada, aproveitando todo o contexto hierárquico coletado." :
+
+                @"You are a software analysis and QA expert.
+                
+                PROJECT: {0}
+                QUESTION: ""{1}""
+                HIERARCHICAL CONTEXT: {2}
+                EXECUTED STEPS: {3}
+                
+                Answer the question precisely and structured, leveraging all the hierarchical context collected.";
+
+            var finalPrompt = string.Format(prompt, project, question, context.CombinedContext,
+                string.Join(" → ", context.Steps));
+
+            var history = _chatHistoryService.GetSumarizer(sessionId);
+            history.AddUserMessage(finalPrompt);
+
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.7,
+                TopP = 1.0,
+                FrequencyPenalty = 0,
+                PresencePenalty = 0
+            };
+
+            var response = await _chatCompletionService.GetChatMessageContentAsync(history, executionSettings);
+            history.AddMessage(response.Role, response.Content ?? "");
+            _chatHistoryService.UpdateHistory(sessionId, history);
+
+            return response.Content ?? "";
+        }
+
+        private string FormatResults(IEnumerable<VectorSearchResult> results)
+        {
+            return string.Join("\n\n", results.Select((item, index) =>
+                $"=== DOCUMENTO {index + 1} ===\n" +
+                $"Relevância: {item.Score:P1}\n" +
+                $"Conteúdo: {item.Content}"));
+        }
+
+        public Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        {
+            return GetResponse(userData, projectId, sessionId, question, "pt");
+        }
+    }
+
+    // Classes de apoio para o RAG Hierárquico
+    public class QueryAnalysis
+    {
+        public string Strategy { get; set; } = "specific";
+        public string Complexity { get; set; } = "medium";
+        public string Scope { get; set; } = "filtered";
+        public string[] Concepts { get; set; } = Array.Empty<string>();
+        public bool Needs_Hierarchy { get; set; } = false;
+    }
+
+    public class HierarchicalContext
+    {
+        public List<string> Steps { get; set; } = new();
+        public string CombinedContext { get; set; } = "";
+        public Dictionary<string, object> Metadata { get; set; } = new();
+
+        public void AddStep(string step)
+        {
+            Steps.Add($"{DateTime.Now:HH:mm:ss} - {step}");
+        }
+    }
+
+}
+#pragma warning restore SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.

Services/ResponseService/ConfidenceAwareRAGService.cs

@@ -0,0 +1,385 @@
+using ChatApi;
+using ChatApi.Models;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.Confidence;
+using ChatRAG.Services.PromptConfiguration;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.ChatCompletion;
+using Microsoft.SemanticKernel.Connectors.OpenAI;
+using Microsoft.SemanticKernel.Embeddings;
+using System.Text.Json;
+using ChatRAG.Settings;
+using Microsoft.Extensions.Options;
+
+#pragma warning disable SKEXP0001 
+
+namespace ChatRAG.Services.ResponseService
+{
+    public class ConfidenceAwareRAGService : IResponseService
+    {
+        private readonly ChatHistoryService _chatHistoryService;
+        private readonly Kernel _kernel;
+        private readonly TextFilter _textFilter;
+        private readonly IProjectDataRepository _projectDataRepository;
+        private readonly IChatCompletionService _chatCompletionService;
+        private readonly IVectorSearchService _vectorSearchService;
+        private readonly ILogger<ConfidenceAwareRAGService> _logger;
+        private readonly ConfidenceVerifier _confidenceVerifier;
+        private readonly PromptConfigurationService _promptService;
+        private readonly ConfidenceAwareSettings _settings;
+
+        public ConfidenceAwareRAGService(
+            ChatHistoryService chatHistoryService,
+            Kernel kernel,
+            TextFilter textFilter,
+            IProjectDataRepository projectDataRepository,
+            IChatCompletionService chatCompletionService,
+            IVectorSearchService vectorSearchService,
+            ILogger<ConfidenceAwareRAGService> logger,
+            ConfidenceVerifier confidenceVerifier,
+            PromptConfigurationService promptService,
+            IOptions<ConfidenceAwareSettings> settings)
+        {
+            _chatHistoryService = chatHistoryService;
+            _kernel = kernel;
+            _textFilter = textFilter;
+            _projectDataRepository = projectDataRepository;
+            _chatCompletionService = chatCompletionService;
+            _vectorSearchService = vectorSearchService;
+            _logger = logger;
+            _confidenceVerifier = confidenceVerifier;
+            _promptService = promptService;
+            _settings = settings.Value;
+        }
+
+        public async Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question, string language = "pt")
+        {
+            var stopWatch = new System.Diagnostics.Stopwatch();
+            stopWatch.Start();
+            string detectedLanguage = language;
+
+            try
+            {
+                detectedLanguage = _settings.Languages.AutoDetectLanguage
+                    ? _promptService.DetectLanguage(question)
+                    : language;
+
+                var projectData = await _projectDataRepository.GetAsync(projectId);
+                var detectedDomain = _promptService.DetectDomain(question, projectData?.Descricao);
+                var prompts = _promptService.GetPrompts(detectedDomain, detectedLanguage);
+                var queryAnalysis = await AnalyzeQuery(question, detectedLanguage, prompts.QueryAnalysis);
+                var context = await ExecuteHierarchicalSearch(question, projectId, queryAnalysis, prompts, detectedLanguage);
+                var confidenceResult = await VerifyConfidenceIfEnabled(queryAnalysis, context, projectId, detectedLanguage);
+
+                if (!confidenceResult.ShouldRespond)
+                {
+                    stopWatch.Stop();
+                    var fallbackResponse = confidenceResult.SuggestedResponse ?? GetGenericFallbackMessage(detectedLanguage);
+                    return FormatFinalResponse(fallbackResponse, stopWatch.ElapsedMilliseconds, context.Steps.Count, confidenceResult);
+                }
+
+                var response = await GenerateResponse(question, projectId, context, sessionId, detectedLanguage, prompts.Response, detectedDomain);
+                stopWatch.Stop();
+                return FormatFinalResponse(response, stopWatch.ElapsedMilliseconds, context.Steps.Count, confidenceResult);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro no ConfidenceAwareRAG");
+                stopWatch.Stop();
+                var errorMessage = detectedLanguage == "en" ? $"Error: {ex.Message}" : $"Erro: {ex.Message}";
+                return $"{errorMessage}\nTempo: {stopWatch.ElapsedMilliseconds / 1000}s";
+            }
+        }
+
+        private string GetGenericFallbackMessage(string language)
+        {
+            return language == "en"
+                ? "I don't have enough information to respond safely. Could you try rephrasing the question?"
+                : "Não tenho informações suficientes para responder com segurança. Pode tentar reformular a pergunta?";
+        }
+
+        private async Task<QueryAnalysis> AnalyzeQuery(string question, string language, string promptTemplate)
+        {
+            var prompt = string.Format(promptTemplate, question);
+            var response = await _chatCompletionService.GetChatMessageContentAsync(prompt, new OpenAIPromptExecutionSettings { Temperature = 0.1, MaxTokens = 300 });
+
+            try
+            {
+                var jsonResponse = response.Content?.Trim() ?? "{}";
+                var startIndex = jsonResponse.IndexOf('{');
+                var endIndex = jsonResponse.LastIndexOf('}');
+                if (startIndex >= 0 && endIndex >= startIndex)
+                    jsonResponse = jsonResponse.Substring(startIndex, endIndex - startIndex + 1);
+
+                var analysis = JsonSerializer.Deserialize<QueryAnalysis>(jsonResponse, new JsonSerializerOptions
+                {
+                    PropertyNameCaseInsensitive = true,
+                    PropertyNamingPolicy = JsonNamingPolicy.CamelCase
+                });
+                return analysis ?? new QueryAnalysis { Strategy = "specific", Complexity = "medium" };
+            }
+            catch (Exception ex)
+            {
+                _logger.LogWarning(ex, "Erro ao parsear análise da query, usando padrão");
+                return new QueryAnalysis { Strategy = "specific", Complexity = "medium" };
+            }
+        }
+
+        private async Task<HierarchicalContext> ExecuteHierarchicalSearch(string question, string projectId, QueryAnalysis analysis, PromptTemplates prompts, string language)
+        {
+            var context = new HierarchicalContext();
+            var embeddingService = _kernel.GetRequiredService<ITextEmbeddingGenerationService>();
+            context.Metadata["DetectedLanguage"] = language;
+            context.Metadata["SearchResults"] = new List<VectorSearchResult>();
+
+            switch (analysis.Strategy)
+            {
+                case "overview":
+                    await ExecuteOverviewStrategy(context, question, projectId, embeddingService, prompts);
+                    break;
+                case "detailed":
+                    await ExecuteDetailedStrategy(context, question, projectId, embeddingService, analysis, prompts);
+                    break;
+                default:
+                    await ExecuteSpecificStrategy(context, question, projectId, embeddingService, prompts);
+                    break;
+            }
+            return context;
+        }
+
+        private async Task<ConfidenceResult> VerifyConfidenceIfEnabled(QueryAnalysis analysis, HierarchicalContext context, string projectId, string language)
+        {
+            if (!_settings.EnableConfidenceCheck)
+            {
+                return new ConfidenceResult
+                {
+                    ShouldRespond = true,
+                    ConfidenceScore = 1.0,
+                    Reason = language == "en" ? "Confidence check disabled" : "Verificação de confiança desabilitada"
+                };
+            }
+
+            var results = ExtractResultsFromContext(context, projectId);
+            return _confidenceVerifier.VerifyConfidence(analysis, results, context, _settings.UseStrictMode, language);
+        }
+
+        private List<VectorSearchResult> ExtractResultsFromContext(HierarchicalContext context, string projectId)
+        {
+            if (context.Metadata.ContainsKey("SearchResults") && context.Metadata["SearchResults"] is List<VectorSearchResult> storedResults)
+                return storedResults;
+
+            var results = new List<VectorSearchResult>();
+            var contextLength = context.CombinedContext?.Length ?? 0;
+
+            if (contextLength > 0)
+            {
+                var estimatedDocuments = Math.Max(1, Math.Min(10, contextLength / 500));
+                for (int i = 0; i < estimatedDocuments; i++)
+                {
+                    results.Add(new VectorSearchResult
+                    {
+                        Id = $"estimated_doc_{i}",
+                        Score = Math.Max(0.1, 0.8 - (i * 0.1)),
+                        Content = "Conteúdo estimado do contexto",
+                        Title = $"Documento estimado {i + 1}",
+                        ProjectId = projectId ?? "unknown"
+                    });
+                }
+            }
+            return results;
+        }
+
+        private async Task ExecuteOverviewStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService, PromptTemplates prompts)
+        {
+            context.AddStep("Buscando todos os documentos do projeto");
+            var allProjectDocs = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+            StoreSearchResults(context, allProjectDocs);
+
+            var requirementsDocs = allProjectDocs.Where(d => d.Title.ToLower().Contains("requisito") || d.Content.ToLower().Contains("requisito")).ToList();
+            var architectureDocs = allProjectDocs.Where(d => d.Title.ToLower().Contains("arquitetura") || d.Content.ToLower().Contains("arquitetura")).ToList();
+            var otherDocs = allProjectDocs.Except(requirementsDocs).Except(architectureDocs).ToList();
+
+            context.AddStep("Resumindo documentos por categoria");
+            var requirementsSummary = await SummarizeDocuments(requirementsDocs, "requisitos", prompts.Summary);
+            var architectureSummary = await SummarizeDocuments(architectureDocs, "arquitetura", prompts.Summary);
+            var otherSummary = await SummarizeDocuments(otherDocs, "outros documentos", prompts.Summary);
+
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+            var relevantDocs = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.3, 8);
+            AddToSearchResults(context, relevantDocs);
+
+            var contextParts = new List<string>();
+            if (!string.IsNullOrEmpty(requirementsSummary)) contextParts.Add($"RESUMO DOS REQUISITOS:\n{requirementsSummary}");
+            if (!string.IsNullOrEmpty(architectureSummary)) contextParts.Add($"RESUMO DA ARQUITETURA:\n{architectureSummary}");
+            if (!string.IsNullOrEmpty(otherSummary)) contextParts.Add($"OUTROS DOCUMENTOS:\n{otherSummary}");
+            contextParts.Add($"DOCUMENTOS RELEVANTES:\n{FormatResults(relevantDocs)}");
+            context.CombinedContext = string.Join("\n\n", contextParts);
+        }
+
+        private async Task ExecuteSpecificStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService, PromptTemplates prompts)
+        {
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+            var initialResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.4, 3);
+            StoreSearchResults(context, initialResults);
+
+            if (initialResults.Any())
+            {
+                var expandedContext = await ExpandContext(initialResults, projectId, embeddingService);
+                AddToSearchResults(context, expandedContext);
+                context.CombinedContext = $"CONTEXTO PRINCIPAL:\n{FormatResults(initialResults)}\n\nCONTEXTO EXPANDIDO:\n{FormatResults(expandedContext)}";
+            }
+            else
+            {
+                var fallbackResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.2, 5);
+                StoreSearchResults(context, fallbackResults);
+                context.CombinedContext = FormatResults(fallbackResults);
+            }
+        }
+
+        private async Task ExecuteDetailedStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService, QueryAnalysis analysis, PromptTemplates prompts)
+        {
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+            var conceptualResults = new List<VectorSearchResult>();
+
+            if (analysis.Concepts?.Any() == true)
+            {
+                foreach (var concept in analysis.Concepts)
+                {
+                    var conceptEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(concept));
+                    var conceptArray = conceptEmbedding.ToArray().Select(e => (double)e).ToArray();
+                    var conceptResults = await _vectorSearchService.SearchSimilarAsync(conceptArray, projectId, 0.3, 2);
+                    conceptualResults.AddRange(conceptResults);
+                }
+            }
+
+            var directResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.3, 3);
+            var allResults = conceptualResults.Concat(directResults).DistinctBy(r => r.Id).ToList();
+            StoreSearchResults(context, allResults);
+
+            var intermediateContext = FormatResults(allResults);
+            var gaps = await IdentifyKnowledgeGaps(question, intermediateContext, prompts.GapAnalysis);
+
+            if (!string.IsNullOrEmpty(gaps))
+            {
+                var gapEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(gaps));
+                var gapArray = gapEmbedding.ToArray().Select(e => (double)e).ToArray();
+                var gapResults = await _vectorSearchService.SearchSimilarAsync(gapArray, projectId, 0.25, 2);
+                AddToSearchResults(context, gapResults);
+                context.CombinedContext = $"CONTEXTO CONCEITUAL:\n{FormatResults(conceptualResults)}\n\nCONTEXTO DIRETO:\n{FormatResults(directResults)}\n\nCONTEXTO COMPLEMENTAR:\n{FormatResults(gapResults)}";
+            }
+            else
+            {
+                context.CombinedContext = $"CONTEXTO CONCEITUAL:\n{FormatResults(conceptualResults)}\n\nCONTEXTO DIRETO:\n{FormatResults(directResults)}";
+            }
+        }
+
+        private async Task<string> GenerateResponse(string question, string projectId, HierarchicalContext context, string sessionId, string language, string promptTemplate, string? domain)
+        {
+            var projectData = await _projectDataRepository.GetAsync(projectId);
+            var project = $"Nome: {projectData.Nome}\nDescrição: {projectData.Descricao}";
+            if (!string.IsNullOrEmpty(domain)) project += $"\nDomínio: {domain}";
+
+            var finalPrompt = string.Format(promptTemplate, project, question, context.CombinedContext, string.Join(" → ", context.Steps));
+            var history = _chatHistoryService.GetSumarizer(sessionId);
+            history.AddUserMessage(finalPrompt);
+
+            var response = await _chatCompletionService.GetChatMessageContentAsync(history, new OpenAIPromptExecutionSettings { Temperature = 0.6 });
+            history.AddMessage(response.Role, response.Content ?? "");
+            _chatHistoryService.UpdateHistory(sessionId, history);
+            return response.Content ?? "";
+        }
+
+        private string FormatFinalResponse(string response, long milliseconds, int steps, ConfidenceResult? confidence = null)
+        {
+            var result = response;
+            if (_settings.ShowDebugInfo)
+            {
+                result += $"\n\n📊 **Debug Info:**\n⏱️ Tempo: {milliseconds / 1000}s\n🔍 Etapas: {steps}";
+                if (confidence != null)
+                {
+                    result += $"\n🎯 Confiança: {confidence.ConfidenceScore:P1}\n📋 Estratégia: {confidence.Strategy}";
+                    result += $"\n✅ Deve responder: {(confidence.ShouldRespond ? "Sim" : "Não")}";
+                    if (!string.IsNullOrEmpty(confidence.Reason)) result += $"\n💭 Motivo: {confidence.Reason}";
+                }
+            }
+            return result;
+        }
+
+        private string FormatResults(IEnumerable<VectorSearchResult> results)
+        {
+            return string.Join("\n\n", results.Select((item, index) => $"=== DOCUMENTO {index + 1} ===\nRelevância: {item.Score:P1}\nConteúdo: {item.Content}"));
+        }
+
+        private void StoreSearchResults(HierarchicalContext context, List<VectorSearchResult> results)
+        {
+            if (!context.Metadata.ContainsKey("SearchResults")) context.Metadata["SearchResults"] = new List<VectorSearchResult>();
+            ((List<VectorSearchResult>)context.Metadata["SearchResults"]).AddRange(results);
+        }
+
+        private void AddToSearchResults(HierarchicalContext context, List<VectorSearchResult> additionalResults)
+        {
+            if (context.Metadata.ContainsKey("SearchResults"))
+            {
+                var storedResults = (List<VectorSearchResult>)context.Metadata["SearchResults"];
+                storedResults.AddRange(additionalResults.Where(r => !storedResults.Any(sr => sr.Id == r.Id)));
+            }
+            else StoreSearchResults(context, additionalResults);
+        }
+
+        private async Task<List<VectorSearchResult>> ExpandContext(List<VectorSearchResult> initialResults, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            var expandedResults = new List<VectorSearchResult>();
+            foreach (var result in initialResults.Take(2))
+            {
+                var resultEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(result.Content));
+                var embeddingArray = resultEmbedding.ToArray().Select(e => (double)e).ToArray();
+                var relatedDocs = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.4, 2);
+                expandedResults.AddRange(relatedDocs.Where(r => !initialResults.Any(ir => ir.Id == r.Id)));
+            }
+            return expandedResults.DistinctBy(r => r.Id).ToList();
+        }
+
+        private async Task<string> SummarizeDocuments(List<VectorSearchResult> documents, string category, string promptTemplate)
+        {
+            if (!documents.Any()) return string.Empty;
+            if (documents.Count <= 3) return FormatResults(documents);
+
+            var chunks = documents.Chunk(5).ToList();
+            var tasks = chunks.Select(async chunk =>
+            {
+                try
+                {
+                    var prompt = string.Format(promptTemplate, category, FormatResults(chunk));
+                    var response = await _chatCompletionService.GetChatMessageContentAsync(prompt, new OpenAIPromptExecutionSettings { Temperature = 0.1, MaxTokens = 300 });
+                    return response.Content ?? string.Empty;
+                }
+                catch { return FormatResults(chunk); }
+            });
+
+            var summaries = await Task.WhenAll(tasks);
+            var validSummaries = summaries.Where(s => !string.IsNullOrEmpty(s)).ToList();
+            return validSummaries.Count > 1 ? string.Join("\n\n", validSummaries) : validSummaries.FirstOrDefault() ?? string.Empty;
+        }
+
+        private async Task<string> IdentifyKnowledgeGaps(string question, string currentContext, string promptTemplate)
+        {
+            var prompt = string.Format(promptTemplate, question, currentContext.Substring(0, Math.Min(1000, currentContext.Length)));
+            var response = await _chatCompletionService.GetChatMessageContentAsync(prompt, new OpenAIPromptExecutionSettings { Temperature = 0.2, MaxTokens = 100 });
+            var gaps = response.Content?.Trim() ?? "";
+            return gaps.Equals("SUFICIENTE", StringComparison.OrdinalIgnoreCase) ? "" : gaps;
+        }
+
+        public Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        {
+            return GetResponse(userData, projectId, sessionId, question, "pt");
+        }
+    }
+}
+
+#pragma warning restore SKEXP0001

Services/ResponseService/HierarchicalRAGService.cs

@@ -0,0 +1,572 @@
+using ChatApi;
+using ChatApi.Models;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.ChatCompletion;
+using Microsoft.SemanticKernel.Connectors.OpenAI;
+using Microsoft.SemanticKernel.Embeddings;
+using System.Text.Json;
+
+#pragma warning disable SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+namespace ChatRAG.Services.ResponseService
+{
+    public class HierarchicalRAGService : IResponseService
+    {
+        private readonly ChatHistoryService _chatHistoryService;
+        private readonly Kernel _kernel;
+        private readonly TextFilter _textFilter;
+        private readonly IProjectDataRepository _projectDataRepository;
+        private readonly IChatCompletionService _chatCompletionService;
+        private readonly IVectorSearchService _vectorSearchService;
+        private readonly ILogger<HierarchicalRAGService> _logger;
+
+        public HierarchicalRAGService(
+            ChatHistoryService chatHistoryService,
+            Kernel kernel,
+            TextFilter textFilter,
+            IProjectDataRepository projectDataRepository,
+            IChatCompletionService chatCompletionService,
+            IVectorSearchService vectorSearchService,
+            ILogger<HierarchicalRAGService> logger)
+        {
+            _chatHistoryService = chatHistoryService;
+            _kernel = kernel;
+            _textFilter = textFilter;
+            _projectDataRepository = projectDataRepository;
+            _chatCompletionService = chatCompletionService;
+            _vectorSearchService = vectorSearchService;
+            _logger = logger;
+        }
+
+        public async Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question, string language = "pt")
+        {
+            var stopWatch = new System.Diagnostics.Stopwatch();
+            stopWatch.Start();
+
+            try
+            {
+                // 1. Análise da query para determinar estratégia
+                var queryAnalysis = await AnalyzeQuery(question, language);
+                _logger.LogInformation("Query Analysis: {Strategy}, Complexity: {Complexity}",
+                    queryAnalysis.Strategy, queryAnalysis.Complexity);
+
+                // 2. Execução hierárquica baseada na análise
+                var context = await ExecuteHierarchicalSearch(question, projectId, queryAnalysis);
+
+                // 3. Geração da resposta final
+                var response = await GenerateResponse(question, projectId, context, sessionId, language);
+
+                stopWatch.Stop();
+                return $"{response}\n\nTempo: {stopWatch.ElapsedMilliseconds / 1000}s\nEtapas: {context.Steps.Count}";
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro no RAG Hierárquico");
+                stopWatch.Stop();
+                return $"Erro: {ex.Message}\nTempo: {stopWatch.ElapsedMilliseconds / 1000}s";
+            }
+        }
+
+        private async Task<QueryAnalysis> AnalyzeQuery(string question, string language)
+        {
+            var analysisPrompt = language == "pt" ?
+                @"Analise esta pergunta e classifique com precisão:
+        PERGUNTA: ""{0}""
+        
+        Responda APENAS no formato JSON:
+        {{
+            ""strategy"": ""overview|specific|detailed|out_of_scope"",
+            ""complexity"": ""simple|medium|complex"",
+            ""scope"": ""global|filtered|targeted"",
+            ""concepts"": [""conceito1"", ""conceito2""],
+            ""needs_hierarchy"": true|false,
+        }}
+        
+        DEFINIÇÕES PRECISAS:
+        
+        STRATEGY:
+        - overview: Pergunta sobre o PROJETO COMO UM TODO. Palavras-chave: ""projeto"", ""sistema"", ""aplicação"", ""este projeto"", ""todo o"", ""geral"", ""inteiro"". NÃO menciona módulos, funcionalidades ou tecnologias específicas.
+        - out_of_scope: Pergunta/frase sem sentido relacionada à projetos. Saudações, cumprimentos, perguntas sem sentido, etc. Palavras-chave: ""oi"", ""olá"", ""bom dia"", ""boa tarde"", ""quem"", ""quando"", ""etc"". NÃO menciona projetos e contém apenas uma saudação ou o usuário se apresentando, sem falar mais nada além disso.
+        - specific: Pergunta sobre MÓDULO/FUNCIONALIDADE ESPECÍFICA. Menciona: nome de classe, controller, entidade, CRUD específico, funcionalidade particular, tecnologia específica.
+        - detailed: Pergunta técnica específica que precisa de CONTEXTO PROFUNDO e detalhes de implementação.
+        - out_of_scope: Suadação, pergunta sem relação com os textos ou fora de contexto
+        
+        SCOPE:
+        - global: Busca informações de TODO o projeto (usar com overview ou com out_of_scope)
+        - filtered: Busca com filtros específicos (usar com specific/detailed)
+        - targeted: Busca muito específica e direcionada
+        
+        EXEMPLOS:
+        - ""Gere casos de teste para este projeto"" → overview/global
+        - ""Gere casos de teste do projeto"" → overview/global  
+        - ""Gere casos de teste para o CRUD de usuário"" → specific/filtered
+        - ""Como implementar autenticação JWT neste controller"" → detailed/targeted
+        - ""Documente este sistema"" → overview/global
+        - ""Oi!"" → out_of_scope/global
+        - ""Boa tarde!"" → out_of_scope/global
+        - ""Meu nome é [nome de usuario]"" → out_of_scope/global
+        - ""Faça uma conta"" → out_of_scope/global
+        - ""Me passe a receita de bolo?"" → out_of_scope/global
+        - ""Explique a classe UserService"" → specific/filtered" :
+
+                @"Analyze this question and classify precisely:
+        QUESTION: ""{0}""
+        
+        Answer ONLY in JSON format:
+        {{
+            ""strategy"": ""overview|specific|detailed|out_of_scope"",
+            ""complexity"": ""simple|medium|complex"",
+            ""scope"": ""global|filtered|targeted"",
+            ""concepts"": [""concept1"", ""concept2""],
+            ""needs_hierarchy"": true|false
+        }}
+        
+        PRECISE DEFINITIONS:
+        
+        STRATEGY:
+        - overview: Question about the PROJECT AS A WHOLE. Keywords: ""project"", ""system"", ""application"", ""this project"", ""entire"", ""general"", ""whole"". Does NOT mention specific modules, functionalities or technologies.
+        - out_of_scope: Meaningless question/phrase related to projects. Greetings, salutations, meaningless questions, etc. Keywords: ""hi"", ""hello"", ""good morning"", ""good afternoon"", ""who"", ""when"", ""etc"". Does NOT mention projects and contains only a greeting or the user introducing themselves, without saying anything else.
+        - specific: Question about SPECIFIC MODULE/FUNCTIONALITY. Mentions: class name, controller, entity, specific CRUD, particular functionality, specific technology.
+        - detailed: Technical specific question needing DEEP CONTEXT and implementation details.
+        
+        SCOPE:
+        - global: Search information from ENTIRE project (use with overview or out_of_scope)
+        - filtered: Search with specific filters (use with specific/detailed)
+        - targeted: Very specific and directed search
+        
+        EXAMPLES:
+        - ""Generate test cases for this project"" → overview/global
+        - ""Generate test cases for user CRUD"" → specific/filtered
+        - ""How to implement JWT authentication in this controller"" → detailed/targeted
+        - ""Document this system"" → overview/global
+        - ""Hi!"" → out_of_scope/global
+        - ""Good afternoon!"" → out_of_scope/global
+        - ""My name is [nome de usuario]"" → out_of_scope/global
+        - ""Do an operation math for me"" → out_of_scope/global
+        - ""Give me the recipe for a cake?"" → out_of_scope/global
+        - ""Explain the UserService class"" → specific/filtered";
+
+            var prompt = string.Format(analysisPrompt, question);
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.1,
+                MaxTokens = 300 // Aumentei um pouco para acomodar o prompt maior
+            };
+            var response = await _chatCompletionService.GetChatMessageContentAsync(prompt, executionSettings);
+
+            try
+            {
+                var jsonResponse = response.Content?.Trim() ?? "{}";
+                // Extrair JSON se vier com texto extra
+                var startIndex = jsonResponse.IndexOf('{');
+                var endIndex = jsonResponse.LastIndexOf('}');
+                if (startIndex >= 0 && endIndex >= startIndex)
+                {
+                    jsonResponse = jsonResponse.Substring(startIndex, endIndex - startIndex + 1);
+                }
+
+                var options = new JsonSerializerOptions
+                {
+                    PropertyNameCaseInsensitive = true,
+                    PropertyNamingPolicy = JsonNamingPolicy.CamelCase
+                };
+
+                var analysis = System.Text.Json.JsonSerializer.Deserialize<QueryAnalysis>(jsonResponse, options);
+
+                // Log para debug - remover em produção
+                _logger.LogInformation($"Query: '{question}' → Strategy: {analysis?.Strategy}, Scope: {analysis?.Scope}");
+
+                return analysis ?? new QueryAnalysis { Strategy = "specific", Complexity = "medium" };
+            }
+            catch (Exception ex)
+            {
+                _logger.LogWarning(ex, "Erro ao parsear análise da query, usando padrão");
+                return new QueryAnalysis { Strategy = "specific", Complexity = "medium" };
+            }
+        }
+
+        private async Task<HierarchicalContext> ExecuteHierarchicalSearch(string question, string projectId, QueryAnalysis analysis)
+        {
+            var context = new HierarchicalContext();
+            var embeddingService = _kernel.GetRequiredService<ITextEmbeddingGenerationService>();
+
+            switch (analysis.Strategy)
+            {
+                case "out_of_scope":
+                    await ExecuteOutOfContextStrategy(context, question, projectId, embeddingService);
+                    break;
+                case "overview":
+                    await ExecuteOverviewStrategy(context, question, projectId, embeddingService);
+                    break;
+
+                case "detailed":
+                    await ExecuteDetailedStrategy(context, question, projectId, embeddingService, analysis);
+                    break;
+
+                default: // specific
+                    await ExecuteSpecificStrategy(context, question, projectId, embeddingService);
+                    break;
+            }
+
+            return context;
+        }
+
+        private async Task ExecuteOutOfContextStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            context.AddStep("Buscando o projeto");
+            var project = _projectDataRepository.GetAsync(projectId);
+
+            context.CombinedContext = string.Join("\n\n", project);
+        }
+
+
+
+        private async Task ExecuteOverviewStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            // Etapa 1: Buscar TODOS os documentos do projeto
+            context.AddStep("Buscando todos os documentos do projeto");
+            var allProjectDocs = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+
+            // Etapa 2: Categorizar documentos por tipo/importância
+            context.AddStep("Categorizando e resumindo contexto do projeto");
+
+            // Etapa 2: Categorizar documentos por tipo baseado nos seus dados reais
+            context.AddStep("Categorizando e resumindo contexto do projeto");
+
+            var requirementsDocs = allProjectDocs.Where(d =>
+                d.Title.ToLower().StartsWith("requisito") ||
+                d.Title.ToLower().Contains("requisito") ||
+                d.Content.ToLower().Contains("requisito") ||
+                d.Content.ToLower().Contains("funcionalidade") ||
+                d.Content.ToLower().Contains("aplicação deve") ||
+                d.Content.ToLower().Contains("sistema deve")).ToList();
+
+            var architectureDocs = allProjectDocs.Where(d =>
+                d.Title.ToLower().Contains("arquitetura") ||
+                d.Title.ToLower().Contains("estrutura") ||
+                d.Title.ToLower().Contains("documentação") ||
+                d.Title.ToLower().Contains("readme") ||
+                d.Content.ToLower().Contains("arquitetura") ||
+                d.Content.ToLower().Contains("estrutura") ||
+                d.Content.ToLower().Contains("tecnologia")).ToList();
+
+            // Documentos que não são requisitos nem arquitetura (códigos, outros docs)
+            var otherDocs = allProjectDocs
+                .Except(requirementsDocs)
+                .Except(architectureDocs)
+                .ToList();
+
+            // Etapa 3: Resumir cada categoria se tiver muitos documentos
+            var requirementsSummary = await SummarizeDocuments(requirementsDocs, "requisitos e funcionalidades do projeto");
+            var architectureSummary = await SummarizeDocuments(architectureDocs, "arquitetura e documentação técnica");
+            var otherSummary = await SummarizeDocuments(otherDocs, "outros documentos do projeto");
+
+            // Etapa 4: Busca específica para a pergunta (mantém precisão)
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+            context.AddStep("Identificando documentos específicos para a pergunta");
+            var relevantDocs = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.3, 8);
+
+            // Etapa 5: Combinar resumos + documentos específicos
+            var contextParts = new List<string>();
+
+            if (!string.IsNullOrEmpty(requirementsSummary))
+                contextParts.Add($"RESUMO DOS REQUISITOS E FUNCIONALIDADES:\n{requirementsSummary}");
+
+            if (!string.IsNullOrEmpty(architectureSummary))
+                contextParts.Add($"RESUMO DA ARQUITETURA E DOCUMENTAÇÃO:\n{architectureSummary}");
+
+            if (!string.IsNullOrEmpty(otherSummary))
+                contextParts.Add($"OUTROS DOCUMENTOS DO PROJETO:\n{otherSummary}");
+
+            contextParts.Add($"DOCUMENTOS MAIS RELEVANTES PARA A PERGUNTA:\n{FormatResults(relevantDocs)}");
+
+            context.CombinedContext = string.Join("\n\n", contextParts);
+        }
+
+        private async Task<string> SummarizeDocuments(List<VectorSearchResult> documents, string category)
+        {
+            if (!documents.Any()) return string.Empty;
+
+            // Se poucos documentos, usar todos sem resumir
+            if (documents.Count <= 3)
+            {
+                return FormatResults(documents);
+            }
+
+            // Se muitos documentos, resumir em chunks
+            var chunks = documents.Chunk(5).ToList(); // Grupos de 5 documentos
+            var tasks = new List<Task<string>>();
+
+            // Semáforo para controlar concorrência (máximo 3 chamadas simultâneas)
+            var semaphore = new SemaphoreSlim(3, 3);
+
+            foreach (var chunk in chunks)
+            {
+                var chunkContent = FormatResults(chunk);
+
+                tasks.Add(Task.Run(async () =>
+                {
+                    await semaphore.WaitAsync();
+                    try
+                    {
+                        var summaryPrompt = $@"Resuma os pontos principais destes documentos sobre {category}:
+
+                            {chunkContent}
+
+                            Responda apenas com uma lista concisa dos pontos mais importantes:";
+
+                        var response = await _chatCompletionService.GetChatMessageContentAsync(
+                            summaryPrompt,
+                            new OpenAIPromptExecutionSettings
+                            {
+                                Temperature = 0.1,
+                                MaxTokens = 300
+                            });
+
+                        return response.Content ?? string.Empty;
+                    }
+                    catch (Exception ex)
+                    {
+                        _logger.LogWarning(ex, $"Erro ao resumir chunk de {category}, usando conteúdo original");
+                        return chunkContent;
+                    }
+                    finally
+                    {
+                        semaphore.Release();
+                    }
+                }));
+            }
+
+            // Aguardar todas as tasks de resumo
+            var summaries = await Task.WhenAll(tasks);
+            var validSummaries = summaries.Where(s => !string.IsNullOrEmpty(s)).ToList();
+
+            // Se tiver múltiplos resumos, consolidar
+            if (validSummaries.Count > 1)
+            {
+                var consolidationPrompt = $@"Consolide estes resumos sobre {category} em um resumo final:
+
+                    {string.Join("\n\n", validSummaries)}
+
+                    Responda com os pontos mais importantes organizados:";
+
+                try
+                {
+                    var finalResponse = await _chatCompletionService.GetChatMessageContentAsync(
+                        consolidationPrompt,
+                        new OpenAIPromptExecutionSettings
+                        {
+                            Temperature = 0.1,
+                            MaxTokens = 400
+                        });
+
+                    return finalResponse.Content ?? string.Empty;
+                }
+                catch
+                {
+                    return string.Join("\n\n", validSummaries);
+                }
+            }
+
+            return validSummaries.FirstOrDefault() ?? string.Empty;
+        }
+
+        private async Task ExecuteSpecificStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            // Etapa 1: Busca inicial por similaridade
+            context.AddStep("Busca inicial por similaridade");
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+            var initialResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.4, 3);
+
+            if (initialResults.Any())
+            {
+                context.AddStep("Expandindo contexto com documentos relacionados");
+
+                // Etapa 2: Expandir com contexto relacionado
+                var expandedContext = await ExpandContext(initialResults, projectId, embeddingService);
+                context.CombinedContext = $"CONTEXTO PRINCIPAL:\n{FormatResults(initialResults)}\n\nCONTEXTO EXPANDIDO:\n{FormatResults(expandedContext)}";
+            }
+            else
+            {
+                context.AddStep("Fallback para busca ampla");
+                var fallbackResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.2, 5);
+                context.CombinedContext = FormatResults(fallbackResults);
+            }
+        }
+
+        private async Task ExecuteDetailedStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService, QueryAnalysis analysis)
+        {
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+            // Etapa 1: Busca conceitual baseada nos conceitos identificados
+            context.AddStep("Busca conceitual inicial");
+            var conceptualResults = new List<VectorSearchResult>();
+
+            if (analysis.Concepts?.Any() == true)
+            {
+                foreach (var concept in analysis.Concepts)
+                {
+                    var conceptEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(concept));
+                    var conceptArray = conceptEmbedding.ToArray().Select(e => (double)e).ToArray();
+                    var conceptResults = await _vectorSearchService.SearchSimilarAsync(conceptArray, projectId, 0.3, 2);
+                    conceptualResults.AddRange(conceptResults);
+                }
+            }
+
+            // Etapa 2: Busca direta pela pergunta
+            context.AddStep("Busca direta pela pergunta");
+            var directResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.3, 3);
+
+            // Etapa 3: Síntese intermediária para identificar lacunas
+            context.AddStep("Identificando lacunas de conhecimento");
+            var intermediateContext = FormatResults(conceptualResults.Concat(directResults).DistinctBy(r => r.Id));
+            var gaps = await IdentifyKnowledgeGaps(question, intermediateContext);
+
+            // Etapa 4: Busca complementar baseada nas lacunas
+            if (!string.IsNullOrEmpty(gaps))
+            {
+                context.AddStep("Preenchendo lacunas de conhecimento");
+                var gapEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(gaps));
+                var gapArray = gapEmbedding.ToArray().Select(e => (double)e).ToArray();
+                var gapResults = await _vectorSearchService.SearchSimilarAsync(gapArray, projectId, 0.25, 2);
+
+                context.CombinedContext = $"CONTEXTO CONCEITUAL:\n{FormatResults(conceptualResults)}\n\nCONTEXTO DIRETO:\n{FormatResults(directResults)}\n\nCONTEXTO COMPLEMENTAR:\n{FormatResults(gapResults)}";
+            }
+            else
+            {
+                context.CombinedContext = $"CONTEXTO CONCEITUAL:\n{FormatResults(conceptualResults)}\n\nCONTEXTO DIRETO:\n{FormatResults(directResults)}";
+            }
+        }
+
+        private async Task<List<VectorSearchResult>> ExpandContext(List<VectorSearchResult> initialResults, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            var expandedResults = new List<VectorSearchResult>();
+
+            // Para cada resultado inicial, buscar documentos relacionados
+            foreach (var result in initialResults.Take(2)) // Limitar para evitar explosão de contexto
+            {
+                var resultEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(result.Content));
+                var embeddingArray = resultEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+                var relatedDocs = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.4, 2);
+                expandedResults.AddRange(relatedDocs.Where(r => !initialResults.Any(ir => ir.Id == r.Id)));
+            }
+
+            return expandedResults.DistinctBy(r => r.Id).ToList();
+        }
+
+        private async Task<string> IdentifyKnowledgeGaps(string question, string currentContext)
+        {
+            var gapPrompt = @"Baseado na pergunta e contexto atual, identifique que informações ainda faltam para uma resposta completa.
+            
+            PERGUNTA: {0}
+            CONTEXTO ATUAL: {1}
+            
+            Responda APENAS com palavras-chave dos conceitos/informações que ainda faltam, separados por vírgula.
+            Se o contexto for suficiente, responda 'SUFICIENTE'.";
+
+            var prompt = string.Format(gapPrompt, question, currentContext.Substring(0, Math.Min(1000, currentContext.Length)));
+
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.2,
+                MaxTokens = 100
+            };
+
+            var response = await _chatCompletionService.GetChatMessageContentAsync(prompt, executionSettings);
+            var gaps = response.Content?.Trim() ?? "";
+
+            return gaps.Equals("SUFICIENTE", StringComparison.OrdinalIgnoreCase) ? "" : gaps;
+        }
+
+        private async Task<string> GenerateResponse(string question, string projectId, HierarchicalContext context, string sessionId, string language)
+        {
+            var projectData = await _projectDataRepository.GetAsync(projectId);
+            var project = $"Nome: {projectData.Nome} \n\n Descrição:{projectData.Descricao}";
+
+            var prompt = language == "pt" ?
+                @"Você é um especialista em análise de software e QA, mas também atende ao chat.
+                
+                PROJETO: {0}
+                PERGUNTA: ""{1}""
+                CONTEXTO HIERÁRQUICO: {2}
+                ETAPAS EXECUTADAS: {3}
+                
+                Responda à pergunta de forma precisa e estruturada, aproveitando todo o contexto hierárquico coletado. Se for uma saudação ou não for uma pergunta relativa ao contexto, avise que não entendeu." :
+
+                @"You are a software analysis and QA expert.
+                
+                PROJECT: {0}
+                QUESTION: ""{1}""
+                HIERARCHICAL CONTEXT: {2}
+                EXECUTED STEPS: {3}
+                
+                Answer the question precisely and structured, leveraging all the hierarchical context collected.";
+
+            var finalPrompt = string.Format(prompt, project, question, context.CombinedContext,
+                string.Join(" → ", context.Steps));
+
+            var history = _chatHistoryService.GetSumarizer(sessionId);
+            history.AddUserMessage(finalPrompt);
+
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.7,
+                TopP = 1.0,
+                FrequencyPenalty = 0,
+                PresencePenalty = 0
+            };
+
+            var response = await _chatCompletionService.GetChatMessageContentAsync(history, executionSettings);
+            history.AddMessage(response.Role, response.Content ?? "");
+            _chatHistoryService.UpdateHistory(sessionId, history);
+
+            return response.Content ?? "";
+        }
+
+        private string FormatResults(IEnumerable<VectorSearchResult> results)
+        {
+            return string.Join("\n\n", results.Select((item, index) =>
+                $"=== DOCUMENTO {index + 1} ===\n" +
+                $"Relevância: {item.Score:P1}\n" +
+                $"Conteúdo: {item.Content}"));
+        }
+
+        public Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        {
+            return GetResponse(userData, projectId, sessionId, question, "pt");
+        }
+    }
+
+    // Classes de apoio para o RAG Hierárquico
+    public class QueryAnalysis
+    {
+        public string Strategy { get; set; } = "specific";
+        public string Complexity { get; set; } = "medium";
+        public string Scope { get; set; } = "filtered";
+        public string[] Concepts { get; set; } = Array.Empty<string>();
+        public bool Needs_Hierarchy { get; set; } = false;
+    }
+
+    public class HierarchicalContext
+    {
+        public List<string> Steps { get; set; } = new();
+        public string CombinedContext { get; set; } = "";
+        public Dictionary<string, object> Metadata { get; set; } = new();
+
+        public void AddStep(string step)
+        {
+            Steps.Add($"{DateTime.Now:HH:mm:ss} - {step}");
+        }
+    }
+
+}
+#pragma warning restore SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.

Services/ResponseService/MongoResponseService.cs

@@ -0,0 +1,118 @@
+using ChatApi.Models;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using Microsoft.SemanticKernel.Embeddings;
+
+#pragma warning disable SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+namespace ChatRAG.Services.ResponseService
+{
+    public class MongoResponseService : IResponseService
+    {
+        private readonly ResponseRAGService _originalService; // Sua classe atual!
+        private readonly IVectorSearchService _vectorSearchService;
+        private readonly ITextEmbeddingGenerationService _embeddingService;
+        private readonly TextFilter _textFilter;
+
+        public MongoResponseService(
+            ResponseRAGService originalService,
+            IVectorSearchService vectorSearchService,
+            ITextEmbeddingGenerationService embeddingService,
+            TextFilter textFilter)
+        {
+            _originalService = originalService;
+            _vectorSearchService = vectorSearchService;
+            _embeddingService = embeddingService;
+            _textFilter = textFilter;
+        }
+
+        public string ProviderName => "MongoDB";
+
+        // ========================================
+        // MÉTODO ORIGINAL - Delega para ResponseRAGService
+        // ========================================
+        public async Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question, string language="pt")
+        {
+            return await _originalService.GetResponse(userData, projectId, sessionId, question);
+        }
+
+        // ========================================
+        // MÉTODO ESTENDIDO COM MAIS DETALHES
+        // ========================================
+        public async Task<ResponseResult> GetResponseDetailed(
+            UserData userData,
+            string projectId,
+            string sessionId,
+            string question,
+            ResponseOptions? options = null)
+        {
+            options ??= new ResponseOptions();
+            var stopwatch = System.Diagnostics.Stopwatch.StartNew();
+
+            // Gera embedding da pergunta
+            var embeddingPergunta = await _embeddingService.GenerateEmbeddingAsync(
+                _textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = embeddingPergunta.ToArray().Select(e => (double)e).ToArray();
+
+            var searchStart = stopwatch.ElapsedMilliseconds;
+
+            // Busca documentos similares usando a interface
+            var documentos = await _vectorSearchService.SearchSimilarDynamicAsync(
+                embeddingArray,
+                projectId,
+                options.SimilarityThreshold,
+                options.MaxContextDocuments);
+
+            var searchTime = stopwatch.ElapsedMilliseconds - searchStart;
+            var llmStart = stopwatch.ElapsedMilliseconds;
+
+            // Chama o método original para gerar resposta
+            var response = await _originalService.GetResponse(userData, projectId, sessionId, question);
+
+            var llmTime = stopwatch.ElapsedMilliseconds - llmStart;
+            stopwatch.Stop();
+
+            // Monta resultado detalhado
+            return new ResponseResult
+            {
+                Content = response,
+                Provider = "MongoDB",
+                Sources = documentos.Select(d => new SourceDocument
+                {
+                    Id = d.Id,
+                    Title = d.Title,
+                    Content = d.Content,
+                    Similarity = d.Score,
+                    Metadata = d.Metadata
+                }).ToList(),
+                Metrics = new ResponseMetrics
+                {
+                    TotalTimeMs = stopwatch.ElapsedMilliseconds,
+                    SearchTimeMs = searchTime,
+                    LlmTimeMs = llmTime,
+                    DocumentsFound = documentos.Count,
+                    DocumentsUsed = documentos.Count,
+                    AverageSimilarity = documentos.Any() ? documentos.Average(d => d.Score) : 0
+                }
+            };
+        }
+
+        public async Task<ResponseStats> GetStatsAsync()
+        {
+            // Implementação básica - pode ser expandida
+            return new ResponseStats
+            {
+                TotalRequests = 0,
+                AverageResponseTime = 0,
+                RequestsByProject = new Dictionary<string, int>(),
+                LastRequest = DateTime.UtcNow
+            };
+        }
+
+        public Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        {
+            return this.GetResponse(userData, projectId, sessionId, question, "pt");
+        }
+    }
+}
+#pragma warning restore SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.

Services/ResponseService/QdrantResponseService.cs

@@ -0,0 +1,212 @@
+#pragma warning disable SKEXP0001
+
+using ChatApi.Models;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.ChatCompletion;
+using Microsoft.SemanticKernel.Embeddings;
+
+namespace ChatRAG.Services.ResponseService
+{
+    public class QdrantResponseService : IResponseService
+    {
+        private readonly IVectorSearchService _vectorSearchService;
+        private readonly ITextEmbeddingGenerationService _embeddingService;
+        private readonly IChatCompletionService _chatService;
+        private readonly ILogger<QdrantResponseService> _logger;
+
+        public QdrantResponseService(
+            IVectorSearchService vectorSearchService,
+            ITextEmbeddingGenerationService embeddingService,
+            IChatCompletionService chatService,
+            ILogger<QdrantResponseService> logger)
+        {
+            _vectorSearchService = vectorSearchService;
+            _embeddingService = embeddingService;
+            _chatService = chatService;
+            _logger = logger;
+        }
+
+        public string ProviderName => "Qdrant";
+
+        public async Task<string> GetResponse(
+            UserData userData,
+            string projectId,
+            string sessionId,
+            string userMessage,
+            string language = "pt")
+        {
+            try
+            {
+                _logger.LogInformation("Processando consulta RAG com Qdrant para projeto {ProjectId}", projectId);
+
+                // 1. Gerar embedding da pergunta do usuário
+                var questionEmbedding = await _embeddingService.GenerateEmbeddingAsync(userMessage);
+                var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+                // 2. Buscar documentos similares no Qdrant
+                var searchResults = await _vectorSearchService.SearchSimilarDynamicAsync(
+                    queryEmbedding: embeddingArray,
+                    projectId: projectId,
+                    minThreshold: 0.5,
+                    limit: 5
+                );
+
+                // 3. Construir contexto a partir dos resultados
+                var context = BuildContextFromResults(searchResults);
+
+                // 4. Criar prompt com contexto
+                var prompt = BuildRagPrompt(userMessage, context);
+
+                // 5. Gerar resposta usando LLM
+                var response = await _chatService.GetChatMessageContentAsync(prompt);
+
+                _logger.LogDebug("Resposta RAG gerada com {ResultCount} documentos do Qdrant",
+                    searchResults.Count);
+
+                return response.Content ?? "Desculpe, não foi possível gerar uma resposta.";
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao processar consulta RAG com Qdrant");
+                return "Ocorreu um erro ao processar sua consulta. Tente novamente.";
+            }
+        }
+
+        public async Task<string> GetResponseWithHistory(
+            UserData userData,
+            string projectId,
+            string sessionId,
+            string userMessage,
+            List<string> conversationHistory)
+        {
+            try
+            {
+                // Combina histórico com mensagem atual para melhor contexto
+                var enhancedMessage = BuildEnhancedMessageWithHistory(userMessage, conversationHistory);
+
+                return await GetResponse(userData, projectId, sessionId, enhancedMessage);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao processar consulta RAG com histórico");
+                return "Ocorreu um erro ao processar sua consulta. Tente novamente.";
+            }
+        }
+
+        // ========================================
+        // MÉTODOS AUXILIARES PRIVADOS
+        // ========================================
+
+        private string BuildContextFromResults(List<VectorSearchResult> results)
+        {
+            if (!results.Any())
+            {
+                return "Nenhum documento relevante encontrado.";
+            }
+
+            var contextBuilder = new System.Text.StringBuilder();
+            contextBuilder.AppendLine("=== CONTEXTO DOS DOCUMENTOS ===");
+
+            foreach (var result in results.Take(5)) // Limita a 5 documentos
+            {
+                contextBuilder.AppendLine($"\n--- Documento: {result.Title} (Relevância: {result.GetScorePercentage()}) ---");
+                contextBuilder.AppendLine(result.Content);
+                contextBuilder.AppendLine();
+            }
+
+            return contextBuilder.ToString();
+        }
+
+        private string BuildRagPrompt(string userQuestion, string context)
+        {
+            return $@"
+                Você é um assistente especializado que responde perguntas baseado nos documentos fornecidos.
+
+                CONTEXTO DOS DOCUMENTOS:
+                {context}
+
+                PERGUNTA DO USUÁRIO:
+                {userQuestion}
+
+                INSTRUÇÕES:
+                - Responda baseado APENAS nas informações dos documentos fornecidos
+                - Se a informação não estiver nos documentos, diga que não encontrou a informação
+                - Seja preciso e cite trechos relevantes quando possível
+                - Mantenha um tom profissional e prestativo
+                - Se houver múltiplas informações relevantes, organize-as de forma clara
+
+                RESPOSTA:
+                ";
+        }
+
+        private string BuildEnhancedMessageWithHistory(string currentMessage, List<string> history)
+        {
+            if (!history.Any())
+                return currentMessage;
+
+            var enhancedMessage = new System.Text.StringBuilder();
+
+            enhancedMessage.AppendLine("HISTÓRICO DA CONVERSA:");
+            foreach (var message in history.TakeLast(3)) // Últimas 3 mensagens para contexto
+            {
+                enhancedMessage.AppendLine($"- {message}");
+            }
+
+            enhancedMessage.AppendLine($"\nPERGUNTA ATUAL: {currentMessage}");
+
+            return enhancedMessage.ToString();
+        }
+
+        // ========================================
+        // MÉTODOS DE ESTATÍSTICAS
+        // ========================================
+
+        public async Task<Dictionary<string, object>> GetProviderStatsAsync()
+        {
+            try
+            {
+                var vectorStats = await _vectorSearchService.GetStatsAsync();
+
+                return new Dictionary<string, object>(vectorStats)
+                {
+                    ["response_service_provider"] = "Qdrant",
+                    ["supports_history"] = true,
+                    ["supports_dynamic_threshold"] = true,
+                    ["last_check"] = DateTime.UtcNow
+                };
+            }
+            catch (Exception ex)
+            {
+                return new Dictionary<string, object>
+                {
+                    ["response_service_provider"] = "Qdrant",
+                    ["health"] = "error",
+                    ["error"] = ex.Message,
+                    ["last_check"] = DateTime.UtcNow
+                };
+            }
+        }
+
+        public async Task<bool> IsHealthyAsync()
+        {
+            try
+            {
+                return await _vectorSearchService.IsHealthyAsync();
+            }
+            catch
+            {
+                return false;
+            }
+        }
+
+        public Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        {
+            return this.GetResponse(userData, projectId, sessionId, question, "pt");
+        }
+    }
+}
+
+#pragma warning restore SKEXP0001

Services/ResponseService/ResponseCompanyService.cs

@@ -1,10 +1,13 @@
 
 using ChatApi;
 using ChatApi.Models;
+using ChatRAG.Contracts.VectorSearch;
 using ChatRAG.Data;
 using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
 using Microsoft.SemanticKernel;
 using Microsoft.SemanticKernel.ChatCompletion;
+using Microsoft.SemanticKernel.Connectors.OpenAI;
 using Microsoft.SemanticKernel.Embeddings;
 
 #pragma warning disable SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
@@ -17,16 +20,19 @@ namespace ChatRAG.Services.ResponseService
         private readonly Kernel _kernel;
         private readonly TextFilter _textFilter;
         private readonly TextDataRepository _textDataRepository;
-        private readonly ProjectDataRepository _projectDataRepository;
+        private readonly IProjectDataRepository _projectDataRepository;
         private readonly IChatCompletionService _chatCompletionService;
+        private readonly IVectorSearchService _vectorSearchService;
 
         public ResponseRAGService(
             ChatHistoryService chatHistoryService,
             Kernel kernel,
             TextFilter textFilter,
             TextDataRepository textDataRepository,
-            ProjectDataRepository projectDataRepository,
-            IChatCompletionService chatCompletionService)
+            IProjectDataRepository projectDataRepository,
+            IChatCompletionService chatCompletionService,
+            IVectorSearchService vectorSearchService, 
+            ITextDataService textDataService)
         {
             this._chatHistoryService = chatHistoryService;
             this._kernel = kernel;
@@ -34,27 +40,71 @@ namespace ChatRAG.Services.ResponseService
             this._textDataRepository = textDataRepository;
             this._projectDataRepository = projectDataRepository;
             this._chatCompletionService = chatCompletionService;
+            this._vectorSearchService = vectorSearchService;
         }
 
-        public async Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        public async Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question, string language = "pt")
         {
             var stopWatch = new System.Diagnostics.Stopwatch();
             stopWatch.Start();
 
-            //var resposta = await BuscarTextoRelacionado(question);
-            //var resposta = await BuscarTopTextosRelacionados(question, projectId);
-            var resposta = await BuscarTopTextosRelacionadosDinamico(question, projectId);
+            var searchStrategy = await ClassificarEstrategiaDeBusca(question, language);
 
-            var projectData = (await _projectDataRepository.GetAsync()).FirstOrDefault();
+            string resposta;
+            switch (searchStrategy)
+            {
+                case SearchStrategy.TodosProjeto:
+                    resposta = await BuscarTodosRequisitosDoProjeto(question, projectId);
+                    break;
+                case SearchStrategy.SimilaridadeComFiltro:
+                    resposta = await BuscarTopTextosRelacionadosComInterface(question, projectId);
+                    break;
+                case SearchStrategy.SimilaridadeGlobal:
+                    resposta = await BuscarTopTextosRelacionados(question, projectId);
+                    break;
+                default:
+                    resposta = await BuscarTopTextosRelacionadosComInterface(question, projectId);
+                    break;
+            }
+
+            var projectData = await _projectDataRepository.GetAsync(projectId);
 
             var project = $"Nome: {projectData.Nome} \n\n Descrição:{projectData.Descricao}";
 
-            question = $"Para responder à solicitação/pergunta: \"{question }\" por favor, considere o projeto: \"{project}\" e os requisitos: \"{resposta}\"";
+            //question = $"Para responder à solicitação/pergunta: \"{question}\" por favor, considere o projeto: \"{project}\" e os requisitos: \"{resposta}\"";
+            // Base prompt template
+            string basePrompt = @"You are a QA professional. Generate ONLY what the user requests.
+            Project Context: {0}
+            Requirements: {1}
+            User Request: ""{2}""
+
+            Focus exclusively on the user's request. Do not add summaries, explanations, or additional content unless specifically asked.";
+
+            if (language == "pt")
+            {
+                basePrompt = @"Você é um profissional de QA. Gere APENAS o que o usuário solicitar.
+                Contexto do Projeto: {0}
+                Requisitos: {1}
+                Solicitação do Usuário: ""{2}""
+                
+                Foque exclusivamente na solicitação do usuário. Não adicione resumos, explicações ou conteúdo adicional, a menos que especificamente solicitado.";
+            }
+            // Usage
+            question = string.Format(basePrompt, project, resposta, question);
+            
             ChatHistory history = _chatHistoryService.GetSumarizer(sessionId);
 
             history.AddUserMessage(question);
 
-            var response = await _chatCompletionService.GetChatMessageContentAsync(history);
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.8,
+                TopP = 1.0,
+                FrequencyPenalty = 0,
+                PresencePenalty = 0
+            };
+
+            var response = await _chatCompletionService.GetChatMessageContentAsync(history, executionSettings);
             history.AddMessage(response.Role, response.Content ?? "");
 
             _chatHistoryService.UpdateHistory(sessionId, history);
@@ -64,6 +114,68 @@ namespace ChatRAG.Services.ResponseService
 
         }
 
+        private async Task<SearchStrategy> ClassificarEstrategiaDeBusca(string question, string language)
+        {
+            string prompt = language == "pt" ?
+                @"TAREFA: Classificar estratégia de busca
+                    ENTRADA: ""{0}""
+
+                    REGRAS OBRIGATÓRIAS:
+                    - Se menciona ""projeto"" sem especificar módulos/aspectos → TODOS_PROJETO
+                    - Se menciona ""todo"", ""todos"", ""completo"", ""geral"" → TODOS_PROJETO  
+                    - Se menciona aspectos específicos como ""usuário"", ""login"", ""pagamento"" → SIMILARIDADE_FILTRADA
+                    - Se pergunta ""como funciona"" algo específico → SIMILARIDADE_GLOBAL
+
+                    EXEMPLOS OBRIGATÓRIOS:
+                    ""gere casos de teste para o projeto"" → TODOS_PROJETO
+                    ""gere resumo do projeto"" → TODOS_PROJETO
+                    ""gere lista de tarefas para este projeto"" → TODOS_PROJETO
+                    ""casos de teste para usuários"" → SIMILARIDADE_FILTRADA
+                    ""como funciona validação CPF"" → SIMILARIDADE_GLOBAL
+
+                    RESPOSTA OBRIGATÓRIA (copie exatamente): TODOS_PROJETO, SIMILARIDADE_FILTRADA ou SIMILARIDADE_GLOBAL" :
+
+                                    @"TASK: Classify search strategy
+                    INPUT: ""{0}""
+
+                    MANDATORY RULES:
+                    - If mentions ""project"" without specifying modules/aspects → ALL_PROJECT
+                    - If mentions ""all"", ""entire"", ""complete"", ""overview"" → ALL_PROJECT
+                    - If mentions specific aspects like ""user"", ""login"", ""payment"" → FILTERED_SIMILARITY
+                    - If asks ""how does"" something specific work → GLOBAL_SIMILARITY
+
+                    MANDATORY EXAMPLES:
+                    ""generate test cases for the project"" → ALL_PROJECT
+                    ""generate project summary"" → ALL_PROJECT
+                    ""generate task list for this project"" → ALL_PROJECT
+                    ""test cases for users"" → FILTERED_SIMILARITY
+                    ""how does CPF validation work"" → GLOBAL_SIMILARITY
+
+                    MANDATORY RESPONSE (copy exactly): ALL_PROJECT, FILTERED_SIMILARITY or GLOBAL_SIMILARITY";
+
+            var classificationPrompt = string.Format(prompt, question);
+
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.0,        // Mais determinístico
+                MaxTokens = 50,           // Resposta curta
+                TopP = 1.0,
+                FrequencyPenalty = 0,
+                PresencePenalty = 0
+            };
+
+            // Aqui você faria a chamada para o Ollama
+            var resp = await _chatCompletionService.GetChatMessageContentAsync(classificationPrompt, executionSettings);
+            //var classification = await _ollamaService.GetResponse(classificationPrompt);
+            var classification = resp.Content ?? "";
+
+            return classification.ToUpper().Contains("TODOS") || classification.ToUpper().Contains("ALL") ?
+                SearchStrategy.TodosProjeto :
+                classification.ToUpper().Contains("FILTRADA") || classification.ToUpper().Contains("FILTERED") ?
+                SearchStrategy.SimilaridadeComFiltro :
+                SearchStrategy.SimilaridadeGlobal;
+        }
+
         async Task<string> BuscarTextoRelacionado(string pergunta)
         {
             var embeddingService = _kernel.GetRequiredService<ITextEmbeddingGenerationService>();
@@ -88,7 +200,49 @@ namespace ChatRAG.Services.ResponseService
             return melhorTexto != null ? melhorTexto.Conteudo : "Não encontrei uma resposta adequada.";
         }
 
-        // Adicione esta nova rotina no seu ResponseRAGService
+        private async Task<string> BuscarTopTextosRelacionadosComInterface(string pergunta, string projectId)
+        {
+            var embeddingService = _kernel.GetRequiredService<ITextEmbeddingGenerationService>();
+            var embeddingPergunta = await embeddingService.GenerateEmbeddingAsync(
+                _textFilter.ToLowerAndWithoutAccents(pergunta));
+            var embeddingArray = embeddingPergunta.ToArray().Select(e => (double)e).ToArray();
+
+            var resultados = await _vectorSearchService.SearchSimilarDynamicAsync(embeddingArray, projectId, 0.5, 3);
+
+            if (!resultados.Any())
+                return "Não encontrei respostas adequadas para a pergunta fornecida.";
+
+            var cabecalho = $"Contexto encontrado para: '{pergunta}' ({resultados.Count} resultado(s)):\n\n";
+
+            var resultadosFormatados = resultados
+                .Select((item, index) =>
+                    $"=== CONTEXTO {index + 1} ===\n" +
+                    $"Relevância: {item.Score:P1}\n" +
+                    $"Conteúdo:\n{item.Content}")
+                .ToList();
+
+            return cabecalho + string.Join("\n\n", resultadosFormatados);
+        }
+
+        private async Task<string> BuscarTodosRequisitosDoProjeto(string pergunta, string projectId)
+        {
+            var resultados = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+
+            if (!resultados.Any())
+                return "Não encontrei respostas adequadas para a pergunta fornecida.";
+
+            var cabecalho = $"Contexto encontrado para: '{pergunta}' ({resultados.Count} resultado(s)):\n\n";
+
+            var resultadosFormatados = resultados
+                .Select((item, index) =>
+                    $"=== CONTEXTO {index + 1} ===\n" +
+                    $"Relevância: {item.Score:P1}\n" +
+                    $"Conteúdo:\n{item.Content}")
+                .ToList();
+
+            return cabecalho + string.Join("\n\n", resultadosFormatados);
+        }
+
 
         async Task<string> BuscarTopTextosRelacionadosDinamico(string pergunta, string projectId, int size = 3)
         {
@@ -221,6 +375,18 @@ namespace ChatRAG.Services.ResponseService
             }
             return dotProduct / (Math.Sqrt(normA) * Math.Sqrt(normB));
         }
+
+        public Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        {
+            return this.GetResponse(userData, projectId, sessionId, question, "pt");
+        }
+    }
+
+    public enum SearchStrategy
+    {
+        TodosProjeto,
+        SimilaridadeComFiltro,
+        SimilaridadeGlobal
     }
 }
 

Services/ResponseService/dxsmsw5a.kio~

@@ -0,0 +1,572 @@
+using ChatApi;
+using ChatApi.Models;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.ChatCompletion;
+using Microsoft.SemanticKernel.Connectors.OpenAI;
+using Microsoft.SemanticKernel.Embeddings;
+using System.Text.Json;
+
+#pragma warning disable SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+namespace ChatRAG.Services.ResponseService
+{
+    public class HierarchicalRAGService : IResponseService
+    {
+        private readonly ChatHistoryService _chatHistoryService;
+        private readonly Kernel _kernel;
+        private readonly TextFilter _textFilter;
+        private readonly IProjectDataRepository _projectDataRepository;
+        private readonly IChatCompletionService _chatCompletionService;
+        private readonly IVectorSearchService _vectorSearchService;
+        private readonly ILogger<HierarchicalRAGService> _logger;
+
+        public HierarchicalRAGService(
+            ChatHistoryService chatHistoryService,
+            Kernel kernel,
+            TextFilter textFilter,
+            IProjectDataRepository projectDataRepository,
+            IChatCompletionService chatCompletionService,
+            IVectorSearchService vectorSearchService,
+            ILogger<HierarchicalRAGService> logger)
+        {
+            _chatHistoryService = chatHistoryService;
+            _kernel = kernel;
+            _textFilter = textFilter;
+            _projectDataRepository = projectDataRepository;
+            _chatCompletionService = chatCompletionService;
+            _vectorSearchService = vectorSearchService;
+            _logger = logger;
+        }
+
+        public async Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question, string language = "pt")
+        {
+            var stopWatch = new System.Diagnostics.Stopwatch();
+            stopWatch.Start();
+
+            try
+            {
+                // 1. Análise da query para determinar estratégia
+                var queryAnalysis = await AnalyzeQuery(question, language);
+                _logger.LogInformation("Query Analysis: {Strategy}, Complexity: {Complexity}",
+                    queryAnalysis.Strategy, queryAnalysis.Complexity);
+
+                // 2. Execução hierárquica baseada na análise
+                var context = await ExecuteHierarchicalSearch(question, projectId, queryAnalysis);
+
+                // 3. Geração da resposta final
+                var response = await GenerateResponse(question, projectId, context, sessionId, language);
+
+                stopWatch.Stop();
+                return $"{response}\n\nTempo: {stopWatch.ElapsedMilliseconds / 1000}s\nEtapas: {context.Steps.Count}";
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro no RAG Hierárquico");
+                stopWatch.Stop();
+                return $"Erro: {ex.Message}\nTempo: {stopWatch.ElapsedMilliseconds / 1000}s";
+            }
+        }
+
+        private async Task<QueryAnalysis> AnalyzeQuery(string question, string language)
+        {
+            var analysisPrompt = language == "pt" ?
+                @"Analise esta pergunta e classifique com precisão:
+        PERGUNTA: ""{0}""
+        
+        Responda APENAS no formato JSON:
+        {{
+            ""strategy"": ""overview|specific|detailed|out_of_scope"",
+            ""complexity"": ""simple|medium|complex"",
+            ""scope"": ""global|filtered|targeted"",
+            ""concepts"": [""conceito1"", ""conceito2""],
+            ""needs_hierarchy"": true|false,
+        }}
+        
+        DEFINIÇÕES PRECISAS:
+        
+        STRATEGY:
+        - overview: Pergunta sobre o PROJETO COMO UM TODO. Palavras-chave: ""projeto"", ""sistema"", ""aplicação"", ""este projeto"", ""todo o"", ""geral"", ""inteiro"". NÃO menciona módulos, funcionalidades ou tecnologias específicas.
+        - out_of_scope: Pergunta/frase sem sentido relacionada à projetos. Saudações, cumprimentos, perguntas sem sentido, etc. Palavras-chave: ""oi"", ""olá"", ""bom dia"", ""boa tarde"", ""quem"", ""quando"", ""etc"". NÃO menciona projetos e contém apenas uma saudação ou o usuário se apresentando, sem falar mais nada além disso.
+        - specific: Pergunta sobre MÓDULO/FUNCIONALIDADE ESPECÍFICA. Menciona: nome de classe, controller, entidade, CRUD específico, funcionalidade particular, tecnologia específica.
+        - detailed: Pergunta técnica específica que precisa de CONTEXTO PROFUNDO e detalhes de implementação.
+        - out_of_scope: Suadação, pergunta sem relação com os textos ou fora de contexto
+        
+        SCOPE:
+        - global: Busca informações de TODO o projeto (usar com overview ou com out_of_scope)
+        - filtered: Busca com filtros específicos (usar com specific/detailed)
+        - targeted: Busca muito específica e direcionada
+        
+        EXEMPLOS:
+        - ""Gere casos de teste para este projeto"" → overview/global
+        - ""Gere casos de teste do projeto"" → overview/global  
+        - ""Gere casos de teste para o CRUD de usuário"" → specific/filtered
+        - ""Como implementar autenticação JWT neste controller"" → detailed/targeted
+        - ""Documente este sistema"" → overview/global
+        - ""Oi!"" → out_of_scope/global
+        - ""Boa tarde!"" → out_of_scope/global
+        - ""Meu nome é [nome de usuario]"" → out_of_scope/global
+        - ""Faça uma conta"" → out_of_scope/global
+        - ""Me passe a receita de bolo?"" → out_of_scope/global
+        - ""Explique a classe UserService"" → specific/filtered" :
+
+                @"Analyze this question and classify precisely:
+        QUESTION: ""{0}""
+        
+        Answer ONLY in JSON format:
+        {{
+            ""strategy"": ""overview|specific|detailed|out_of_scope"",
+            ""complexity"": ""simple|medium|complex"",
+            ""scope"": ""global|filtered|targeted"",
+            ""concepts"": [""concept1"", ""concept2""],
+            ""needs_hierarchy"": true|false
+        }}
+        
+        PRECISE DEFINITIONS:
+        
+        STRATEGY:
+        - overview: Question about the PROJECT AS A WHOLE. Keywords: ""project"", ""system"", ""application"", ""this project"", ""entire"", ""general"", ""whole"". Does NOT mention specific modules, functionalities or technologies.
+        - out_of_scope: Meaningless question/phrase related to projects. Greetings, salutations, meaningless questions, etc. Keywords: ""hi"", ""hello"", ""good morning"", ""good afternoon"", ""who"", ""when"", ""etc"". Does NOT mention projects and contains only a greeting or the user introducing themselves, without saying anything else.
+        - specific: Question about SPECIFIC MODULE/FUNCTIONALITY. Mentions: class name, controller, entity, specific CRUD, particular functionality, specific technology.
+        - detailed: Technical specific question needing DEEP CONTEXT and implementation details.
+        
+        SCOPE:
+        - global: Search information from ENTIRE project (use with overview or out_of_scope)
+        - filtered: Search with specific filters (use with specific/detailed)
+        - targeted: Very specific and directed search
+        
+        EXAMPLES:
+        - ""Generate test cases for this project"" → overview/global
+        - ""Generate test cases for user CRUD"" → specific/filtered
+        - ""How to implement JWT authentication in this controller"" → detailed/targeted
+        - ""Document this system"" → overview/global
+        - ""Hi!"" → out_of_scope/global
+        - ""Good afternoon!"" → out_of_scope/global
+        - ""My name is [nome de usuario]"" → out_of_scope/global
+        - ""Do an operation math for me"" → out_of_scope/global
+        - ""Give me the recipe for a cake?"" → out_of_scope/global
+        - ""Explain the UserService class"" → specific/filtered";
+
+            var prompt = string.Format(analysisPrompt, question);
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.1,
+                MaxTokens = 300 // Aumentei um pouco para acomodar o prompt maior
+            };
+            var response = await _chatCompletionService.GetChatMessageContentAsync(prompt, executionSettings);
+
+            try
+            {
+                var jsonResponse = response.Content?.Trim() ?? "{}";
+                // Extrair JSON se vier com texto extra
+                var startIndex = jsonResponse.IndexOf('{');
+                var endIndex = jsonResponse.LastIndexOf('}');
+                if (startIndex >= 0 && endIndex >= startIndex)
+                {
+                    jsonResponse = jsonResponse.Substring(startIndex, endIndex - startIndex + 1);
+                }
+
+                var options = new JsonSerializerOptions
+                {
+                    PropertyNameCaseInsensitive = true,
+                    PropertyNamingPolicy = JsonNamingPolicy.CamelCase
+                };
+
+                var analysis = System.Text.Json.JsonSerializer.Deserialize<QueryAnalysis>(jsonResponse, options);
+
+                // Log para debug - remover em produção
+                _logger.LogInformation($"Query: '{question}' → Strategy: {analysis?.Strategy}, Scope: {analysis?.Scope}");
+
+                return analysis ?? new QueryAnalysis { Strategy = "specific", Complexity = "medium" };
+            }
+            catch (Exception ex)
+            {
+                _logger.LogWarning(ex, "Erro ao parsear análise da query, usando padrão");
+                return new QueryAnalysis { Strategy = "specific", Complexity = "medium" };
+            }
+        }
+
+        private async Task<HierarchicalContext> ExecuteHierarchicalSearch(string question, string projectId, QueryAnalysis analysis)
+        {
+            var context = new HierarchicalContext();
+            var embeddingService = _kernel.GetRequiredService<ITextEmbeddingGenerationService>();
+
+            switch (analysis.Strategy)
+            {
+                case "out_of_scope":
+                    await ExecuteOutOfContextStrategy(context, question, projectId, embeddingService);
+                    break;
+                case "overview":
+                    await ExecuteOverviewStrategy(context, question, projectId, embeddingService);
+                    break;
+
+                case "detailed":
+                    await ExecuteDetailedStrategy(context, question, projectId, embeddingService, analysis);
+                    break;
+
+                default: // specific
+                    await ExecuteSpecificStrategy(context, question, projectId, embeddingService);
+                    break;
+            }
+
+            return context;
+        }
+
+        private async Task ExecuteOutOfContextStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            context.AddStep("Buscando o projeto");
+            var project = _projectDataRepository.GetAsync(projectId);
+
+            context.CombinedContext = string.Join("\n\n", project);
+        }
+
+
+
+        private async Task ExecuteOverviewStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            // Etapa 1: Buscar TODOS os documentos do projeto
+            context.AddStep("Buscando todos os documentos do projeto");
+            var allProjectDocs = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+
+            // Etapa 2: Categorizar documentos por tipo/importância
+            context.AddStep("Categorizando e resumindo contexto do projeto");
+
+            // Etapa 2: Categorizar documentos por tipo baseado nos seus dados reais
+            context.AddStep("Categorizando e resumindo contexto do projeto");
+
+            var requirementsDocs = allProjectDocs.Where(d =>
+                d.Title.ToLower().StartsWith("requisito") ||
+                d.Title.ToLower().Contains("requisito") ||
+                d.Content.ToLower().Contains("requisito") ||
+                d.Content.ToLower().Contains("funcionalidade") ||
+                d.Content.ToLower().Contains("aplicação deve") ||
+                d.Content.ToLower().Contains("sistema deve")).ToList();
+
+            var architectureDocs = allProjectDocs.Where(d =>
+                d.Title.ToLower().Contains("arquitetura") ||
+                d.Title.ToLower().Contains("estrutura") ||
+                d.Title.ToLower().Contains("documentação") ||
+                d.Title.ToLower().Contains("readme") ||
+                d.Content.ToLower().Contains("arquitetura") ||
+                d.Content.ToLower().Contains("estrutura") ||
+                d.Content.ToLower().Contains("tecnologia")).ToList();
+
+            // Documentos que não são requisitos nem arquitetura (códigos, outros docs)
+            var otherDocs = allProjectDocs
+                .Except(requirementsDocs)
+                .Except(architectureDocs)
+                .ToList();
+
+            // Etapa 3: Resumir cada categoria se tiver muitos documentos
+            var requirementsSummary = await SummarizeDocuments(requirementsDocs, "requisitos e funcionalidades do projeto");
+            var architectureSummary = await SummarizeDocuments(architectureDocs, "arquitetura e documentação técnica");
+            var otherSummary = await SummarizeDocuments(otherDocs, "outros documentos do projeto");
+
+            // Etapa 4: Busca específica para a pergunta (mantém precisão)
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+            context.AddStep("Identificando documentos específicos para a pergunta");
+            var relevantDocs = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.3, 8);
+
+            // Etapa 5: Combinar resumos + documentos específicos
+            var contextParts = new List<string>();
+
+            if (!string.IsNullOrEmpty(requirementsSummary))
+                contextParts.Add($"RESUMO DOS REQUISITOS E FUNCIONALIDADES:\n{requirementsSummary}");
+
+            if (!string.IsNullOrEmpty(architectureSummary))
+                contextParts.Add($"RESUMO DA ARQUITETURA E DOCUMENTAÇÃO:\n{architectureSummary}");
+
+            if (!string.IsNullOrEmpty(otherSummary))
+                contextParts.Add($"OUTROS DOCUMENTOS DO PROJETO:\n{otherSummary}");
+
+            contextParts.Add($"DOCUMENTOS MAIS RELEVANTES PARA A PERGUNTA:\n{FormatResults(relevantDocs)}");
+
+            context.CombinedContext = string.Join("\n\n", contextParts);
+        }
+
+        private async Task<string> SummarizeDocuments(List<VectorSearchResult> documents, string category)
+        {
+            if (!documents.Any()) return string.Empty;
+
+            // Se poucos documentos, usar todos sem resumir
+            if (documents.Count <= 3)
+            {
+                return FormatResults(documents);
+            }
+
+            // Se muitos documentos, resumir em chunks
+            var chunks = documents.Chunk(5).ToList(); // Grupos de 5 documentos
+            var tasks = new List<Task<string>>();
+
+            // Semáforo para controlar concorrência (máximo 3 chamadas simultâneas)
+            var semaphore = new SemaphoreSlim(3, 3);
+
+            foreach (var chunk in chunks)
+            {
+                var chunkContent = FormatResults(chunk);
+
+                tasks.Add(Task.Run(async () =>
+                {
+                    await semaphore.WaitAsync();
+                    try
+                    {
+                        var summaryPrompt = $@"Resuma os pontos principais destes documentos sobre {category}:
+
+                            {chunkContent}
+
+                            Responda apenas com uma lista concisa dos pontos mais importantes:";
+
+                        var response = await _chatCompletionService.GetChatMessageContentAsync(
+                            summaryPrompt,
+                            new OpenAIPromptExecutionSettings
+                            {
+                                Temperature = 0.1,
+                                MaxTokens = 300
+                            });
+
+                        return response.Content ?? string.Empty;
+                    }
+                    catch (Exception ex)
+                    {
+                        _logger.LogWarning(ex, $"Erro ao resumir chunk de {category}, usando conteúdo original");
+                        return chunkContent;
+                    }
+                    finally
+                    {
+                        semaphore.Release();
+                    }
+                }));
+            }
+
+            // Aguardar todas as tasks de resumo
+            var summaries = await Task.WhenAll(tasks);
+            var validSummaries = summaries.Where(s => !string.IsNullOrEmpty(s)).ToList();
+
+            // Se tiver múltiplos resumos, consolidar
+            if (validSummaries.Count > 1)
+            {
+                var consolidationPrompt = $@"Consolide estes resumos sobre {category} em um resumo final:
+
+                    {string.Join("\n\n", validSummaries)}
+
+                    Responda com os pontos mais importantes organizados:";
+
+                try
+                {
+                    var finalResponse = await _chatCompletionService.GetChatMessageContentAsync(
+                        consolidationPrompt,
+                        new OpenAIPromptExecutionSettings
+                        {
+                            Temperature = 0.1,
+                            MaxTokens = 400
+                        });
+
+                    return finalResponse.Content ?? string.Empty;
+                }
+                catch
+                {
+                    return string.Join("\n\n", validSummaries);
+                }
+            }
+
+            return validSummaries.FirstOrDefault() ?? string.Empty;
+        }
+
+        private async Task ExecuteSpecificStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            // Etapa 1: Busca inicial por similaridade
+            context.AddStep("Busca inicial por similaridade");
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+            var initialResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.4, 3);
+
+            if (initialResults.Any())
+            {
+                context.AddStep("Expandindo contexto com documentos relacionados");
+
+                // Etapa 2: Expandir com contexto relacionado
+                var expandedContext = await ExpandContext(initialResults, projectId, embeddingService);
+                context.CombinedContext = $"CONTEXTO PRINCIPAL:\n{FormatResults(initialResults)}\n\nCONTEXTO EXPANDIDO:\n{FormatResults(expandedContext)}";
+            }
+            else
+            {
+                context.AddStep("Fallback para busca ampla");
+                var fallbackResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.2, 5);
+                context.CombinedContext = FormatResults(fallbackResults);
+            }
+        }
+
+        private async Task ExecuteDetailedStrategy(HierarchicalContext context, string question, string projectId, ITextEmbeddingGenerationService embeddingService, QueryAnalysis analysis)
+        {
+            var questionEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(question));
+            var embeddingArray = questionEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+            // Etapa 1: Busca conceitual baseada nos conceitos identificados
+            context.AddStep("Busca conceitual inicial");
+            var conceptualResults = new List<VectorSearchResult>();
+
+            if (analysis.Concepts?.Any() == true)
+            {
+                foreach (var concept in analysis.Concepts)
+                {
+                    var conceptEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(concept));
+                    var conceptArray = conceptEmbedding.ToArray().Select(e => (double)e).ToArray();
+                    var conceptResults = await _vectorSearchService.SearchSimilarAsync(conceptArray, projectId, 0.3, 2);
+                    conceptualResults.AddRange(conceptResults);
+                }
+            }
+
+            // Etapa 2: Busca direta pela pergunta
+            context.AddStep("Busca direta pela pergunta");
+            var directResults = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.3, 3);
+
+            // Etapa 3: Síntese intermediária para identificar lacunas
+            context.AddStep("Identificando lacunas de conhecimento");
+            var intermediateContext = FormatResults(conceptualResults.Concat(directResults).DistinctBy(r => r.Id));
+            var gaps = await IdentifyKnowledgeGaps(question, intermediateContext);
+
+            // Etapa 4: Busca complementar baseada nas lacunas
+            if (!string.IsNullOrEmpty(gaps))
+            {
+                context.AddStep("Preenchendo lacunas de conhecimento");
+                var gapEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(gaps));
+                var gapArray = gapEmbedding.ToArray().Select(e => (double)e).ToArray();
+                var gapResults = await _vectorSearchService.SearchSimilarAsync(gapArray, projectId, 0.25, 2);
+
+                context.CombinedContext = $"CONTEXTO CONCEITUAL:\n{FormatResults(conceptualResults)}\n\nCONTEXTO DIRETO:\n{FormatResults(directResults)}\n\nCONTEXTO COMPLEMENTAR:\n{FormatResults(gapResults)}";
+            }
+            else
+            {
+                context.CombinedContext = $"CONTEXTO CONCEITUAL:\n{FormatResults(conceptualResults)}\n\nCONTEXTO DIRETO:\n{FormatResults(directResults)}";
+            }
+        }
+
+        private async Task<List<VectorSearchResult>> ExpandContext(List<VectorSearchResult> initialResults, string projectId, ITextEmbeddingGenerationService embeddingService)
+        {
+            var expandedResults = new List<VectorSearchResult>();
+
+            // Para cada resultado inicial, buscar documentos relacionados
+            foreach (var result in initialResults.Take(2)) // Limitar para evitar explosão de contexto
+            {
+                var resultEmbedding = await embeddingService.GenerateEmbeddingAsync(_textFilter.ToLowerAndWithoutAccents(result.Content));
+                var embeddingArray = resultEmbedding.ToArray().Select(e => (double)e).ToArray();
+
+                var relatedDocs = await _vectorSearchService.SearchSimilarAsync(embeddingArray, projectId, 0.4, 2);
+                expandedResults.AddRange(relatedDocs.Where(r => !initialResults.Any(ir => ir.Id == r.Id)));
+            }
+
+            return expandedResults.DistinctBy(r => r.Id).ToList();
+        }
+
+        private async Task<string> IdentifyKnowledgeGaps(string question, string currentContext)
+        {
+            var gapPrompt = @"Baseado na pergunta e contexto atual, identifique que informações ainda faltam para uma resposta completa.
+            
+            PERGUNTA: {0}
+            CONTEXTO ATUAL: {1}
+            
+            Responda APENAS com palavras-chave dos conceitos/informações que ainda faltam, separados por vírgula.
+            Se o contexto for suficiente, responda 'SUFICIENTE'.";
+
+            var prompt = string.Format(gapPrompt, question, currentContext.Substring(0, Math.Min(1000, currentContext.Length)));
+
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.2,
+                MaxTokens = 100
+            };
+
+            var response = await _chatCompletionService.GetChatMessageContentAsync(prompt, executionSettings);
+            var gaps = response.Content?.Trim() ?? "";
+
+            return gaps.Equals("SUFICIENTE", StringComparison.OrdinalIgnoreCase) ? "" : gaps;
+        }
+
+        private async Task<string> GenerateResponse(string question, string projectId, HierarchicalContext context, string sessionId, string language)
+        {
+            var projectData = await _projectDataRepository.GetAsync(projectId);
+            var project = $"Nome: {projectData.Nome} \n\n Descrição:{projectData.Descricao}";
+
+            var prompt = language == "pt" ?
+                @"Você é um especialista em análise de software e QA, mas também atende ao chat.
+                
+                PROJETO: {0}
+                PERGUNTA: ""{1}""
+                CONTEXTO HIERÁRQUICO: {2}
+                ETAPAS EXECUTADAS: {3}
+                
+                Responda à pergunta de forma precisa e estruturada, aproveitando todo o contexto hierárquico coletado." :
+
+                @"You are a software analysis and QA expert.
+                
+                PROJECT: {0}
+                QUESTION: ""{1}""
+                HIERARCHICAL CONTEXT: {2}
+                EXECUTED STEPS: {3}
+                
+                Answer the question precisely and structured, leveraging all the hierarchical context collected.";
+
+            var finalPrompt = string.Format(prompt, project, question, context.CombinedContext,
+                string.Join(" → ", context.Steps));
+
+            var history = _chatHistoryService.GetSumarizer(sessionId);
+            history.AddUserMessage(finalPrompt);
+
+            var executionSettings = new OpenAIPromptExecutionSettings
+            {
+                Temperature = 0.7,
+                TopP = 1.0,
+                FrequencyPenalty = 0,
+                PresencePenalty = 0
+            };
+
+            var response = await _chatCompletionService.GetChatMessageContentAsync(history, executionSettings);
+            history.AddMessage(response.Role, response.Content ?? "");
+            _chatHistoryService.UpdateHistory(sessionId, history);
+
+            return response.Content ?? "";
+        }
+
+        private string FormatResults(IEnumerable<VectorSearchResult> results)
+        {
+            return string.Join("\n\n", results.Select((item, index) =>
+                $"=== DOCUMENTO {index + 1} ===\n" +
+                $"Relevância: {item.Score:P1}\n" +
+                $"Conteúdo: {item.Content}"));
+        }
+
+        public Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        {
+            return GetResponse(userData, projectId, sessionId, question, "pt");
+        }
+    }
+
+    // Classes de apoio para o RAG Hierárquico
+    public class QueryAnalysis
+    {
+        public string Strategy { get; set; } = "specific";
+        public string Complexity { get; set; } = "medium";
+        public string Scope { get; set; } = "filtered";
+        public string[] Concepts { get; set; } = Array.Empty<string>();
+        public bool Needs_Hierarchy { get; set; } = false;
+    }
+
+    public class HierarchicalContext
+    {
+        public List<string> Steps { get; set; } = new();
+        public string CombinedContext { get; set; } = "";
+        public Dictionary<string, object> Metadata { get; set; } = new();
+
+        public void AddStep(string step)
+        {
+            Steps.Add($"{DateTime.Now:HH:mm:ss} - {step}");
+        }
+    }
+
+}
+#pragma warning restore SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.

Services/SearchVectors/ChromaVectorSearchService.cs

@@ -0,0 +1,651 @@
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Models;
+using Microsoft.Extensions.Options;
+using System.Text;
+using System.Text.Json;
+using Microsoft.SemanticKernel.Embeddings;
+using ChatRAG.Settings.ChatRAG.Configuration;
+
+namespace ChatRAG.Services.SearchVectors
+{
+    public class ChromaVectorSearchService : IVectorSearchService
+    {
+        private readonly HttpClient _httpClient;
+        private readonly ILogger<ChromaVectorSearchService> _logger;
+        private readonly ChromaSettings _settings;
+        private readonly string _collectionName;
+
+        public ChromaVectorSearchService(
+            IOptions<VectorDatabaseSettings> settings,
+            ILogger<ChromaVectorSearchService> logger,
+            HttpClient httpClient)
+        {
+            _settings = settings.Value.Chroma ?? throw new ArgumentNullException("Chroma settings not configured");
+            _logger = logger;
+            _httpClient = httpClient;
+            _httpClient.BaseAddress = new Uri($"http://{_settings.Host}:{_settings.Port}");
+            _collectionName = _settings.CollectionName;
+
+            InitializeAsync().GetAwaiter().GetResult();
+        }
+
+        private async Task InitializeAsync()
+        {
+            try
+            {
+                // Verificar se a collection existe, se não, criar
+                var collections = await GetCollectionsAsync();
+                if (!collections.Contains(_collectionName))
+                {
+                    await CreateCollectionAsync();
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao inicializar Chroma");
+                throw;
+            }
+        }
+
+        // ========================================
+        // BUSCA VETORIAL
+        // ========================================
+
+        public async Task<List<VectorSearchResult>> SearchSimilarAsync(
+            double[] queryEmbedding,
+            string? projectId = null,
+            double threshold = 0.3,
+            int limit = 5,
+            Dictionary<string, object>? filters = null)
+        {
+            try
+            {
+                // Construir filtros WHERE
+                var whereClause = BuildWhereClause(projectId, filters);
+
+                var query = new
+                {
+                    query_embeddings = new[] { queryEmbedding },
+                    n_results = limit,
+                    where = whereClause,
+                    include = new[] { "documents", "metadatas", "distances" }
+                };
+
+                var json = JsonSerializer.Serialize(query);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v1/collections/{_collectionName}/query", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    var error = await response.Content.ReadAsStringAsync();
+                    _logger.LogError("Erro na busca Chroma: {Error}", error);
+                    return new List<VectorSearchResult>();
+                }
+
+                var result = await response.Content.ReadAsStringAsync();
+                var queryResult = JsonSerializer.Deserialize<ChromaQueryResult>(result);
+
+                return ParseQueryResults(queryResult, threshold);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar similares no Chroma");
+                return new List<VectorSearchResult>();
+            }
+        }
+
+        public async Task<List<VectorSearchResult>> SearchSimilarDynamicAsync(
+            double[] queryEmbedding,
+            string projectId,
+            double minThreshold = 0.5,
+            int limit = 5)
+        {
+            // Estratégia 1: Busca com threshold alto
+            var results = await SearchSimilarAsync(queryEmbedding, projectId, minThreshold, limit);
+
+            if (results.Count >= limit)
+            {
+                return results.Take(limit).ToList();
+            }
+
+            // Estratégia 2: Relaxar threshold se não conseguiu o suficiente
+            if (results.Count < limit && minThreshold > 0.35)
+            {
+                var mediumResults = await SearchSimilarAsync(queryEmbedding, projectId, 0.35, limit * 2);
+                if (mediumResults.Count >= limit)
+                {
+                    return mediumResults.Take(limit).ToList();
+                }
+                results = mediumResults;
+            }
+
+            // Estratégia 3: Threshold baixo como último recurso
+            if (results.Count < limit && minThreshold > 0.2)
+            {
+                var lowResults = await SearchSimilarAsync(queryEmbedding, projectId, 0.2, limit * 3);
+                results = lowResults;
+            }
+
+            return results.Take(limit).ToList();
+        }
+
+        // ========================================
+        // CRUD DE DOCUMENTOS
+        // ========================================
+
+        public async Task<string> AddDocumentAsync(
+            string title,
+            string content,
+            string projectId,
+            double[] embedding,
+            Dictionary<string, object>? metadata = null)
+        {
+            try
+            {
+                var documentId = Guid.NewGuid().ToString();
+
+                var combinedMetadata = new Dictionary<string, object>
+                {
+                    ["title"] = title,
+                    ["project_id"] = projectId,
+                    ["created_at"] = DateTime.UtcNow.ToString("O")
+                };
+
+                if (metadata != null)
+                {
+                    foreach (var kvp in metadata)
+                    {
+                        combinedMetadata[kvp.Key] = kvp.Value;
+                    }
+                }
+
+                var document = new
+                {
+                    ids = new[] { documentId },
+                    documents = new[] { content },
+                    metadatas = new[] { combinedMetadata },
+                    embeddings = new[] { embedding }
+                };
+
+                var json = JsonSerializer.Serialize(document);
+                var requestContent = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v1/collections/{_collectionName}/add", requestContent);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    var error = await response.Content.ReadAsStringAsync();
+                    throw new Exception($"Erro ao adicionar documento: {error}");
+                }
+
+                return documentId;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao adicionar documento no Chroma");
+                throw;
+            }
+        }
+
+        public async Task UpdateDocumentAsync(
+            string id,
+            string title,
+            string content,
+            string projectId,
+            double[] embedding,
+            Dictionary<string, object>? metadata = null)
+        {
+            try
+            {
+                // Chroma não tem update direto, então fazemos delete + add
+                await DeleteDocumentAsync(id);
+
+                var combinedMetadata = new Dictionary<string, object>
+                {
+                    ["title"] = title,
+                    ["project_id"] = projectId,
+                    ["updated_at"] = DateTime.UtcNow.ToString("O")
+                };
+
+                if (metadata != null)
+                {
+                    foreach (var kvp in metadata)
+                    {
+                        combinedMetadata[kvp.Key] = kvp.Value;
+                    }
+                }
+
+                var document = new
+                {
+                    ids = new[] { id },
+                    documents = new[] { content },
+                    metadatas = new[] { combinedMetadata },
+                    embeddings = new[] { embedding }
+                };
+
+                var json = JsonSerializer.Serialize(document);
+                var requestContent = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v1/collections/{_collectionName}/upsert", requestContent);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    var error = await response.Content.ReadAsStringAsync();
+                    throw new Exception($"Erro ao atualizar documento: {error}");
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar documento no Chroma");
+                throw;
+            }
+        }
+
+        public async Task DeleteDocumentAsync(string id)
+        {
+            try
+            {
+                var deleteRequest = new
+                {
+                    ids = new[] { id }
+                };
+
+                var json = JsonSerializer.Serialize(deleteRequest);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v1/collections/{_collectionName}/delete", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    var error = await response.Content.ReadAsStringAsync();
+                    _logger.LogWarning("Erro ao deletar documento {Id}: {Error}", id, error);
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao deletar documento {Id} no Chroma", id);
+                throw;
+            }
+        }
+
+        // ========================================
+        // CONSULTAS AUXILIARES
+        // ========================================
+
+        public async Task<bool> DocumentExistsAsync(string id)
+        {
+            try
+            {
+                var doc = await GetDocumentAsync(id);
+                return doc != null;
+            }
+            catch
+            {
+                return false;
+            }
+        }
+
+        public async Task<VectorSearchResult?> GetDocumentAsync(string id)
+        {
+            try
+            {
+                var query = new
+                {
+                    ids = new[] { id },
+                    include = new[] { "documents", "metadatas" }
+                };
+
+                var json = JsonSerializer.Serialize(query);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v1/collections/{_collectionName}/get", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    return null;
+                }
+
+                var result = await response.Content.ReadAsStringAsync();
+                var getResult = JsonSerializer.Deserialize<ChromaGetResult>(result);
+
+                if (getResult?.ids?.Length > 0)
+                {
+                    return new VectorSearchResult
+                    {
+                        Id = getResult.ids[0],
+                        Content = getResult.documents?[0] ?? "",
+                        Score = 1.0,
+                        Metadata = getResult.metadatas?[0]
+                    };
+                }
+
+                return null;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar documento {Id} no Chroma", id);
+                return null;
+            }
+        }
+
+        public async Task<List<VectorSearchResult>> GetDocumentsByProjectAsync(string projectId)
+        {
+            try
+            {
+                var query = new
+                {
+                    where = new { project_id = projectId },
+                    include = new[] { "documents", "metadatas" }
+                };
+
+                var json = JsonSerializer.Serialize(query);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v1/collections/{_collectionName}/get", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    var error = await response.Content.ReadAsStringAsync();
+                    _logger.LogError("Erro ao buscar documentos do projeto {ProjectId}: {Error}", projectId, error);
+                    return new List<VectorSearchResult>();
+                }
+
+                var result = await response.Content.ReadAsStringAsync();
+                var getResult = JsonSerializer.Deserialize<ChromaGetResult>(result);
+
+                var results = new List<VectorSearchResult>();
+
+                if (getResult?.documents?.Length > 0)
+                {
+                    for (int i = 0; i < getResult.documents.Length; i++)
+                    {
+                        results.Add(new VectorSearchResult
+                        {
+                            Id = getResult.ids[i],
+                            Content = getResult.documents[i],
+                            Score = 1.0, // Todos os documentos do projeto
+                            Metadata = getResult.metadatas?[i]
+                        });
+                    }
+                }
+
+                return results;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar documentos do projeto {ProjectId} no Chroma", projectId);
+                return new List<VectorSearchResult>();
+            }
+        }
+
+        public async Task<int> GetDocumentCountAsync(string? projectId = null)
+        {
+            try
+            {
+                var query = new
+                {
+                    where = projectId != null ? new { project_id = projectId } : null
+                };
+
+                var json = JsonSerializer.Serialize(query);
+                var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+                var response = await _httpClient.PostAsync($"/api/v1/collections/{_collectionName}/count", content);
+
+                if (!response.IsSuccessStatusCode)
+                {
+                    _logger.LogWarning("Erro ao contar documentos no Chroma");
+                    return 0;
+                }
+
+                var result = await response.Content.ReadAsStringAsync();
+                var countResult = JsonSerializer.Deserialize<ChromaCountResult>(result);
+                return countResult?.count ?? 0;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao contar documentos no Chroma");
+                return 0;
+            }
+        }
+
+        // ========================================
+        // HEALTH CHECK E MÉTRICAS
+        // ========================================
+
+        public async Task<bool> IsHealthyAsync()
+        {
+            try
+            {
+                var response = await _httpClient.GetAsync("/api/v1/heartbeat");
+                return response.IsSuccessStatusCode;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro no health check do Chroma");
+                return false;
+            }
+        }
+
+        public async Task<Dictionary<string, object>> GetStatsAsync()
+        {
+            try
+            {
+                var stats = new Dictionary<string, object>
+                {
+                    ["provider"] = "Chroma",
+                    ["collection"] = _collectionName,
+                    ["host"] = _settings.Host,
+                    ["port"] = _settings.Port
+                };
+
+                // Tentar obter informações da collection
+                var response = await _httpClient.GetAsync($"/api/v1/collections/{_collectionName}");
+                if (response.IsSuccessStatusCode)
+                {
+                    var content = await response.Content.ReadAsStringAsync();
+                    var collectionInfo = JsonSerializer.Deserialize<Dictionary<string, object>>(content);
+                    if (collectionInfo != null)
+                    {
+                        stats["collection_info"] = collectionInfo;
+                    }
+                }
+
+                // Contar documentos totais
+                stats["total_documents"] = await GetDocumentCountAsync();
+
+                return stats;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao obter stats do Chroma");
+                return new Dictionary<string, object>
+                {
+                    ["provider"] = "Chroma",
+                    ["error"] = ex.Message,
+                    ["status"] = "error"
+                };
+            }
+        }
+
+        // ========================================
+        // MÉTODOS AUXILIARES PRIVADOS
+        // ========================================
+
+        private async Task<string[]> GetCollectionsAsync()
+        {
+            try
+            {
+                var response = await _httpClient.GetAsync("/api/v1/collections");
+                if (!response.IsSuccessStatusCode)
+                {
+                    _logger.LogWarning("Erro ao obter collections: {StatusCode}", response.StatusCode);
+                    return Array.Empty<string>();
+                }
+
+                var content = await response.Content.ReadAsStringAsync();
+
+                // Tentar desserializar como array de strings (versão simples)
+                try
+                {
+                    var collections = JsonSerializer.Deserialize<string[]>(content);
+                    return collections ?? Array.Empty<string>();
+                }
+                catch
+                {
+                    // Tentar desserializar como array de objetos (versão mais nova)
+                    try
+                    {
+                        var collectionsObj = JsonSerializer.Deserialize<CollectionInfo[]>(content);
+                        return collectionsObj?.Select(c => c.name).ToArray() ?? Array.Empty<string>();
+                    }
+                    catch
+                    {
+                        _logger.LogWarning("Não foi possível parsear lista de collections");
+                        return Array.Empty<string>();
+                    }
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar collections");
+                return Array.Empty<string>();
+            }
+        }
+
+        // Classe auxiliar para desserialização
+        private class CollectionInfo
+        {
+            public string name { get; set; } = "";
+            public Dictionary<string, object>? metadata { get; set; }
+        }
+
+        private async Task CreateCollectionAsync()
+        {
+            var collection = new
+            {
+                name = _collectionName,
+                metadata = new
+                {
+                    description = "RAG Collection",
+                    created_at = DateTime.UtcNow.ToString("O")
+                }
+            };
+
+            var json = JsonSerializer.Serialize(collection);
+            var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+            // Tentar primeira abordagem (versão mais nova)
+            var response = await _httpClient.PostAsync("/api/v1/collections", content);
+
+            // Se falhar, tentar segunda abordagem (criar collection via get_or_create)
+            if (!response.IsSuccessStatusCode)
+            {
+                _logger.LogWarning("Método POST falhou, tentando abordagem alternativa");
+
+                // Criar usando get_or_create approach
+                var createPayload = new
+                {
+                    name = _collectionName,
+                    metadata = new
+                    {
+                        description = "RAG Collection",
+                        created_at = DateTime.UtcNow.ToString("O")
+                    },
+                    get_or_create = true
+                };
+
+                var createJson = JsonSerializer.Serialize(createPayload);
+                var createContent = new StringContent(createJson, Encoding.UTF8, "application/json");
+
+                var createResponse = await _httpClient.PostAsync("/api/v1/collections", createContent);
+
+                if (!createResponse.IsSuccessStatusCode)
+                {
+                    var error = await createResponse.Content.ReadAsStringAsync();
+                    _logger.LogError("Erro ao criar collection: {Error}", error);
+
+                    // Última tentativa: assumir que collection já existe
+                    _logger.LogWarning("Assumindo que collection {CollectionName} já existe", _collectionName);
+                    return;
+                }
+            }
+
+            _logger.LogInformation("Collection {CollectionName} criada/verificada com sucesso", _collectionName);
+        }
+
+        private object? BuildWhereClause(string? projectId, Dictionary<string, object>? filters)
+        {
+            var where = new Dictionary<string, object>();
+
+            if (!string.IsNullOrEmpty(projectId))
+            {
+                where["project_id"] = projectId;
+            }
+
+            if (filters != null)
+            {
+                foreach (var filter in filters)
+                {
+                    where[filter.Key] = filter.Value;
+                }
+            }
+
+            return where.Any() ? where : null;
+        }
+
+        private List<VectorSearchResult> ParseQueryResults(ChromaQueryResult? queryResult, double threshold)
+        {
+            var results = new List<VectorSearchResult>();
+
+            if (queryResult?.documents?.Length > 0 && queryResult.documents[0].Length > 0)
+            {
+                for (int i = 0; i < queryResult.documents[0].Length; i++)
+                {
+                    var distance = queryResult.distances?[0][i] ?? 1.0;
+
+                    // Chroma retorna distâncias, converter para similaridade (1 - distance)
+                    var similarity = 1.0 - distance;
+
+                    if (similarity >= threshold)
+                    {
+                        results.Add(new VectorSearchResult
+                        {
+                            Id = queryResult.ids[0][i],
+                            Content = queryResult.documents[0][i],
+                            Score = similarity,
+                            Metadata = queryResult.metadatas?[0][i]
+                        });
+                    }
+                }
+            }
+
+            return results.OrderByDescending(r => r.Score).ToList();
+        }
+    }
+
+    // ========================================
+    // DTOs PARA CHROMA API
+    // ========================================
+
+    public class ChromaQueryResult
+    {
+        public string[][] ids { get; set; } = Array.Empty<string[]>();
+        public string[][] documents { get; set; } = Array.Empty<string[]>();
+        public double[][]? distances { get; set; }
+        public Dictionary<string, object>[][]? metadatas { get; set; }
+    }
+
+    public class ChromaGetResult
+    {
+        public string[] ids { get; set; } = Array.Empty<string>();
+        public string[] documents { get; set; } = Array.Empty<string>();
+        public Dictionary<string, object>[]? metadatas { get; set; }
+    }
+
+    public class ChromaCountResult
+    {
+        public int count { get; set; }
+    }
+}

Services/SearchVectors/MongoVectorSearchService.cs

@@ -0,0 +1,228 @@
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Models;
+using Microsoft.Extensions.VectorData;
+using Microsoft.SemanticKernel.Embeddings;
+
+#pragma warning disable SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+namespace ChatRAG.Services.SearchVectors
+{
+    public class MongoVectorSearchService : IVectorSearchService
+    {
+        private readonly TextDataRepository _textDataRepository;
+        private readonly ITextEmbeddingGenerationService _embeddingService;
+
+        public MongoVectorSearchService(
+            TextDataRepository textDataRepository,
+            ITextEmbeddingGenerationService embeddingService)
+        {
+            _textDataRepository = textDataRepository;
+            _embeddingService = embeddingService;
+        }
+
+        // ... resto da implementação permanece igual ...
+        // (copiar do código anterior)
+
+        public async Task<List<VectorSearchResult>> SearchSimilarAsync(
+            double[] queryEmbedding,
+            string? projectId = null,
+            double threshold = 0.3,
+            int limit = 5,
+            Dictionary<string, object>? filters = null)
+        {
+            List<TextoComEmbedding> textos = null;
+            try
+            {
+                textos = string.IsNullOrEmpty(projectId)
+                    ? await _textDataRepository.GetAsync()
+                    : await _textDataRepository.GetByProjectIdAsync(projectId);
+            }
+            catch (Exception ex)
+            {
+                throw new Exception($"Erro ao buscar documentos: {ex.Message}");
+            }
+
+            var resultados = textos
+                .Select(texto => new VectorSearchResult
+                {
+                    Id = texto.Id,
+                    Title = texto.Titulo,
+                    Content = texto.Conteudo,
+                    ProjectId = texto.ProjetoId,
+                    Score = CalcularSimilaridadeCoseno(queryEmbedding, texto.Embedding),
+                    Embedding = texto.Embedding,
+                    Provider = "MongoDB",
+                    CreatedAt = DateTime.UtcNow,
+                    UpdatedAt = DateTime.UtcNow
+                })
+                .Where(r => r.Score >= threshold)
+                .OrderByDescending(r => r.Score)
+                .Take(limit)
+                .ToList();
+
+            return resultados;
+        }
+
+        public async Task<List<VectorSearchResult>> SearchSimilarDynamicAsync(
+            double[] queryEmbedding,
+            string projectId,
+            double minThreshold = 0.5,
+            int limit = 5)
+        {
+            var resultados = await SearchSimilarAsync(queryEmbedding, projectId, minThreshold, limit);
+
+            if (resultados.Count < 3)
+            {
+                resultados = await SearchSimilarAsync(queryEmbedding, projectId, minThreshold * 0.7, limit);
+            }
+
+            if (resultados.Count < 3)
+            {
+                resultados = await SearchSimilarAsync(queryEmbedding, projectId, 0.2, limit);
+            }
+
+            return resultados.Take(limit).ToList();
+        }
+
+        public async Task<string> AddDocumentAsync(
+            string title,
+            string content,
+            string projectId,
+            double[] embedding,
+            Dictionary<string, object>? metadata = null)
+        {
+            var documento = new TextoComEmbedding
+            {
+                Id = Guid.NewGuid().ToString(),
+                Titulo = title,
+                Conteudo = content,
+                ProjetoId = projectId,
+                Embedding = embedding
+            };
+
+            await _textDataRepository.CreateAsync(documento);
+            return documento.Id;
+        }
+
+        public async Task UpdateDocumentAsync(
+            string id,
+            string title,
+            string content,
+            string projectId,
+            double[] embedding,
+            Dictionary<string, object>? metadata = null)
+        {
+            var documento = new TextoComEmbedding
+            {
+                Id = id,
+                Titulo = title,
+                Conteudo = content,
+                ProjetoId = projectId,
+                Embedding = embedding
+            };
+
+            await _textDataRepository.UpdateAsync(id, documento);
+        }
+
+        public async Task DeleteDocumentAsync(string id)
+        {
+            await _textDataRepository.RemoveAsync(id);
+        }
+
+        public async Task<bool> DocumentExistsAsync(string id)
+        {
+            var doc = await _textDataRepository.GetAsync(id);
+            return doc != null;
+        }
+
+        public async Task<VectorSearchResult?> GetDocumentAsync(string id)
+        {
+            var doc = await _textDataRepository.GetAsync(id);
+            if (doc == null) return null;
+
+            return new VectorSearchResult
+            {
+                Id = doc.Id,
+                Title = doc.Titulo,
+                Content = doc.Conteudo,
+                ProjectId = doc.ProjetoId,
+                Score = 1.0,
+                Embedding = doc.Embedding,
+                Provider = "MongoDB",
+                CreatedAt = DateTime.UtcNow,
+                UpdatedAt = DateTime.UtcNow
+            };
+        }
+
+        public async Task<List<VectorSearchResult>> GetDocumentsByProjectAsync(string projectId)
+        {
+            var docs = await _textDataRepository.GetByProjectIdAsync(projectId);
+            return docs.Select(doc => new VectorSearchResult
+            {
+                Id = doc.Id,
+                Title = doc.Titulo,
+                Content = doc.Conteudo,
+                ProjectId = doc.ProjetoId,
+                Score = 1.0,
+                Embedding = doc.Embedding,
+                Provider = "MongoDB",
+                CreatedAt = DateTime.UtcNow,
+                UpdatedAt = DateTime.UtcNow
+            }).ToList();
+        }
+
+        public async Task<int> GetDocumentCountAsync(string? projectId = null)
+        {
+            if (string.IsNullOrEmpty(projectId))
+            {
+                var all = await _textDataRepository.GetAsync();
+                return all.Count;
+            }
+            else
+            {
+                var byProject = await _textDataRepository.GetByProjectIdAsync(projectId);
+                return byProject.Count;
+            }
+        }
+
+        public async Task<bool> IsHealthyAsync()
+        {
+            try
+            {
+                var count = await GetDocumentCountAsync();
+                return true;
+            }
+            catch
+            {
+                return false;
+            }
+        }
+
+        public async Task<Dictionary<string, object>> GetStatsAsync()
+        {
+            var totalDocs = await GetDocumentCountAsync();
+            return new Dictionary<string, object>
+            {
+                ["provider"] = "MongoDB",
+                ["total_documents"] = totalDocs,
+                ["health"] = await IsHealthyAsync(),
+                ["last_check"] = DateTime.UtcNow
+            };
+        }
+
+        private double CalcularSimilaridadeCoseno(double[] embedding1, double[] embedding2)
+        {
+            double dotProduct = 0.0;
+            double normA = 0.0;
+            double normB = 0.0;
+            for (int i = 0; i < embedding1.Length; i++)
+            {
+                dotProduct += embedding1[i] * embedding2[i];
+                normA += Math.Pow(embedding1[i], 2);
+                normB += Math.Pow(embedding2[i], 2);
+            }
+            return dotProduct / (Math.Sqrt(normA) * Math.Sqrt(normB));
+        }
+    }
+}
+#pragma warning restore SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.

Services/SearchVectors/QdrantVectorSearchService.cs

@@ -0,0 +1,557 @@
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+using Qdrant.Client.Grpc;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using Qdrant.Client;
+using static Qdrant.Client.Grpc.Conditions;
+using System.Drawing;
+using System.Collections.Concurrent;
+
+#pragma warning disable SKEXP0001
+
+namespace ChatRAG.Services.SearchVectors
+{
+    public class QdrantVectorSearchService : IVectorSearchService
+    {
+        private readonly QdrantClient _client;
+        private readonly QdrantSettings _settings;
+        private readonly ILogger<QdrantVectorSearchService> _logger;
+        private volatile bool _collectionInitialized = false;
+        private readonly SemaphoreSlim _initializationSemaphore = new(1, 1);
+        private readonly ConcurrentDictionary<string, bool> _collectionCache = new();
+
+        public QdrantVectorSearchService(
+            IOptions<VectorDatabaseSettings> settings,
+            ILogger<QdrantVectorSearchService> logger)
+        {
+            _settings = settings.Value.Qdrant;
+            _logger = logger;
+
+            _client = new QdrantClient(_settings.Host, _settings.Port, https: _settings.UseTls);
+
+            _logger.LogInformation("QdrantVectorSearchService inicializado para {Host}:{Port}",
+                _settings.Host, _settings.Port);
+        }
+
+        private async Task EnsureCollectionExistsAsync()
+        {
+            if (_collectionInitialized) return;
+
+            await _initializationSemaphore.WaitAsync();
+            try
+            {
+                if (_collectionInitialized) return;
+
+                // Verifica cache primeiro
+                if (_collectionCache.TryGetValue(_settings.CollectionName, out bool exists) && exists)
+                {
+                    _collectionInitialized = true;
+                    return;
+                }
+
+                var collectionExists = await _client.CollectionExistsAsync(_settings.CollectionName);
+                _collectionCache.TryAdd(_settings.CollectionName, collectionExists);
+
+                if (!collectionExists)
+                {
+                    _logger.LogInformation("Criando collection {CollectionName}...", _settings.CollectionName);
+
+                    var vectorsConfig = new VectorParams
+                    {
+                        Size = (ulong)_settings.VectorSize,
+                        Distance = _settings.Distance.ToLower() switch
+                        {
+                            "cosine" => Distance.Cosine,
+                            "euclid" => Distance.Euclid,
+                            "dot" => Distance.Dot,
+                            "manhattan" => Distance.Manhattan,
+                            _ => Distance.Cosine
+                        }
+                    };
+
+                    // Configurações HNSW otimizadas
+                    if (_settings.HnswM > 0)
+                    {
+                        vectorsConfig.HnswConfig = new HnswConfigDiff
+                        {
+                            M = (ulong)_settings.HnswM,
+                            EfConstruct = (ulong)_settings.HnswEfConstruct,
+                            OnDisk = _settings.OnDisk
+                        };
+                    }
+
+                    await _client.CreateCollectionAsync(
+                        collectionName: _settings.CollectionName,
+                        vectorsConfig: vectorsConfig
+                    );
+
+                    _collectionCache.TryAdd(_settings.CollectionName, true);
+                    _logger.LogInformation("✅ Collection {CollectionName} criada", _settings.CollectionName);
+                }
+
+                _collectionInitialized = true;
+            }
+            finally
+            {
+                _initializationSemaphore.Release();
+            }
+        }
+
+        public async Task<List<VectorSearchResult>> SearchSimilarAsync(
+            double[] queryEmbedding,
+            string? projectId = null,
+            double threshold = 0.3,
+            int limit = 5,
+            Dictionary<string, object>? filters = null)
+        {
+            await EnsureCollectionExistsAsync();
+
+            try
+            {
+                var vector = queryEmbedding.Select(x => (float)x).ToArray();
+
+                Filter? filter = null;
+                if (!string.IsNullOrEmpty(projectId) || filters?.Any() == true)
+                {
+                    var mustConditions = new List<Condition>();
+
+                    if (!string.IsNullOrEmpty(projectId))
+                    {
+                        mustConditions.Add(MatchKeyword("project_id", projectId));
+                    }
+
+                    if (filters?.Any() == true)
+                    {
+                        foreach (var kvp in filters)
+                        {
+                            mustConditions.Add(MatchKeyword(kvp.Key, kvp.Value.ToString()!));
+                        }
+                    }
+
+                    if (mustConditions.Any())
+                    {
+                        filter = new Filter();
+                        filter.Must.AddRange(mustConditions);
+                    }
+                }
+
+                var searchResult = await _client.SearchAsync(
+                    collectionName: _settings.CollectionName,
+                    vector: vector,
+                    filter: filter,
+                    limit: (ulong)limit,
+                    scoreThreshold: (float)threshold,
+                    payloadSelector: true,
+                    vectorsSelector: false // Otimização: não buscar vetores desnecessariamente
+                );
+
+                return searchResult.Select(ConvertToVectorSearchResult).ToList();
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro na busca vetorial Qdrant");
+                throw;
+            }
+        }
+
+        public async Task<List<VectorSearchResult>> SearchSimilarDynamicAsync(
+            double[] queryEmbedding,
+            string projectId,
+            double minThreshold = 0.5,
+            int limit = 5)
+        {
+            var results = await SearchSimilarAsync(queryEmbedding, projectId, minThreshold, limit);
+
+            if (results.Count < 3 && minThreshold > 0.2)
+            {
+                results = await SearchSimilarAsync(queryEmbedding, projectId, minThreshold * 0.7, limit);
+            }
+
+            if (results.Count < 3)
+            {
+                results = await SearchSimilarAsync(queryEmbedding, projectId, 0.2, limit);
+            }
+
+            return results.Take(limit).ToList();
+        }
+
+        public async Task<string> AddDocumentAsync(
+            string title,
+            string content,
+            string projectId,
+            double[] embedding,
+            Dictionary<string, object>? metadata = null)
+        {
+            await EnsureCollectionExistsAsync();
+
+            try
+            {
+                var id = Guid.NewGuid().ToString();
+                var vector = embedding.Select(x => (float)x).ToArray();
+
+                var payload = CreatePayload(title, content, projectId, metadata, isUpdate: false);
+
+                var point = new PointStruct
+                {
+                    Id = new PointId { Uuid = id },
+                    Vectors = vector,
+                    Payload = { payload }
+                };
+
+                await _client.UpsertAsync(
+                    collectionName: _settings.CollectionName,
+                    points: new[] { point }
+                );
+
+                _logger.LogDebug("Documento {Id} adicionado ao Qdrant", id);
+                return id;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao adicionar documento no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task UpdateDocumentAsync(
+            string id,
+            string title,
+            string content,
+            string projectId,
+            double[] embedding,
+            Dictionary<string, object>? metadata = null)
+        {
+            await EnsureCollectionExistsAsync();
+
+            try
+            {
+                var vector = embedding.Select(x => (float)x).ToArray();
+                var payload = CreatePayload(title, content, projectId, metadata, isUpdate: true);
+
+                var point = new PointStruct
+                {
+                    Id = new PointId { Uuid = id },
+                    Vectors = vector,
+                    Payload = { payload }
+                };
+
+                await _client.UpsertAsync(
+                    collectionName: _settings.CollectionName,
+                    points: new[] { point }
+                );
+
+                _logger.LogDebug("Documento {Id} atualizado no Qdrant", id);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar documento {Id} no Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task DeleteDocumentAsync(string id)
+        {
+            await EnsureCollectionExistsAsync();
+
+            try
+            {
+                var pointId = new PointId { Uuid = id };
+
+                await _client.DeleteAsync(
+                    collectionName: _settings.CollectionName,
+                    ids: new ulong[] { pointId.Num } 
+                );
+
+                _logger.LogDebug("Documento {Id} removido do Qdrant", id);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao remover documento {Id} do Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task<bool> DocumentExistsAsync(string id)
+        {
+            try
+            {
+                await EnsureCollectionExistsAsync();
+
+                var pointId = new PointId { Uuid = id };
+
+                var results = await _client.RetrieveAsync(
+                    collectionName: _settings.CollectionName,
+                    ids: new PointId[] { pointId },
+                    withPayload: false, // Otimização: só queremos saber se existe
+                    withVectors: false
+                );
+
+                return results.Any();
+            }
+            catch
+            {
+                return false;
+            }
+        }
+
+        public async Task<VectorSearchResult?> GetDocumentAsync(string id)
+        {
+            await EnsureCollectionExistsAsync();
+
+            try
+            {
+                var pointId = new PointId { Uuid = id };
+
+                var results = await _client.RetrieveAsync(
+                    collectionName: _settings.CollectionName,
+                    ids: new PointId[] { pointId },
+                    withPayload: true,
+                    withVectors: false
+                );
+
+                var point = results.FirstOrDefault();
+                return point != null ? ConvertToVectorSearchResult(point) : null;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar documento {Id} do Qdrant", id);
+                return null;
+            }
+        }
+
+        public async Task<List<VectorSearchResult>> GetDocumentsByProjectAsync(string projectId)
+        {
+            await EnsureCollectionExistsAsync();
+
+            try
+            {
+                var filter = new Filter();
+                filter.Must.Add(MatchKeyword("project_id", projectId));
+
+                var scrollRequest = new ScrollPoints
+                {
+                    CollectionName = _settings.CollectionName,
+                    Filter = filter,
+                    Limit = 10000,
+                    WithPayload = true,
+                    WithVectors = false // Otimização: não buscar vetores
+                };
+
+                var results = await _client.ScrollAsync(_settings.CollectionName, filter, 10000, null, true, false);
+
+                return results.Result.Select(ConvertToVectorSearchResult).ToList();
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao buscar documentos do projeto {ProjectId} no Qdrant", projectId);
+                throw;
+            }
+        }
+
+        public async Task<int> GetDocumentCountAsync(string? projectId = null)
+        {
+            await EnsureCollectionExistsAsync();
+
+            try
+            {
+                Filter? filter = null;
+                if (!string.IsNullOrEmpty(projectId))
+                {
+                    filter = new Filter();
+                    filter.Must.Add(MatchKeyword("project_id", projectId));
+                }
+
+                var result = await _client.CountAsync(_settings.CollectionName, filter);
+                return (int)result;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao contar documentos no Qdrant");
+                return 0;
+            }
+        }
+
+        public async Task<bool> IsHealthyAsync()
+        {
+            try
+            {
+                var collections = await _client.ListCollectionsAsync();
+                return collections != null;
+            }
+            catch
+            {
+                return false;
+            }
+        }
+
+        public async Task<Dictionary<string, object>> GetStatsAsync()
+        {
+            try
+            {
+                await EnsureCollectionExistsAsync();
+
+                var collectionInfo = await _client.GetCollectionInfoAsync(_settings.CollectionName);
+                var totalDocs = await GetDocumentCountAsync();
+
+                return new Dictionary<string, object>
+                {
+                    ["provider"] = "Qdrant",
+                    ["total_documents"] = totalDocs,
+                    ["collection_name"] = _settings.CollectionName,
+                    ["vector_size"] = _settings.VectorSize,
+                    ["distance_metric"] = _settings.Distance,
+                    ["points_count"] = collectionInfo.PointsCount,
+                    ["segments_count"] = collectionInfo.SegmentsCount,
+                    ["health"] = await IsHealthyAsync(),
+                    ["last_check"] = DateTime.UtcNow
+                };
+            }
+            catch (Exception ex)
+            {
+                return new Dictionary<string, object>
+                {
+                    ["provider"] = "Qdrant",
+                    ["health"] = false,
+                    ["error"] = ex.Message,
+                    ["last_check"] = DateTime.UtcNow
+                };
+            }
+        }
+
+        // Métodos auxiliares otimizados
+        private static Dictionary<string, Value> CreatePayload(
+            string title,
+            string content,
+            string projectId,
+            Dictionary<string, object>? metadata,
+            bool isUpdate)
+        {
+            var payload = new Dictionary<string, Value>
+            {
+                ["title"] = title,
+                ["content"] = content,
+                ["project_id"] = projectId
+            };
+
+            if (isUpdate)
+            {
+                payload["updated_at"] = DateTime.UtcNow.ToString("O");
+            }
+            else
+            {
+                payload["created_at"] = DateTime.UtcNow.ToString("O");
+                payload["updated_at"] = DateTime.UtcNow.ToString("O");
+            }
+
+            if (metadata?.Any() == true)
+            {
+                foreach (var kvp in metadata)
+                {
+                    payload[$"meta_{kvp.Key}"] = ConvertToValue(kvp.Value);
+                }
+            }
+
+            return payload;
+        }
+
+        private static VectorSearchResult ConvertToVectorSearchResult(ScoredPoint point)
+        {
+            return new VectorSearchResult
+            {
+                Id = point.Id.Uuid ?? point.Id.Num.ToString(),
+                Title = GetStringFromPayload(point.Payload, "title"),
+                Content = GetStringFromPayload(point.Payload, "content"),
+                ProjectId = GetStringFromPayload(point.Payload, "project_id"),
+                Score = point.Score,
+                Provider = "Qdrant",
+                CreatedAt = GetDateTimeFromPayload(point.Payload, "created_at"),
+                UpdatedAt = GetDateTimeFromPayload(point.Payload, "updated_at"),
+                Metadata = ConvertPayloadToMetadata(point.Payload)
+            };
+        }
+
+        private static VectorSearchResult ConvertToVectorSearchResult(RetrievedPoint point)
+        {
+            return new VectorSearchResult
+            {
+                Id = point.Id.Uuid ?? point.Id.Num.ToString(),
+                Title = GetStringFromPayload(point.Payload, "title"),
+                Content = GetStringFromPayload(point.Payload, "content"),
+                ProjectId = GetStringFromPayload(point.Payload, "project_id"),
+                Score = 1.0,
+                Provider = "Qdrant",
+                CreatedAt = GetDateTimeFromPayload(point.Payload, "created_at"),
+                UpdatedAt = GetDateTimeFromPayload(point.Payload, "updated_at"),
+                Metadata = ConvertPayloadToMetadata(point.Payload)
+            };
+        }
+
+        private static Value ConvertToValue(object value)
+        {
+            return value switch
+            {
+                string s => s,
+                int i => i,
+                long l => l,
+                double d => d,
+                float f => f,
+                bool b => b,
+                DateTime dt => dt.ToString("O"),
+                _ => value?.ToString() ?? ""
+            };
+        }
+
+        private static string GetStringFromPayload(
+            IDictionary<string, Value> payload,
+            string key,
+            string defaultValue = "")
+        {
+            return payload.TryGetValue(key, out var value) ? value.StringValue : defaultValue;
+        }
+
+        private static DateTime GetDateTimeFromPayload(
+            IDictionary<string, Value> payload,
+            string key)
+        {
+            if (payload.TryGetValue(key, out var value) &&
+                DateTime.TryParse(value.StringValue, out var date))
+            {
+                return date;
+            }
+            return DateTime.UtcNow;
+        }
+
+        private static Dictionary<string, object>? ConvertPayloadToMetadata(
+            IDictionary<string, Value> payload)
+        {
+            var metadata = new Dictionary<string, object>();
+
+            foreach (var kvp in payload.Where(p => p.Key.StartsWith("meta_")))
+            {
+                var key = kvp.Key.Substring(5);
+                var value = kvp.Value;
+
+                metadata[key] = value.KindCase switch
+                {
+                    Value.KindOneofCase.StringValue => value.StringValue,
+                    Value.KindOneofCase.IntegerValue => value.IntegerValue,
+                    Value.KindOneofCase.DoubleValue => value.DoubleValue,
+                    Value.KindOneofCase.BoolValue => value.BoolValue,
+                    _ => value.StringValue
+                };
+            }
+
+            return metadata.Any() ? metadata : null;
+        }
+
+        public void Dispose()
+        {
+            _initializationSemaphore?.Dispose();
+            _client?.Dispose();
+        }
+    }
+}
+
+#pragma warning restore SKEXP0001

Services/SearchVectors/VectorDatabaseFactory.cs

@@ -0,0 +1,107 @@
+using ChatApi.Data;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.ResponseService;
+using ChatRAG.Services.TextServices;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+
+namespace ChatRAG.Services.SearchVectors
+{
+    public class VectorDatabaseFactory : IVectorDatabaseFactory
+    {
+        private readonly IServiceProvider _serviceProvider;
+        private readonly VectorDatabaseSettings _settings;
+        private readonly ILogger<VectorDatabaseFactory> _logger;
+
+        public VectorDatabaseFactory(
+            IServiceProvider serviceProvider,
+            IOptions<VectorDatabaseSettings> settings,
+            ILogger<VectorDatabaseFactory> logger)
+        {
+            _serviceProvider = serviceProvider;
+            _settings = settings.Value;
+            _logger = logger;
+        }
+
+        public string GetActiveProvider()
+        {
+            return _settings.Provider;
+        }
+
+        public VectorDatabaseSettings GetSettings()
+        {
+            return _settings;
+        }
+
+        public IVectorSearchService CreateVectorSearchService()
+        {
+            _logger.LogInformation("Criando VectorSearchService para provider: {Provider}", _settings.Provider);
+
+            return _settings.Provider.ToLower() switch
+            {
+                "qdrant" => GetService<QdrantVectorSearchService>(),
+                "mongodb" => GetService<MongoVectorSearchService>(),
+                "chroma" => GetService<ChromaVectorSearchService>(),
+                _ => throw new ArgumentException($"Provider de VectorSearch não suportado: {_settings.Provider}")
+            };
+        }
+
+        public ITextDataService CreateTextDataService()
+        {
+            _logger.LogInformation("Criando TextDataService para provider: {Provider}", _settings.Provider);
+
+            return _settings.Provider.ToLower() switch
+            {
+                "qdrant" => GetService<QdrantTextDataService>(),
+                "mongodb" => GetService<MongoTextDataService>(),
+                "chroma" => GetService<ChromaTextDataService>(),
+                _ => throw new ArgumentException($"Provider de TextDataService não suportado: {_settings.Provider}")
+            };
+        }
+
+        public IResponseService CreateResponseService()
+        {
+            _logger.LogInformation("Criando ResponseService para provider: {Provider}", _settings.Provider);
+
+            // Verificar se deve usar RAG Hierárquico
+            var configuration = _serviceProvider.GetService<IConfiguration>();
+            var useHierarchical = configuration?.GetValue<bool>("Features:UseHierarchicalRAG") ?? false;
+            var useConfidenceAware = configuration?.GetValue<bool>("Features:UseConfidenceAwareRAG") ?? false;
+
+            if (useHierarchical && !useConfidenceAware)
+            {
+                _logger.LogInformation("Usando HierarchicalRAGService");
+                return GetService<HierarchicalRAGService>();
+            }
+            
+            if (useConfidenceAware)
+            {
+                _logger.LogInformation("Usando ConfidenceAwareRAGService");
+                return GetService<ConfidenceAwareRAGService>();
+            }
+
+            // Usar estratégia baseada no provider ou configuração
+            var ragStrategy = configuration?.GetValue<string>("Features:RAGStrategy");
+
+            return ragStrategy?.ToLower() switch
+            {
+                "hierarchical" => GetService<HierarchicalRAGService>(),
+                "standard" => GetService<ResponseRAGService>(),
+                _ => GetService<ResponseRAGService>() // Padrão
+            };
+        }
+
+        private T GetService<T>() where T : class
+        {
+            var service = _serviceProvider.GetService<T>();
+            if (service == null)
+            {
+                throw new InvalidOperationException($"Serviço {typeof(T).Name} não está registrado no DI container. " +
+                    $"Verifique se o serviço foi registrado para o provider '{_settings.Provider}'.");
+            }
+            return service;
+        }
+    }
+}

Services/SearchVectors/anv10eil.vdi~

@@ -0,0 +1,55 @@
+using ChatApi.Data;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.ResponseService;
+using ChatRAG.Services.TextServices;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+
+namespace ChatRAG.Services.SearchVectors
+{
+    public class VectorDatabaseFactory : IVectorDatabaseFactory
+    {
+        private readonly IServiceProvider _serviceProvider;
+        private readonly VectorDatabaseSettings _settings;
+        private readonly ILogger<VectorDatabaseFactory> _logger;
+
+        public VectorDatabaseFactory(
+            IServiceProvider serviceProvider,
+            IOptions<VectorDatabaseSettings> settings,
+            ILogger<VectorDatabaseFactory> logger)
+        {
+            _serviceProvider = serviceProvider;
+            _settings = settings.Value;
+            _logger = logger;
+        }
+
+        public string GetActiveProvider()
+        {
+            return _settings.Provider;
+        }
+
+        public IVectorSearchService CreateVectorSearchService()
+        {
+            _logger.LogInformation("Criando VectorSearchService para provider: {Provider}", _settings.Provider);
+
+            return _settings.Provider.ToLower() switch
+            {
+                "qdrant" => GetService<QdrantVectorSearchService>(),
+                "mongodb" => GetService<MongoVectorSearchService>(),
+                "chroma" => GetService<ChromaVectorSearchService>(),
+                _ => throw new ArgumentException($"Provider de VectorSearch não suportado: {_settings.Provider}")
+            };
+        }
+
+        private T GetService<T>() where T : class
+        {
+            var service = _serviceProvider.GetService<T>();
+            if (service == null)
+            {
+                throw new InvalidOperationException($"Serviço {typeof(T).Name} não está registrado no DI container");
+            }
+            return service;
+        }
+    }
+}

Services/TextServices/ChromaTextDataService.cs

@@ -0,0 +1,537 @@
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Data;
+using Microsoft.SemanticKernel.Embeddings;
+using System.Text;
+
+#pragma warning disable SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+namespace ChatRAG.Services
+{
+    // ========================================
+    // CHROMA TEXT DATA SERVICE - IMPLEMENTAÇÃO COMPLETA
+    // ========================================
+
+    public class ChromaTextDataService : ITextDataService
+    {
+        private readonly IVectorSearchService _vectorSearchService;
+        private readonly ITextEmbeddingGenerationService _embeddingService;
+        private readonly ILogger<ChromaTextDataService> _logger;
+
+        public ChromaTextDataService(
+            IVectorSearchService vectorSearchService,
+            ITextEmbeddingGenerationService embeddingService,
+            ILogger<ChromaTextDataService> logger)
+        {
+            _vectorSearchService = vectorSearchService;
+            _embeddingService = embeddingService;
+            _logger = logger;
+        }
+
+        public string ProviderName => "Chroma";
+
+        // ========================================
+        // MÉTODOS ORIGINAIS (compatibilidade com MongoDB)
+        // ========================================
+
+        public async Task SalvarNoMongoDB(string titulo, string texto, string projectId)
+        {
+            await SalvarNoMongoDB(null, titulo, texto, projectId);
+        }
+
+        public async Task SalvarNoMongoDB(string? id, string titulo, string texto, string projectId)
+        {
+            try
+            {
+                var conteudo = $"**{titulo}** \n\n {texto}";
+
+                // Gera embedding
+                var embedding = await _embeddingService.GenerateEmbeddingAsync(conteudo);
+                var embeddingArray = embedding.ToArray().Select(e => (double)e).ToArray();
+
+                if (string.IsNullOrEmpty(id))
+                {
+                    // Cria novo documento
+                    await _vectorSearchService.AddDocumentAsync(titulo, texto, projectId, embeddingArray);
+                    _logger.LogDebug("Documento '{Title}' criado no Chroma", titulo);
+                }
+                else
+                {
+                    // Atualiza documento existente
+                    await _vectorSearchService.UpdateDocumentAsync(id, titulo, texto, projectId, embeddingArray);
+                    _logger.LogDebug("Documento '{Id}' atualizado no Chroma", id);
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar documento '{Title}' no Chroma", titulo);
+                throw;
+            }
+        }
+
+        public async Task SalvarTextoComEmbeddingNoMongoDB(string textoCompleto, string projectId)
+        {
+            try
+            {
+                var textoArray = new List<string>();
+                string[] textolinhas = textoCompleto.Split(
+                    new string[] { "\n" },
+                    StringSplitOptions.None
+                );
+
+                var title = textolinhas[0];
+                var builder = new StringBuilder();
+
+                foreach (string line in textolinhas)
+                {
+                    if (line.StartsWith("**") || line.StartsWith("\r**"))
+                    {
+                        if (builder.Length > 0)
+                        {
+                            textoArray.Add(title.Replace("**", "").Replace("\r", "") + ": " + Environment.NewLine + builder.ToString());
+                            builder = new StringBuilder();
+                            title = line;
+                        }
+                    }
+                    else
+                    {
+                        builder.AppendLine(line);
+                    }
+                }
+
+                // Adiciona último bloco se houver
+                if (builder.Length > 0)
+                {
+                    textoArray.Add(title.Replace("**", "").Replace("\r", "") + ": " + Environment.NewLine + builder.ToString());
+                }
+
+                // Processa cada seção
+                foreach (var item in textoArray)
+                {
+                    await SalvarNoMongoDB(title.Replace("**", "").Replace("\r", ""), item, projectId);
+                }
+
+                _logger.LogInformation("Texto completo processado: {SectionCount} seções salvas no Chroma", textoArray.Count);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao processar texto completo no Chroma");
+                throw;
+            }
+        }
+
+        public async Task<IEnumerable<TextoComEmbedding>> GetAll()
+        {
+            try
+            {
+                // Busca todos os projetos e depois todos os documentos
+                var allDocuments = new List<VectorSearchResult>();
+
+                // Como Chroma não tem um "GetAll" direto, vamos usar scroll
+                // Isso é uma limitação vs MongoDB, mas é mais eficiente
+                var projects = await GetAllProjectIds();
+
+                foreach (var projectId in projects)
+                {
+                    var projectDocs = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+                    allDocuments.AddRange(projectDocs);
+                }
+
+                return allDocuments.Select(ConvertToTextoComEmbedding);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar todos os documentos do Chroma");
+                throw;
+            }
+        }
+
+        public async Task<IEnumerable<TextoComEmbedding>> GetByPorjectId(string projectId)
+        {
+            try
+            {
+                var documents = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+                return documents.Select(ConvertToTextoComEmbedding);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar documentos do projeto {ProjectId} no Chroma", projectId);
+                throw;
+            }
+        }
+
+        public async Task<TextoComEmbedding> GetById(string id)
+        {
+            try
+            {
+                var document = await _vectorSearchService.GetDocumentAsync(id);
+                if (document == null)
+                {
+                    throw new ArgumentException($"Documento {id} não encontrado no Chroma");
+                }
+
+                return ConvertToTextoComEmbedding(document);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar documento {Id} do Chroma", id);
+                throw;
+            }
+        }
+
+        // ========================================
+        // MÉTODOS NOVOS DA INTERFACE
+        // ========================================
+
+        public async Task<string> SaveDocumentAsync(DocumentInput document)
+        {
+            try
+            {
+                var conteudo = $"**{document.Title}** \n\n {document.Content}";
+                var embedding = await _embeddingService.GenerateEmbeddingAsync(conteudo);
+                var embeddingArray = embedding.ToArray().Select(e => (double)e).ToArray();
+
+                string id;
+                if (!string.IsNullOrEmpty(document.Id))
+                {
+                    // Atualizar documento existente
+                    await _vectorSearchService.UpdateDocumentAsync(
+                        document.Id,
+                        document.Title,
+                        document.Content,
+                        document.ProjectId,
+                        embeddingArray,
+                        document.Metadata);
+                    id = document.Id;
+                }
+                else
+                {
+                    // Criar novo documento
+                    id = await _vectorSearchService.AddDocumentAsync(
+                        document.Title,
+                        document.Content,
+                        document.ProjectId,
+                        embeddingArray,
+                        document.Metadata);
+                }
+
+                _logger.LogDebug("Documento {Id} salvo no Chroma via SaveDocumentAsync", id);
+                return id;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar documento no Chroma");
+                throw;
+            }
+        }
+
+        public async Task UpdateDocumentAsync(string id, DocumentInput document)
+        {
+            try
+            {
+                var conteudo = $"**{document.Title}** \n\n {document.Content}";
+                var embedding = await _embeddingService.GenerateEmbeddingAsync(conteudo);
+                var embeddingArray = embedding.ToArray().Select(e => (double)e).ToArray();
+
+                await _vectorSearchService.UpdateDocumentAsync(
+                    id,
+                    document.Title,
+                    document.Content,
+                    document.ProjectId,
+                    embeddingArray,
+                    document.Metadata);
+
+                _logger.LogDebug("Documento {Id} atualizado no Chroma", id);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar documento {Id} no Chroma", id);
+                throw;
+            }
+        }
+
+        public async Task DeleteDocumentAsync(string id)
+        {
+            try
+            {
+                await _vectorSearchService.DeleteDocumentAsync(id);
+                _logger.LogDebug("Documento {Id} deletado do Chroma", id);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao deletar documento {Id} do Chroma", id);
+                throw;
+            }
+        }
+
+        public async Task<bool> DocumentExistsAsync(string id)
+        {
+            try
+            {
+                return await _vectorSearchService.DocumentExistsAsync(id);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao verificar existência do documento {Id} no Chroma", id);
+                return false;
+            }
+        }
+
+        public async Task<DocumentOutput?> GetDocumentAsync(string id)
+        {
+            try
+            {
+                var result = await _vectorSearchService.GetDocumentAsync(id);
+                if (result == null) return null;
+
+                return new DocumentOutput
+                {
+                    Id = result.Id,
+                    Title = result.Metadata?.GetValueOrDefault("title")?.ToString() ?? "",
+                    Content = result.Content,
+                    ProjectId = result.Metadata?.GetValueOrDefault("project_id")?.ToString() ?? "",
+                    Embedding = Array.Empty<double>(), // Chroma não retorna embedding na busca
+                    CreatedAt = ParseDateTime(result.Metadata?.GetValueOrDefault("created_at")?.ToString()).Value,
+                    UpdatedAt = ParseDateTime(result.Metadata?.GetValueOrDefault("updated_at")?.ToString()).Value,
+                    Metadata = result.Metadata
+                };
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar documento {Id} do Chroma", id);
+                return null;
+            }
+        }
+
+        public async Task<List<DocumentOutput>> GetDocumentsByProjectAsync(string projectId)
+        {
+            try
+            {
+                var results = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+
+                return results.Select(result => new DocumentOutput
+                {
+                    Id = result.Id,
+                    Title = result.Metadata?.GetValueOrDefault("title")?.ToString() ?? "",
+                    Content = result.Content,
+                    ProjectId = projectId,
+                    Embedding = Array.Empty<double>(),
+                    CreatedAt = ParseDateTime(result.Metadata?.GetValueOrDefault("created_at")?.ToString()).Value,
+                    UpdatedAt = ParseDateTime(result.Metadata?.GetValueOrDefault("updated_at")?.ToString()).Value,
+                    Metadata = result.Metadata
+                }).ToList();
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar documentos do projeto {ProjectId} do Chroma", projectId);
+                throw;
+            }
+        }
+
+        public async Task<int> GetDocumentCountAsync(string? projectId = null)
+        {
+            try
+            {
+                return await _vectorSearchService.GetDocumentCountAsync(projectId);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao contar documentos no Chroma");
+                return 0;
+            }
+        }
+
+        // ========================================
+        // OPERAÇÕES EM LOTE
+        // ========================================
+
+        public async Task<List<string>> SaveDocumentsBatchAsync(List<DocumentInput> documents)
+        {
+            var ids = new List<string>();
+            var errors = new List<Exception>();
+
+            // Processa em lotes menores para performance
+            var batchSize = 10;
+            for (int i = 0; i < documents.Count; i += batchSize)
+            {
+                var batch = documents.Skip(i).Take(batchSize);
+                var tasks = batch.Select(async doc =>
+                {
+                    try
+                    {
+                        var id = await SaveDocumentAsync(doc);
+                        return id;
+                    }
+                    catch (Exception ex)
+                    {
+                        errors.Add(ex);
+                        _logger.LogError(ex, "Erro ao salvar documento '{Title}' em lote", doc.Title);
+                        return null;
+                    }
+                });
+
+                var batchResults = await Task.WhenAll(tasks);
+                ids.AddRange(batchResults.Where(id => id != null)!);
+            }
+
+            if (errors.Any())
+            {
+                _logger.LogWarning("Batch save completado com {ErrorCount} erros de {TotalCount} documentos",
+                    errors.Count, documents.Count);
+            }
+
+            _logger.LogInformation("Batch save: {SuccessCount}/{TotalCount} documentos salvos no Chroma",
+                ids.Count, documents.Count);
+
+            return ids;
+        }
+
+        public async Task DeleteDocumentsBatchAsync(List<string> ids)
+        {
+            var errors = new List<Exception>();
+
+            // Processa em lotes para não sobrecarregar
+            var batchSize = 20;
+            for (int i = 0; i < ids.Count; i += batchSize)
+            {
+                var batch = ids.Skip(i).Take(batchSize);
+                var tasks = batch.Select(async id =>
+                {
+                    try
+                    {
+                        await DeleteDocumentAsync(id);
+                        return true;
+                    }
+                    catch (Exception ex)
+                    {
+                        errors.Add(ex);
+                        _logger.LogError(ex, "Erro ao deletar documento {Id} em lote", id);
+                        return false;
+                    }
+                });
+
+                await Task.WhenAll(tasks);
+            }
+
+            if (errors.Any())
+            {
+                _logger.LogWarning("Batch delete completado com {ErrorCount} erros de {TotalCount} documentos",
+                    errors.Count, ids.Count);
+            }
+            else
+            {
+                _logger.LogInformation("Batch delete: {TotalCount} documentos removidos do Chroma", ids.Count);
+            }
+        }
+
+        // ========================================
+        // ESTATÍSTICAS DO PROVIDER
+        // ========================================
+
+        public async Task<Dictionary<string, object>> GetProviderStatsAsync()
+        {
+            try
+            {
+                var baseStats = await _vectorSearchService.GetStatsAsync();
+                var totalDocs = await GetDocumentCountAsync();
+
+                // Adiciona estatísticas específicas do TextData
+                var projectIds = await GetAllProjectIds();
+                var projectStats = new Dictionary<string, int>();
+
+                foreach (var projectId in projectIds)
+                {
+                    var count = await GetDocumentCountAsync(projectId);
+                    projectStats[projectId] = count;
+                }
+
+                var enhancedStats = new Dictionary<string, object>(baseStats)
+                {
+                    ["text_service_provider"] = "Chroma",
+                    ["total_documents_via_text_service"] = totalDocs,
+                    ["projects_count"] = projectIds.Count,
+                    ["documents_by_project"] = projectStats,
+                    ["supports_batch_operations"] = true,
+                    ["supports_metadata"] = true,
+                    ["embedding_auto_generation"] = true
+                };
+
+                return enhancedStats;
+            }
+            catch (Exception ex)
+            {
+                return new Dictionary<string, object>
+                {
+                    ["provider"] = "Chroma",
+                    ["text_service_provider"] = "Chroma",
+                    ["health"] = "error",
+                    ["error"] = ex.Message,
+                    ["last_check"] = DateTime.UtcNow
+                };
+            }
+        }
+
+        // ========================================
+        // MÉTODOS AUXILIARES PRIVADOS
+        // ========================================
+
+        private static TextoComEmbedding ConvertToTextoComEmbedding(VectorSearchResult result)
+        {
+            return new TextoComEmbedding
+            {
+                Id = result.Id,
+                Titulo = result.Metadata?.GetValueOrDefault("title")?.ToString() ?? "",
+                Conteudo = result.Content,
+                ProjetoId = result.Metadata?.GetValueOrDefault("project_id")?.ToString() ?? "",
+                Embedding = Array.Empty<double>(), // Chroma não retorna embedding na busca
+                                                   // Campos que podem não existir no Chroma
+                ProjetoNome = result.Metadata?.GetValueOrDefault("project_name")?.ToString() ?? "",
+                TipoDocumento = result.Metadata?.GetValueOrDefault("document_type")?.ToString() ?? "",
+                Categoria = result.Metadata?.GetValueOrDefault("category")?.ToString() ?? "",
+                Tags = result.Metadata?.GetValueOrDefault("tags") as string[] ?? Array.Empty<string>()
+            };
+        }
+
+        private async Task<List<string>> GetAllProjectIds()
+        {
+            try
+            {
+                // Esta é uma operação custosa no Chroma
+                // Em produção, seria melhor manter um cache de project IDs
+                // ou usar uma estrutura de dados separada
+
+                // Por agora, vamos usar uma busca com um vetor dummy para pegar todos os documentos
+                var dummyVector = new double[384]; // Assumindo embeddings padrão
+                var allResults = await _vectorSearchService.SearchSimilarAsync(
+                    dummyVector,
+                    projectId: null,
+                    threshold: 0.0,
+                    limit: 10000);
+
+                return allResults
+                    .Select(r => r.Metadata?.GetValueOrDefault("project_id")?.ToString())
+                    .Where(pid => !string.IsNullOrEmpty(pid))
+                    .Distinct()
+                    .ToList()!;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar IDs de projetos do Chroma");
+                return new List<string>();
+            }
+        }
+
+        private static DateTime? ParseDateTime(string? dateString)
+        {
+            if (string.IsNullOrEmpty(dateString))
+                return null;
+
+            if (DateTime.TryParse(dateString, out var date))
+                return date;
+
+            return null;
+        }
+    }
+}
+#pragma warning restore SKEXP0001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+

Services/TextServices/QdrantTextDataService.cs

@@ -0,0 +1,674 @@
+#pragma warning disable SKEXP0001
+
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using Microsoft.SemanticKernel.Embeddings;
+using System.Text;
+using System.Collections.Concurrent;
+
+namespace ChatRAG.Services.TextServices
+{
+    public class QdrantTextDataService : ITextDataService
+    {
+        private readonly IVectorSearchService _vectorSearchService;
+        private readonly ITextEmbeddingGenerationService _embeddingService;
+        private readonly ILogger<QdrantTextDataService> _logger;
+
+        // Cache para project IDs para evitar buscas custosas
+        private readonly ConcurrentDictionary<string, DateTime> _projectIdCache = new();
+        private readonly TimeSpan _cacheTimeout = TimeSpan.FromMinutes(5);
+
+        public QdrantTextDataService(
+            IVectorSearchService vectorSearchService,
+            ITextEmbeddingGenerationService embeddingService,
+            ILogger<QdrantTextDataService> logger)
+        {
+            _vectorSearchService = vectorSearchService;
+            _embeddingService = embeddingService;
+            _logger = logger;
+        }
+
+        public string ProviderName => "Qdrant";
+
+        // ========================================
+        // MÉTODOS ORIGINAIS (compatibilidade com MongoDB)
+        // ========================================
+
+        public async Task SalvarNoMongoDB(string titulo, string texto, string projectId)
+        {
+            await SalvarNoMongoDB(null, titulo, texto, projectId);
+        }
+
+        public async Task SalvarNoMongoDB(string? id, string titulo, string texto, string projectId)
+        {
+            try
+            {
+                var conteudo = $"**{titulo}** \n\n {texto}";
+
+                // Gera embedding uma única vez
+                var embedding = await GenerateEmbeddingOptimized(conteudo);
+
+                if (string.IsNullOrEmpty(id))
+                {
+                    // Cria novo documento
+                    var newId = await _vectorSearchService.AddDocumentAsync(titulo, texto, projectId, embedding);
+
+                    // Atualiza cache de project IDs
+                    _projectIdCache.TryAdd(projectId, DateTime.UtcNow);
+
+                    _logger.LogDebug("Documento '{Title}' criado no Qdrant com ID {Id}", titulo, newId);
+                }
+                else
+                {
+                    // Atualiza documento existente
+                    await _vectorSearchService.UpdateDocumentAsync(id, titulo, texto, projectId, embedding);
+                    _logger.LogDebug("Documento '{Id}' atualizado no Qdrant", id);
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar documento '{Title}' no Qdrant", titulo);
+                throw;
+            }
+        }
+
+        public async Task SalvarTextoComEmbeddingNoMongoDB(string textoCompleto, string projectId)
+        {
+            try
+            {
+                var textoArray = ParseTextIntoSections(textoCompleto);
+
+                // Processa seções em paralelo com limite de concorrência
+                var semaphore = new SemaphoreSlim(5, 5); // Máximo 5 operações simultâneas
+                var tasks = textoArray.Select(async item =>
+                {
+                    await semaphore.WaitAsync();
+                    try
+                    {
+                        var lines = item.Split('\n', 2);
+                        var title = lines[0].Replace("**", "").Replace("\r", "").Trim();
+                        var content = lines.Length > 1 ? lines[1] : "";
+
+                        await SalvarNoMongoDB(title, content, projectId);
+                    }
+                    finally
+                    {
+                        semaphore.Release();
+                    }
+                });
+
+                await Task.WhenAll(tasks);
+                semaphore.Dispose();
+
+                _logger.LogInformation("Texto completo processado: {SectionCount} seções salvas no Qdrant", textoArray.Count);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao processar texto completo no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task<IEnumerable<TextoComEmbedding>> GetAll()
+        {
+            try
+            {
+                // Usa cache de project IDs quando possível
+                var projectIds = await GetAllProjectIdsOptimized();
+
+                if (!projectIds.Any())
+                {
+                    return Enumerable.Empty<TextoComEmbedding>();
+                }
+
+                var allDocuments = new List<VectorSearchResult>();
+
+                // Busca documentos em paralelo por projeto
+                var semaphore = new SemaphoreSlim(3, 3); // Máximo 3 projetos simultâneos
+                var tasks = projectIds.Select(async projectId =>
+                {
+                    await semaphore.WaitAsync();
+                    try
+                    {
+                        return await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+                    }
+                    catch (Exception ex)
+                    {
+                        _logger.LogWarning(ex, "Erro ao buscar documentos do projeto {ProjectId}", projectId);
+                        return new List<VectorSearchResult>();
+                    }
+                    finally
+                    {
+                        semaphore.Release();
+                    }
+                });
+
+                var results = await Task.WhenAll(tasks);
+                semaphore.Dispose();
+
+                foreach (var projectDocs in results)
+                {
+                    allDocuments.AddRange(projectDocs);
+                }
+
+                return allDocuments.Select(ConvertToTextoComEmbedding);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar todos os documentos do Qdrant");
+                throw;
+            }
+        }
+
+        public async Task<IEnumerable<TextoComEmbedding>> GetByPorjectId(string projectId)
+        {
+            try
+            {
+                var documents = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+                return documents.Select(ConvertToTextoComEmbedding);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar documentos do projeto {ProjectId} no Qdrant", projectId);
+                throw;
+            }
+        }
+
+        public async Task<TextoComEmbedding> GetById(string id)
+        {
+            try
+            {
+                var document = await _vectorSearchService.GetDocumentAsync(id);
+                if (document == null)
+                {
+                    throw new ArgumentException($"Documento {id} não encontrado no Qdrant");
+                }
+
+                return ConvertToTextoComEmbedding(document);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar documento {Id} do Qdrant", id);
+                throw;
+            }
+        }
+
+        // ========================================
+        // MÉTODOS NOVOS DA INTERFACE
+        // ========================================
+
+        public async Task<string> SaveDocumentAsync(DocumentInput document)
+        {
+            try
+            {
+                var embedding = await GenerateEmbeddingOptimized($"**{document.Title}** \n\n {document.Content}");
+
+                string id;
+                if (!string.IsNullOrEmpty(document.Id))
+                {
+                    // Atualizar documento existente
+                    await _vectorSearchService.UpdateDocumentAsync(
+                        document.Id,
+                        document.Title,
+                        document.Content,
+                        document.ProjectId,
+                        embedding,
+                        document.Metadata);
+                    id = document.Id;
+                }
+                else
+                {
+                    // Criar novo documento
+                    id = await _vectorSearchService.AddDocumentAsync(
+                        document.Title,
+                        document.Content,
+                        document.ProjectId,
+                        embedding,
+                        document.Metadata);
+                }
+
+                // Atualiza cache de project IDs
+                _projectIdCache.TryAdd(document.ProjectId, DateTime.UtcNow);
+
+                _logger.LogDebug("Documento {Id} salvo no Qdrant via SaveDocumentAsync", id);
+                return id;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao salvar documento no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task UpdateDocumentAsync(string id, DocumentInput document)
+        {
+            try
+            {
+                var embedding = await GenerateEmbeddingOptimized($"**{document.Title}** \n\n {document.Content}");
+
+                await _vectorSearchService.UpdateDocumentAsync(
+                    id,
+                    document.Title,
+                    document.Content,
+                    document.ProjectId,
+                    embedding,
+                    document.Metadata);
+
+                _logger.LogDebug("Documento {Id} atualizado no Qdrant", id);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao atualizar documento {Id} no Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task DeleteDocumentAsync(string id)
+        {
+            try
+            {
+                await _vectorSearchService.DeleteDocumentAsync(id);
+                _logger.LogDebug("Documento {Id} deletado do Qdrant", id);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao deletar documento {Id} do Qdrant", id);
+                throw;
+            }
+        }
+
+        public async Task<bool> DocumentExistsAsync(string id)
+        {
+            try
+            {
+                return await _vectorSearchService.DocumentExistsAsync(id);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao verificar existência do documento {Id} no Qdrant", id);
+                return false;
+            }
+        }
+
+        public async Task<DocumentOutput?> GetDocumentAsync(string id)
+        {
+            try
+            {
+                var result = await _vectorSearchService.GetDocumentAsync(id);
+                if (result == null) return null;
+
+                return new DocumentOutput
+                {
+                    Id = result.Id,
+                    Title = result.Title,
+                    Content = result.Content,
+                    ProjectId = result.ProjectId,
+                    Embedding = result.Embedding,
+                    CreatedAt = result.CreatedAt,
+                    UpdatedAt = result.UpdatedAt,
+                    Metadata = result.Metadata
+                };
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar documento {Id} do Qdrant", id);
+                return null;
+            }
+        }
+
+        public async Task<List<DocumentOutput>> GetDocumentsByProjectAsync(string projectId)
+        {
+            try
+            {
+                var results = await _vectorSearchService.GetDocumentsByProjectAsync(projectId);
+
+                return results.Select(result => new DocumentOutput
+                {
+                    Id = result.Id,
+                    Title = result.Title,
+                    Content = result.Content,
+                    ProjectId = result.ProjectId,
+                    Embedding = result.Embedding,
+                    CreatedAt = result.CreatedAt,
+                    UpdatedAt = result.UpdatedAt,
+                    Metadata = result.Metadata
+                }).ToList();
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar documentos do projeto {ProjectId} do Qdrant", projectId);
+                throw;
+            }
+        }
+
+        public async Task<int> GetDocumentCountAsync(string? projectId = null)
+        {
+            try
+            {
+                return await _vectorSearchService.GetDocumentCountAsync(projectId);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao contar documentos no Qdrant");
+                return 0;
+            }
+        }
+
+        // ========================================
+        // OPERAÇÕES EM LOTE OTIMIZADAS
+        // ========================================
+
+        public async Task<List<string>> SaveDocumentsBatchAsync(List<DocumentInput> documents)
+        {
+            var ids = new List<string>();
+            var errors = new List<Exception>();
+
+            // Agrupa documentos por projeto para otimizar embeddings
+            var documentsByProject = documents.GroupBy(d => d.ProjectId).ToList();
+
+            foreach (var projectGroup in documentsByProject)
+            {
+                var projectDocs = projectGroup.ToList();
+
+                // Processa em lotes menores dentro do projeto
+                var batchSize = 5; // Reduzido para evitar timeout
+                for (int i = 0; i < projectDocs.Count; i += batchSize)
+                {
+                    var batch = projectDocs.Skip(i).Take(batchSize);
+
+                    // Gera embeddings em paralelo para o lote
+                    var embeddingTasks = batch.Select(async doc =>
+                    {
+                        try
+                        {
+                            var embedding = await GenerateEmbeddingOptimized($"**{doc.Title}** \n\n {doc.Content}");
+                            return new { Document = doc, Embedding = embedding, Error = (Exception?)null };
+                        }
+                        catch (Exception ex)
+                        {
+                            return new { Document = doc, Embedding = (double[]?)null, Error = ex };
+                        }
+                    });
+
+                    var embeddingResults = await Task.WhenAll(embeddingTasks);
+
+                    // Salva documentos com embeddings gerados
+                    var saveTasks = embeddingResults.Select(async result =>
+                    {
+                        if (result.Error != null)
+                        {
+                            errors.Add(result.Error);
+                            return null;
+                        }
+
+                        try
+                        {
+                            string id;
+                            if (!string.IsNullOrEmpty(result.Document.Id))
+                            {
+                                await _vectorSearchService.UpdateDocumentAsync(
+                                    result.Document.Id,
+                                    result.Document.Title,
+                                    result.Document.Content,
+                                    result.Document.ProjectId,
+                                    result.Embedding!,
+                                    result.Document.Metadata);
+                                id = result.Document.Id;
+                            }
+                            else
+                            {
+                                id = await _vectorSearchService.AddDocumentAsync(
+                                    result.Document.Title,
+                                    result.Document.Content,
+                                    result.Document.ProjectId,
+                                    result.Embedding!,
+                                    result.Document.Metadata);
+                            }
+                            return id;
+                        }
+                        catch (Exception ex)
+                        {
+                            errors.Add(ex);
+                            _logger.LogError(ex, "Erro ao salvar documento '{Title}' em lote", result.Document.Title);
+                            return null;
+                        }
+                    });
+
+                    var batchResults = await Task.WhenAll(saveTasks);
+                    ids.AddRange(batchResults.Where(id => id != null)!);
+                }
+
+                // Atualiza cache para o projeto
+                _projectIdCache.TryAdd(projectGroup.Key, DateTime.UtcNow);
+            }
+
+            if (errors.Any())
+            {
+                _logger.LogWarning("Batch save completado com {ErrorCount} erros de {TotalCount} documentos",
+                    errors.Count, documents.Count);
+            }
+
+            _logger.LogInformation("Batch save: {SuccessCount}/{TotalCount} documentos salvos no Qdrant",
+                ids.Count, documents.Count);
+
+            return ids;
+        }
+
+        public async Task DeleteDocumentsBatchAsync(List<string> ids)
+        {
+            var errors = new List<Exception>();
+
+            // Processa em lotes pequenos para não sobrecarregar
+            var batchSize = 10; // Reduzido para melhor estabilidade
+            for (int i = 0; i < ids.Count; i += batchSize)
+            {
+                var batch = ids.Skip(i).Take(batchSize);
+                var tasks = batch.Select(async id =>
+                {
+                    try
+                    {
+                        await _vectorSearchService.DeleteDocumentAsync(id);
+                        return true;
+                    }
+                    catch (Exception ex)
+                    {
+                        errors.Add(ex);
+                        _logger.LogError(ex, "Erro ao deletar documento {Id} em lote", id);
+                        return false;
+                    }
+                });
+
+                await Task.WhenAll(tasks);
+            }
+
+            if (errors.Any())
+            {
+                _logger.LogWarning("Batch delete completado com {ErrorCount} erros de {TotalCount} documentos",
+                    errors.Count, ids.Count);
+            }
+            else
+            {
+                _logger.LogInformation("Batch delete: {TotalCount} documentos removidos do Qdrant", ids.Count);
+            }
+        }
+
+        // ========================================
+        // ESTATÍSTICAS DO PROVIDER
+        // ========================================
+
+        public async Task<Dictionary<string, object>> GetProviderStatsAsync()
+        {
+            try
+            {
+                var baseStats = await _vectorSearchService.GetStatsAsync();
+                var totalDocs = await GetDocumentCountAsync();
+
+                // Usa cache para project IDs
+                var projectIds = await GetAllProjectIdsOptimized();
+                var projectStats = new Dictionary<string, int>();
+
+                // Busca contadores em paralelo
+                var countTasks = projectIds.Select(async projectId =>
+                {
+                    try
+                    {
+                        var count = await GetDocumentCountAsync(projectId);
+                        return new { ProjectId = projectId, Count = count };
+                    }
+                    catch
+                    {
+                        return new { ProjectId = projectId, Count = 0 };
+                    }
+                });
+
+                var countResults = await Task.WhenAll(countTasks);
+                foreach (var result in countResults)
+                {
+                    projectStats[result.ProjectId] = result.Count;
+                }
+
+                var enhancedStats = new Dictionary<string, object>(baseStats)
+                {
+                    ["text_service_provider"] = "Qdrant",
+                    ["total_documents_via_text_service"] = totalDocs,
+                    ["projects_count"] = projectIds.Count,
+                    ["documents_by_project"] = projectStats,
+                    ["supports_batch_operations"] = true,
+                    ["supports_metadata"] = true,
+                    ["embedding_auto_generation"] = true,
+                    ["cache_enabled"] = true,
+                    ["cached_project_ids"] = _projectIdCache.Count
+                };
+
+                return enhancedStats;
+            }
+            catch (Exception ex)
+            {
+                return new Dictionary<string, object>
+                {
+                    ["provider"] = "Qdrant",
+                    ["text_service_provider"] = "Qdrant",
+                    ["health"] = "error",
+                    ["error"] = ex.Message,
+                    ["last_check"] = DateTime.UtcNow
+                };
+            }
+        }
+
+        // ========================================
+        // MÉTODOS AUXILIARES PRIVADOS OTIMIZADOS
+        // ========================================
+
+        private async Task<double[]> GenerateEmbeddingOptimized(string content)
+        {
+            var embedding = await _embeddingService.GenerateEmbeddingAsync(content);
+            return embedding.ToArray().Select(e => (double)e).ToArray();
+        }
+
+        private static List<string> ParseTextIntoSections(string textoCompleto)
+        {
+            var textoArray = new List<string>();
+            string[] textolinhas = textoCompleto.Split(new string[] { "\n" }, StringSplitOptions.None);
+
+            var title = textolinhas[0];
+            var builder = new StringBuilder();
+
+            foreach (string line in textolinhas)
+            {
+                if (line.StartsWith("**") || line.StartsWith("\r**"))
+                {
+                    if (builder.Length > 0)
+                    {
+                        textoArray.Add(title.Replace("**", "").Replace("\r", "") + ": " + Environment.NewLine + builder.ToString());
+                        builder = new StringBuilder();
+                        title = line;
+                    }
+                }
+                else
+                {
+                    builder.AppendLine(line);
+                }
+            }
+
+            // Adiciona último bloco se houver
+            if (builder.Length > 0)
+            {
+                textoArray.Add(title.Replace("**", "").Replace("\r", "") + ": " + Environment.NewLine + builder.ToString());
+            }
+
+            return textoArray;
+        }
+
+        private async Task<List<string>> GetAllProjectIdsOptimized()
+        {
+            // Remove entradas expiradas do cache
+            var now = DateTime.UtcNow;
+            var expiredKeys = _projectIdCache
+                .Where(kvp => now - kvp.Value > _cacheTimeout)
+                .Select(kvp => kvp.Key)
+                .ToList();
+
+            foreach (var key in expiredKeys)
+            {
+                _projectIdCache.TryRemove(key, out _);
+            }
+
+            // Se temos dados no cache e não estão muito antigos, usa o cache
+            if (_projectIdCache.Any())
+            {
+                return _projectIdCache.Keys.ToList();
+            }
+
+            // Caso contrário, busca no Qdrant
+            try
+            {
+                // Esta busca é custosa, mas só será executada quando o cache estiver vazio
+                var allResults = await _vectorSearchService.SearchSimilarAsync(
+                    new double[384], // Vector dummy menor
+                    projectId: null,
+                    threshold: 0.0,
+                    limit: 1000); // Limit menor para melhor performance
+
+                var projectIds = allResults
+                    .Select(r => r.ProjectId)
+                    .Where(pid => !string.IsNullOrEmpty(pid))
+                    .Distinct()
+                    .ToList();
+
+                // Atualiza cache
+                foreach (var projectId in projectIds)
+                {
+                    _projectIdCache.TryAdd(projectId, now);
+                }
+
+                return projectIds;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar IDs de projetos do Qdrant");
+                return new List<string>();
+            }
+        }
+
+        private static TextoComEmbedding ConvertToTextoComEmbedding(VectorSearchResult result)
+        {
+            return new TextoComEmbedding
+            {
+                Id = result.Id,
+                Titulo = result.Title,
+                Conteudo = result.Content,
+                ProjetoId = result.ProjectId,
+                Embedding = result.Embedding,
+                // Campos que podem não existir no Qdrant
+                ProjetoNome = result.Metadata?.GetValueOrDefault("project_name")?.ToString() ?? "",
+                TipoDocumento = result.Metadata?.GetValueOrDefault("document_type")?.ToString() ?? "",
+                Categoria = result.Metadata?.GetValueOrDefault("category")?.ToString() ?? "",
+                Tags = result.Metadata?.GetValueOrDefault("tags") as string[] ?? Array.Empty<string>()
+            };
+        }
+    }
+}
+
+#pragma warning restore SKEXP0001

Services/VectorDatabaseHealthCheck.cs

@@ -0,0 +1,64 @@
+using ChatRAG.Services.Contracts;
+using Microsoft.Extensions.Diagnostics.HealthChecks;
+
+namespace ChatRAG.Services
+{
+    public class VectorDatabaseHealthCheck : IHealthCheck
+    {
+        private readonly IVectorDatabaseFactory _factory;
+        private readonly ILogger<VectorDatabaseHealthCheck> _logger;
+
+        public VectorDatabaseHealthCheck(
+            IVectorDatabaseFactory factory,
+            ILogger<VectorDatabaseHealthCheck> logger)
+        {
+            _factory = factory;
+            _logger = logger;
+        }
+
+        public async Task<HealthCheckResult> CheckHealthAsync(
+            HealthCheckContext context,
+            CancellationToken cancellationToken = default)
+        {
+            try
+            {
+                var provider = _factory.GetActiveProvider();
+                var vectorService = _factory.CreateVectorSearchService();
+                var textService = _factory.CreateTextDataService();
+
+                // Testa conectividade básica
+                var isHealthy = await vectorService.IsHealthyAsync();
+                var stats = await vectorService.GetStatsAsync();
+                var providerStats = await textService.GetProviderStatsAsync();
+
+                var data = new Dictionary<string, object>
+                {
+                    ["provider"] = provider,
+                    ["vector_service_healthy"] = isHealthy,
+                    ["total_documents"] = stats.GetValueOrDefault("total_documents", 0),
+                    ["provider_stats"] = providerStats
+                };
+
+                if (isHealthy)
+                {
+                    _logger.LogDebug("Vector Database health check passou para provider {Provider}", provider);
+                    return HealthCheckResult.Healthy($"Vector Database ({provider}) está saudável", data);
+                }
+                else
+                {
+                    _logger.LogWarning("Vector Database health check falhou para provider {Provider}", provider);
+                    return HealthCheckResult.Unhealthy($"Vector Database ({provider}) não está saudável", data: data);
+                }
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro no health check do Vector Database");
+                return HealthCheckResult.Unhealthy("Erro no Vector Database", ex, new Dictionary<string, object>
+                {
+                    ["provider"] = _factory.GetActiveProvider(),
+                    ["error"] = ex.Message
+                });
+            }
+        }
+    }
+}

Settings/ConfidenceAwareSettings.cs

@@ -0,0 +1,120 @@
+namespace ChatRAG.Settings
+{
+    /// <summary>
+    /// Configurações específicas para o ConfidenceAwareRAG
+    /// </summary>
+    public class ConfidenceAwareSettings
+    {
+        /// <summary>
+        /// Habilita/desabilita verificação de confiança
+        /// true = só responde com confiança, false = sempre responde (como hoje)
+        /// </summary>
+        public bool EnableConfidenceCheck { get; set; } = true;
+
+        /// <summary>
+        /// Modo restrito (critérios rigorosos) vs modo relaxado
+        /// </summary>
+        public bool UseStrictMode { get; set; } = true;
+
+        /// <summary>
+        /// Mostra informações de debug na resposta (confiança, tempo, etc.)
+        /// </summary>
+        public bool ShowDebugInfo { get; set; } = false;
+
+        /// <summary>
+        /// Domínio padrão quando não conseguir detectar automaticamente
+        /// </summary>
+        public string DefaultDomain { get; set; } = "TI";
+
+        /// <summary>
+        /// Mapeamento de palavras-chave para domínios (detecção automática)
+        /// </summary>
+        public Dictionary<string, string> DomainMappings { get; set; } = new()
+        {
+            ["software"] = "TI",
+            ["sistema"] = "TI",
+            ["api"] = "TI",
+            ["backend"] = "TI",
+            ["frontend"] = "TI",
+            ["database"] = "TI",
+            ["funcionário"] = "RH",
+            ["colaborador"] = "RH",
+            ["employee"] = "RH",
+            ["hr"] = "RH",
+            ["financeiro"] = "Financeiro",
+            ["contábil"] = "Financeiro",
+            ["financial"] = "Financeiro",
+            ["accounting"] = "Financeiro",
+            ["teste"] = "QA",
+            ["qualidade"] = "QA",
+            ["quality"] = "QA",
+            ["testing"] = "QA"
+        };
+
+        /// <summary>
+        /// Configuração de idiomas suportados
+        /// </summary>
+        public LanguageSettings Languages { get; set; } = new();
+
+        /// <summary>
+        /// Configurações de cache para prompts
+        /// </summary>
+        public CacheSettings Cache { get; set; } = new();
+    }
+
+    /// <summary>
+    /// Configurações de idioma
+    /// </summary>
+    public class LanguageSettings
+    {
+        /// <summary>
+        /// Idioma padrão do sistema
+        /// </summary>
+        public string DefaultLanguage { get; set; } = "pt";
+
+        /// <summary>
+        /// Idiomas suportados
+        /// </summary>
+        public List<string> SupportedLanguages { get; set; } = new() { "pt", "en" };
+
+        /// <summary>
+        /// Auto-detectar idioma da pergunta
+        /// </summary>
+        public bool AutoDetectLanguage { get; set; } = true;
+
+        /// <summary>
+        /// Sempre responder no idioma detectado/solicitado, mesmo que prompts estejam em PT
+        /// </summary>
+        public bool AlwaysRespondInRequestedLanguage { get; set; } = true;
+
+        /// <summary>
+        /// Palavras-chave para detecção automática de idioma
+        /// </summary>
+        public Dictionary<string, List<string>> LanguageKeywords { get; set; } = new()
+        {
+            ["en"] = new() { "what", "how", "why", "where", "when", "which", "who", "can", "could", "would", "should", "will", "the", "and", "or", "but", "system", "project", "document", "explain", "generate" },
+            ["pt"] = new() { "que", "como", "por", "onde", "quando", "qual", "quem", "pode", "poderia", "deveria", "será", "o", "a", "e", "ou", "mas", "sistema", "projeto", "documento", "explique", "gere" }
+        };
+    }
+
+    /// <summary>
+    /// Configurações de cache
+    /// </summary>
+    public class CacheSettings
+    {
+        /// <summary>
+        /// Habilitar cache de prompts carregados
+        /// </summary>
+        public bool EnablePromptCache { get; set; } = true;
+
+        /// <summary>
+        /// Tempo de cache em minutos
+        /// </summary>
+        public int CacheExpirationMinutes { get; set; } = 30;
+
+        /// <summary>
+        /// Recarregar arquivos automaticamente quando modificados
+        /// </summary>
+        public bool AutoReloadOnFileChange { get; set; } = true;
+    }
+}

Settings/ConfidenceSettings.cs

@@ -0,0 +1,126 @@
+using System.ComponentModel.DataAnnotations;
+
+namespace ChatRAG.Settings
+{
+    /// <summary>
+    /// Configurações para verificação de confiança por estratégia
+    /// </summary>
+    public class ConfidenceSettings
+    {
+        public bool StrictModeByDefault { get; set; } = true;
+
+        [Required]
+        public Dictionary<string, ConfidenceThresholds> Thresholds { get; set; } = new()
+        {
+            ["overview"] = new ConfidenceThresholds
+            {
+                MinDocuments = 5,
+                MinRelevantDocuments = 3,
+                MinHighQualityDocuments = 1,
+                MinContextLength = 1000,
+                MinOverallScore = 0.3,
+                MinMaxScore = 0.4,
+                MinAverageScore = 0.3
+            },
+            ["specific"] = new ConfidenceThresholds
+            {
+                MinDocuments = 2,
+                MinRelevantDocuments = 2,
+                MinHighQualityDocuments = 1,
+                MinContextLength = 500,
+                MinOverallScore = 0.4,
+                MinMaxScore = 0.5,
+                MinAverageScore = 0.4
+            },
+            ["detailed"] = new ConfidenceThresholds
+            {
+                MinDocuments = 3,
+                MinRelevantDocuments = 2,
+                MinHighQualityDocuments = 2,
+                MinContextLength = 800,
+                MinOverallScore = 0.5,
+                MinMaxScore = 0.6,
+                MinAverageScore = 0.5
+            }
+        };
+
+        /// <summary>
+        /// Mensagens de fallback por idioma
+        /// </summary>
+        public Dictionary<string, ConfidenceFallbackMessages> FallbackMessages { get; set; } = new()
+        {
+            ["pt"] = new ConfidenceFallbackMessages
+            {
+                NoDocuments = "Não encontrei informações sobre isso no projeto atual. Você poderia reformular a pergunta ou ser mais específico?",
+                NoRelevantDocuments = "Encontrei alguns documentos, mas nenhum parece diretamente relacionado à sua pergunta. Pode tentar ser mais específico ou usar outras palavras-chave?",
+                InsufficientOverview = "Não tenho informações suficientes para fornecer uma visão geral completa do projeto. Talvez você possa fazer uma pergunta mais específica?",
+                InsufficientSpecific = "Não encontrei documentação suficiente sobre esse tópico específico. Você pode tentar reformular a pergunta?",
+                InsufficientDetailed = "Preciso de mais contexto técnico para responder adequadamente. Você pode ser mais específico sobre o que está procurando?",
+                Generic = "Não tenho informações suficientes para responder com segurança. Pode tentar reformular a pergunta?"
+            },
+            ["en"] = new ConfidenceFallbackMessages
+            {
+                NoDocuments = "I couldn't find information about this in the current project. Could you rephrase the question or be more specific?",
+                NoRelevantDocuments = "I found some documents, but none seem directly related to your question. Could you try being more specific or use different keywords?",
+                InsufficientOverview = "I don't have enough information to provide a complete project overview. Perhaps you could ask a more specific question?",
+                InsufficientSpecific = "I didn't find sufficient documentation about this specific topic. Could you try rephrasing the question?",
+                InsufficientDetailed = "I need more technical context to respond adequately. Could you be more specific about what you're looking for?",
+                Generic = "I don't have enough information to respond safely. Could you try rephrasing the question?"
+            }
+        };
+    }
+
+    /// <summary>
+    /// Thresholds de confiança para uma estratégia específica
+    /// </summary>
+    public class ConfidenceThresholds
+    {
+        /// <summary>
+        /// Número mínimo de documentos encontrados
+        /// </summary>
+        public int MinDocuments { get; set; }
+
+        /// <summary>
+        /// Número mínimo de documentos relevantes (score >= 0.3)
+        /// </summary>
+        public int MinRelevantDocuments { get; set; }
+
+        /// <summary>
+        /// Número mínimo de documentos de alta qualidade (score >= 0.6)
+        /// </summary>
+        public int MinHighQualityDocuments { get; set; }
+
+        /// <summary>
+        /// Tamanho mínimo do contexto combinado (caracteres)
+        /// </summary>
+        public int MinContextLength { get; set; }
+
+        /// <summary>
+        /// Score geral mínimo (0.0 a 1.0)
+        /// </summary>
+        public double MinOverallScore { get; set; }
+
+        /// <summary>
+        /// Score máximo mínimo entre os documentos encontrados
+        /// </summary>
+        public double MinMaxScore { get; set; }
+
+        /// <summary>
+        /// Score médio mínimo entre os documentos encontrados
+        /// </summary>
+        public double MinAverageScore { get; set; }
+    }
+
+    /// <summary>
+    /// Mensagens de fallback quando não há confiança suficiente
+    /// </summary>
+    public class ConfidenceFallbackMessages
+    {
+        public string NoDocuments { get; set; } = "";
+        public string NoRelevantDocuments { get; set; } = "";
+        public string InsufficientOverview { get; set; } = "";
+        public string InsufficientSpecific { get; set; } = "";
+        public string InsufficientDetailed { get; set; } = "";
+        public string Generic { get; set; } = "";
+    }
+}

Settings/VectorDatabaseSettings.cs

@@ -0,0 +1,178 @@
+using Microsoft.Extensions.AI;
+using Qdrant.Client.Grpc;
+
+namespace ChatRAG.Settings.ChatRAG.Configuration
+{
+    public class VectorDatabaseSettings
+    {
+        public string Provider { get; set; } = "Qdrant";
+        public MongoDBSettings? MongoDB { get; set; }
+        public QdrantSettings? Qdrant { get; set; }
+        public ChromaSettings? Chroma { get; set; }
+        public EmbeddingSettings Embedding { get; set; } = new();
+
+        /// <summary>
+        /// Retorna erros de validação
+        /// </summary>
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (string.IsNullOrWhiteSpace(Provider))
+                errors.Add("Provider é obrigatório");
+
+            switch (Provider.ToLower())
+            {
+                case "mongodb":
+                    errors.AddRange(MongoDB.GetValidationErrors());
+                    break;
+                case "qdrant":
+                    errors.AddRange(Qdrant.GetValidationErrors());
+                    break;
+                case "chroma":
+                    errors.AddRange(Chroma.GetValidationErrors());
+                    break;
+                default:
+                    errors.Add($"Provider '{Provider}' não é suportado");
+                    break;
+            }
+
+            errors.AddRange(Embedding.GetValidationErrors());
+
+            return errors;
+        }
+    }
+
+    public class MongoDBSettings
+    {
+        public string ConnectionString { get; set; } = "";
+        public string DatabaseName { get; set; } = "";
+        public string TextCollectionName { get; set; } = "Texts";
+        public string ProjectCollectionName { get; set; } = "Groups";
+        public string UserDataName { get; set; } = "UserData";
+        public int ConnectionTimeoutSeconds { get; set; } = 30;
+
+        public List<string> GetValidationErrors()
+        {
+                var errors = new List<string>();
+
+                if (string.IsNullOrWhiteSpace(ConnectionString))
+                    errors.Add("MongoDB ConnectionString é obrigatória");
+
+                if (string.IsNullOrWhiteSpace(DatabaseName))
+                    errors.Add("MongoDB DatabaseName é obrigatório");
+
+                if (string.IsNullOrWhiteSpace(TextCollectionName))
+                    errors.Add("MongoDB TextCollectionName é obrigatório");
+
+                if (ConnectionTimeoutSeconds <= 0)
+                    errors.Add("MongoDB ConnectionTimeoutSeconds deve ser maior que 0");
+
+                return errors;
+        }
+    }
+
+    public class QdrantSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 6334;
+        public string CollectionName { get; set; } = "texts";
+        public string GroupsCollectionName { get; set; } = "projects";
+        public int VectorSize { get; set; } = 384;
+        public string Distance { get; set; } = "Cosine";
+        public int HnswM { get; set; } = 16;
+        public int HnswEfConstruct { get; set; } = 200;
+        public bool OnDisk { get; set; } = false;
+        public bool UseTls { get; set; } = false;
+
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (string.IsNullOrWhiteSpace(Host))
+                errors.Add("Qdrant Host é obrigatório");
+
+            if (Port <= 0)
+                errors.Add("Qdrant Port deve ser maior que 0");
+
+            if (string.IsNullOrWhiteSpace(CollectionName))
+                errors.Add("Qdrant CollectionName é obrigatório");
+
+            if (VectorSize <= 0)
+                errors.Add("Qdrant VectorSize deve ser maior que 0");
+
+            if (HnswM <= 0)
+                errors.Add("Qdrant HnswM deve ser maior que 0");
+
+            if (HnswEfConstruct <= 0)
+                errors.Add("Qdrant HnswEfConstruct deve ser maior que 0");
+
+            var validDistances = new[] { "Cosine", "Euclid", "Dot", "Manhattan" };
+            if (!validDistances.Contains(Distance))
+                errors.Add($"Qdrant Distance deve ser um de: {string.Join(", ", validDistances)}");
+
+            return errors;
+        }
+    }
+
+    public class ChromaSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 8000;
+        public string CollectionName { get; set; } = "rag_documents";
+        public string ApiVersion { get; set; } = "v1";
+
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            return errors;
+        }
+    }
+
+    public class EmbeddingSettings
+    {
+        /// <summary>
+        /// Provider de embedding (OpenAI, Ollama, Azure, etc.)
+        /// </summary>
+        public string Provider { get; set; } = "OpenAI";
+
+        /// <summary>
+        /// Modelo de embedding
+        /// </summary>
+        public string Model { get; set; } = "text-embedding-ada-002";
+
+        /// <summary>
+        /// Tamanho esperado do embedding
+        /// </summary>
+        public int ExpectedSize { get; set; } = 1536;
+
+        /// <summary>
+        /// Batch size para processamento em lote
+        /// </summary>
+        public int BatchSize { get; set; } = 100;
+
+        /// <summary>
+        /// Cache de embeddings em memória
+        /// </summary>
+        public bool EnableCache { get; set; } = true;
+
+        /// <summary>
+        /// TTL do cache em minutos
+        /// </summary>
+        public int CacheTtlMinutes { get; set; } = 60;
+
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (ExpectedSize <= 0)
+                errors.Add("Embedding ExpectedSize deve ser maior que 0");
+
+            if (BatchSize <= 0)
+                errors.Add("Embedding BatchSize deve ser maior que 0");
+
+            return errors;
+        }
+    }
+}

Settings/VectorDatabaseSettingsValidator.cs

@@ -0,0 +1,23 @@
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.Extensions.Options;
+
+namespace ChatRAG.Settings
+{
+    /// <summary>
+    /// Validador para VectorDatabaseSettings
+    /// </summary>
+    public class VectorDatabaseSettingsValidator : IValidateOptions<VectorDatabaseSettings>
+    {
+        public ValidateOptionsResult Validate(string name, VectorDatabaseSettings options)
+        {
+            var errors = options.GetValidationErrors();
+
+            if (errors.Any())
+            {
+                return ValidateOptionsResult.Fail(errors);
+            }
+
+            return ValidateOptionsResult.Success;
+        }
+    }
+}

Settings/gckijn3t.ir5~

@@ -0,0 +1,128 @@
+using Microsoft.Extensions.AI;
+using Qdrant.Client.Grpc;
+
+namespace ChatRAG.Settings.ChatRAG.Configuration
+{
+    public class VectorDatabaseSettings
+    {
+        public string Provider { get; set; } = "Qdrant";
+        public MongoDBSettings? MongoDB { get; set; }
+        public QdrantSettings? Qdrant { get; set; }
+        public ChromaSettings? Chroma { get; set; }
+
+        /// <summary>
+        /// Retorna erros de validação
+        /// </summary>
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (string.IsNullOrWhiteSpace(Provider))
+                errors.Add("Provider é obrigatório");
+
+            switch (Provider.ToLower())
+            {
+                case "mongodb":
+                    errors.AddRange(MongoDB.GetValidationErrors());
+                    break;
+                case "qdrant":
+                    errors.AddRange(Qdrant.GetValidationErrors());
+                    break;
+                default:
+                    errors.Add($"Provider '{Provider}' não é suportado");
+                    break;
+            }
+
+            errors.AddRange(Embedding.GetValidationErrors());
+
+            return errors;
+        }
+    }
+}
+
+    public class MongoDBSettings
+    {
+        public string ConnectionString { get; set; } = "";
+        public string DatabaseName { get; set; } = "";
+        public string TextCollectionName { get; set; } = "Texts";
+        public string ProjectCollectionName { get; set; } = "Groups";
+        public string UserDataName { get; set; } = "UserData";
+        public int ConnectionTimeoutSeconds { get; set; } = 30;
+
+        public List<string> GetValidationErrors()
+        {
+                var errors = new List<string>();
+
+                if (string.IsNullOrWhiteSpace(ConnectionString))
+                    errors.Add("MongoDB ConnectionString é obrigatória");
+
+                if (string.IsNullOrWhiteSpace(DatabaseName))
+                    errors.Add("MongoDB DatabaseName é obrigatório");
+
+                if (string.IsNullOrWhiteSpace(TextCollectionName))
+                    errors.Add("MongoDB TextCollectionName é obrigatório");
+
+                if (ConnectionTimeoutSeconds <= 0)
+                    errors.Add("MongoDB ConnectionTimeoutSeconds deve ser maior que 0");
+
+                return errors;
+        }
+    }
+
+    public class QdrantSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 6334;
+        public string CollectionName { get; set; } = "texts";
+        public int VectorSize { get; set; } = 384;
+        public string Distance { get; set; } = "Cosine";
+        public int HnswM { get; set; } = 16;
+        public int HnswEfConstruct { get; set; } = 200;
+        public bool OnDisk { get; set; } = false;
+        public bool UseTls { get; set; } = false;
+
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (string.IsNullOrWhiteSpace(Host))
+                errors.Add("Qdrant Host é obrigatório");
+
+            if (Port <= 0)
+                errors.Add("Qdrant Port deve ser maior que 0");
+
+            if (string.IsNullOrWhiteSpace(CollectionName))
+                errors.Add("Qdrant CollectionName é obrigatório");
+
+            if (VectorSize <= 0)
+                errors.Add("Qdrant VectorSize deve ser maior que 0");
+
+            if (HnswM <= 0)
+                errors.Add("Qdrant HnswM deve ser maior que 0");
+
+            if (HnswEfConstruct <= 0)
+                errors.Add("Qdrant HnswEfConstruct deve ser maior que 0");
+
+            var validDistances = new[] { "Cosine", "Euclid", "Dot", "Manhattan" };
+            if (!validDistances.Contains(Distance))
+                errors.Add($"Qdrant Distance deve ser um de: {string.Join(", ", validDistances)}");
+
+            return errors;
+        }
+    }
+
+    public class ChromaSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 8000;
+        public string CollectionName { get; set; } = "rag_documents";
+        public string ApiVersion { get; set; } = "v1";
+
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            return errors;
+        }
+    }
+}

Settings/ghcutjxi.wn3~

@@ -0,0 +1,120 @@
+using Microsoft.Extensions.AI;
+
+namespace ChatRAG.Settings.ChatRAG.Configuration
+{
+    public class VectorDatabaseSettings
+    {
+        public string Provider { get; set; } = "Qdrant";
+        public MongoDBSettings? MongoDB { get; set; }
+        public QdrantSettings? Qdrant { get; set; }
+        public ChromaSettings? Chroma { get; set; }
+
+        /// <summary>
+        /// Retorna erros de validação
+        /// </summary>
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (string.IsNullOrWhiteSpace(Provider))
+                errors.Add("Provider é obrigatório");
+
+            switch (Provider.ToLower())
+            {
+                case "mongodb":
+                    errors.AddRange(MongoDB.GetValidationErrors());
+                    break;
+                case "qdrant":
+                    errors.AddRange(Qdrant.GetValidationErrors());
+                    break;
+                default:
+                    errors.Add($"Provider '{Provider}' não é suportado");
+                    break;
+            }
+
+            errors.AddRange(Embedding.GetValidationErrors());
+
+            return errors;
+        }
+    }
+}
+
+    public class MongoDBSettings
+    {
+        public string ConnectionString { get; set; } = "";
+        public string DatabaseName { get; set; } = "";
+        public string TextCollectionName { get; set; } = "Texts";
+        public string ProjectCollectionName { get; set; } = "Groups";
+        public string UserDataName { get; set; } = "UserData";
+        public int ConnectionTimeoutSeconds { get; set; } = 30;
+
+        public List<string> GetValidationErrors()
+        {
+                var errors = new List<string>();
+
+                if (string.IsNullOrWhiteSpace(ConnectionString))
+                    errors.Add("MongoDB ConnectionString é obrigatória");
+
+                if (string.IsNullOrWhiteSpace(DatabaseName))
+                    errors.Add("MongoDB DatabaseName é obrigatório");
+
+                if (string.IsNullOrWhiteSpace(TextCollectionName))
+                    errors.Add("MongoDB TextCollectionName é obrigatório");
+
+                if (ConnectionTimeoutSeconds <= 0)
+                    errors.Add("MongoDB ConnectionTimeoutSeconds deve ser maior que 0");
+
+                return errors;
+        }
+    }
+
+    public class QdrantSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 6334;
+        public string CollectionName { get; set; } = "texts";
+        public int VectorSize { get; set; } = 384;
+        public string Distance { get; set; } = "Cosine";
+        public int HnswM { get; set; } = 16;
+        public int HnswEfConstruct { get; set; } = 200;
+        public bool OnDisk { get; set; } = false;
+        public bool UseTls { get; set; } = false;
+
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (string.IsNullOrWhiteSpace(Host))
+                errors.Add("Qdrant Host é obrigatório");
+
+            if (Port <= 0)
+                errors.Add("Qdrant Port deve ser maior que 0");
+
+            if (string.IsNullOrWhiteSpace(CollectionName))
+                errors.Add("Qdrant CollectionName é obrigatório");
+
+            if (VectorSize <= 0)
+                errors.Add("Qdrant VectorSize deve ser maior que 0");
+
+            if (HnswM <= 0)
+                errors.Add("Qdrant HnswM deve ser maior que 0");
+
+            if (HnswEfConstruct <= 0)
+                errors.Add("Qdrant HnswEfConstruct deve ser maior que 0");
+
+            var validDistances = new[] { "Cosine", "Euclid", "Dot", "Manhattan" };
+            if (!validDistances.Contains(Distance))
+                errors.Add($"Qdrant Distance deve ser um de: {string.Join(", ", validDistances)}");
+
+            return errors;
+        }
+    }
+
+    public class ChromaSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 8000;
+        public string CollectionName { get; set; } = "rag_documents";
+        public string ApiVersion { get; set; } = "v1";
+    }
+}

Settings/ixb5gark.btp~

@@ -0,0 +1,91 @@
+using Microsoft.Extensions.AI;
+
+namespace ChatRAG.Settings.ChatRAG.Configuration
+{
+    public class VectorDatabaseSettings
+    {
+        public string Provider { get; set; } = "Qdrant";
+        public MongoDBSettings? MongoDB { get; set; }
+        public QdrantSettings? Qdrant { get; set; }
+        public ChromaSettings? Chroma { get; set; }
+
+        /// <summary>
+        /// Retorna erros de validação
+        /// </summary>
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (string.IsNullOrWhiteSpace(Provider))
+                errors.Add("Provider é obrigatório");
+
+            switch (Provider.ToLower())
+            {
+                case "mongodb":
+                    errors.AddRange(MongoDB.GetValidationErrors());
+                    break;
+                case "qdrant":
+                    errors.AddRange(Qdrant.GetValidationErrors());
+                    break;
+                default:
+                    errors.Add($"Provider '{Provider}' não é suportado");
+                    break;
+            }
+
+            errors.AddRange(Embedding.GetValidationErrors());
+
+            return errors;
+        }
+    }
+}
+
+    public class MongoDBSettings
+    {
+        public string ConnectionString { get; set; } = "";
+        public string DatabaseName { get; set; } = "";
+        public string TextCollectionName { get; set; } = "Texts";
+        public string ProjectCollectionName { get; set; } = "Groups";
+        public string UserDataName { get; set; } = "UserData";
+        public int ConnectionTimeoutSeconds { get; set; } = 30;
+
+        public List<string> GetValidationErrors()
+        {
+                var errors = new List<string>();
+
+                if (string.IsNullOrWhiteSpace(ConnectionString))
+                    errors.Add("MongoDB ConnectionString é obrigatória");
+
+                if (string.IsNullOrWhiteSpace(DatabaseName))
+                    errors.Add("MongoDB DatabaseName é obrigatório");
+
+                if (string.IsNullOrWhiteSpace(TextCollectionName))
+                    errors.Add("MongoDB TextCollectionName é obrigatório");
+
+                if (ConnectionTimeoutSeconds <= 0)
+                    errors.Add("MongoDB ConnectionTimeoutSeconds deve ser maior que 0");
+
+                return errors;
+        }
+    }
+
+    public class QdrantSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 6334;
+        public string CollectionName { get; set; } = "texts";
+        public int VectorSize { get; set; } = 384;
+        public string Distance { get; set; } = "Cosine";
+        public int HnswM { get; set; } = 16;
+        public int HnswEfConstruct { get; set; } = 200;
+        public bool OnDisk { get; set; } = false;
+        public bool UseTls { get; set; } = false;
+    }
+
+    public class ChromaSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 8000;
+        public string CollectionName { get; set; } = "rag_documents";
+        public string ApiVersion { get; set; } = "v1";
+    }
+}

Settings/vwuy0ebd.cjy~

@@ -0,0 +1,174 @@
+using Microsoft.Extensions.AI;
+using Qdrant.Client.Grpc;
+
+namespace ChatRAG.Settings.ChatRAG.Configuration
+{
+    public class VectorDatabaseSettings
+    {
+        public string Provider { get; set; } = "Qdrant";
+        public MongoDBSettings? MongoDB { get; set; }
+        public QdrantSettings? Qdrant { get; set; }
+        public ChromaSettings? Chroma { get; set; }
+        public EmbeddingSettings Embedding { get; set; } = new();
+
+        /// <summary>
+        /// Retorna erros de validação
+        /// </summary>
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (string.IsNullOrWhiteSpace(Provider))
+                errors.Add("Provider é obrigatório");
+
+            switch (Provider.ToLower())
+            {
+                case "mongodb":
+                    errors.AddRange(MongoDB.GetValidationErrors());
+                    break;
+                case "qdrant":
+                    errors.AddRange(Qdrant.GetValidationErrors());
+                    break;
+                default:
+                    errors.Add($"Provider '{Provider}' não é suportado");
+                    break;
+            }
+
+            errors.AddRange(Embedding.GetValidationErrors());
+
+            return errors;
+        }
+    }
+
+    public class MongoDBSettings
+    {
+        public string ConnectionString { get; set; } = "";
+        public string DatabaseName { get; set; } = "";
+        public string TextCollectionName { get; set; } = "Texts";
+        public string ProjectCollectionName { get; set; } = "Groups";
+        public string UserDataName { get; set; } = "UserData";
+        public int ConnectionTimeoutSeconds { get; set; } = 30;
+
+        public List<string> GetValidationErrors()
+        {
+                var errors = new List<string>();
+
+                if (string.IsNullOrWhiteSpace(ConnectionString))
+                    errors.Add("MongoDB ConnectionString é obrigatória");
+
+                if (string.IsNullOrWhiteSpace(DatabaseName))
+                    errors.Add("MongoDB DatabaseName é obrigatório");
+
+                if (string.IsNullOrWhiteSpace(TextCollectionName))
+                    errors.Add("MongoDB TextCollectionName é obrigatório");
+
+                if (ConnectionTimeoutSeconds <= 0)
+                    errors.Add("MongoDB ConnectionTimeoutSeconds deve ser maior que 0");
+
+                return errors;
+        }
+    }
+
+    public class QdrantSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 6334;
+        public string CollectionName { get; set; } = "texts";
+        public int VectorSize { get; set; } = 384;
+        public string Distance { get; set; } = "Cosine";
+        public int HnswM { get; set; } = 16;
+        public int HnswEfConstruct { get; set; } = 200;
+        public bool OnDisk { get; set; } = false;
+        public bool UseTls { get; set; } = false;
+
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (string.IsNullOrWhiteSpace(Host))
+                errors.Add("Qdrant Host é obrigatório");
+
+            if (Port <= 0)
+                errors.Add("Qdrant Port deve ser maior que 0");
+
+            if (string.IsNullOrWhiteSpace(CollectionName))
+                errors.Add("Qdrant CollectionName é obrigatório");
+
+            if (VectorSize <= 0)
+                errors.Add("Qdrant VectorSize deve ser maior que 0");
+
+            if (HnswM <= 0)
+                errors.Add("Qdrant HnswM deve ser maior que 0");
+
+            if (HnswEfConstruct <= 0)
+                errors.Add("Qdrant HnswEfConstruct deve ser maior que 0");
+
+            var validDistances = new[] { "Cosine", "Euclid", "Dot", "Manhattan" };
+            if (!validDistances.Contains(Distance))
+                errors.Add($"Qdrant Distance deve ser um de: {string.Join(", ", validDistances)}");
+
+            return errors;
+        }
+    }
+
+    public class ChromaSettings
+    {
+        public string Host { get; set; } = "localhost";
+        public int Port { get; set; } = 8000;
+        public string CollectionName { get; set; } = "rag_documents";
+        public string ApiVersion { get; set; } = "v1";
+
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            return errors;
+        }
+    }
+
+    public class EmbeddingSettings
+    {
+        /// <summary>
+        /// Provider de embedding (OpenAI, Ollama, Azure, etc.)
+        /// </summary>
+        public string Provider { get; set; } = "OpenAI";
+
+        /// <summary>
+        /// Modelo de embedding
+        /// </summary>
+        public string Model { get; set; } = "text-embedding-ada-002";
+
+        /// <summary>
+        /// Tamanho esperado do embedding
+        /// </summary>
+        public int ExpectedSize { get; set; } = 1536;
+
+        /// <summary>
+        /// Batch size para processamento em lote
+        /// </summary>
+        public int BatchSize { get; set; } = 100;
+
+        /// <summary>
+        /// Cache de embeddings em memória
+        /// </summary>
+        public bool EnableCache { get; set; } = true;
+
+        /// <summary>
+        /// TTL do cache em minutos
+        /// </summary>
+        public int CacheTtlMinutes { get; set; } = 60;
+
+        public List<string> GetValidationErrors()
+        {
+            var errors = new List<string>();
+
+            if (ExpectedSize <= 0)
+                errors.Add("Embedding ExpectedSize deve ser maior que 0");
+
+            if (BatchSize <= 0)
+                errors.Add("Embedding BatchSize deve ser maior que 0");
+
+            return errors;
+        }
+    }
+}

Tools/MigrationService.cs

@@ -0,0 +1,264 @@
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Models;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.Migration;
+using ChatRAG.Services.SearchVectors;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using ChatRAG.Settings;
+using Microsoft.Extensions.Options;
+using System.Diagnostics;
+
+namespace ChatRAG.Services.Migration
+{
+    public class MigrationService
+    {
+        private readonly ILogger<MigrationService> _logger;
+        private readonly IServiceProvider _serviceProvider;
+
+        public MigrationService(
+            ILogger<MigrationService> logger,
+            IServiceProvider serviceProvider)
+        {
+            _logger = logger;
+            _serviceProvider = serviceProvider;
+        }
+
+        /// <summary>
+        /// Migra todos os dados do MongoDB para Qdrant
+        /// </summary>
+        public async Task<MigrationResult> MigrateFromMongoToQdrantAsync(
+            bool validateData = true,
+            int batchSize = 50)
+        {
+            var stopwatch = Stopwatch.StartNew();
+            var result = new MigrationResult { StartTime = DateTime.UtcNow };
+
+            try
+            {
+                _logger.LogInformation("🚀 Iniciando migração MongoDB → Qdrant...");
+
+                // Cria serviços específicos para migração
+                var mongoService = CreateMongoService();
+                var qdrantService = CreateQdrantService();
+
+                // 1. Exporta dados do MongoDB
+                _logger.LogInformation("📤 Exportando dados do MongoDB...");
+                var mongoDocuments = await mongoService.GetAll();
+                var documentsList = mongoDocuments.ToList();
+
+                result.TotalDocuments = documentsList.Count;
+                _logger.LogInformation("✅ {Count} documentos encontrados no MongoDB", result.TotalDocuments);
+
+                if (!documentsList.Any())
+                {
+                    _logger.LogWarning("⚠️ Nenhum documento encontrado no MongoDB");
+                    result.Success = true;
+                    result.Message = "Migração concluída - nenhum documento para migrar";
+                    return result;
+                }
+
+                // 2. Agrupa por projeto para migração organizada
+                var documentsByProject = documentsList.GroupBy(d => d.ProjetoId).ToList();
+                _logger.LogInformation("📁 Documentos organizados em {ProjectCount} projetos", documentsByProject.Count);
+
+                // 3. Migra por projeto em lotes
+                foreach (var projectGroup in documentsByProject)
+                {
+                    var projectId = projectGroup.Key;
+                    var projectDocs = projectGroup.ToList();
+
+                    _logger.LogInformation("📂 Migrando projeto {ProjectId}: {DocCount} documentos",
+                        projectId, projectDocs.Count);
+
+                    // Processa em lotes para não sobrecarregar
+                    for (int i = 0; i < projectDocs.Count; i += batchSize)
+                    {
+                        var batch = projectDocs.Skip(i).Take(batchSize).ToList();
+
+                        try
+                        {
+                            await MigrateBatch(batch, qdrantService);
+                            result.MigratedDocuments += batch.Count;
+
+                            _logger.LogDebug("✅ Lote {BatchNum}: {BatchCount} documentos migrados",
+                                (i / batchSize) + 1, batch.Count);
+                        }
+                        catch (Exception ex)
+                        {
+                            _logger.LogError(ex, "❌ Erro no lote {BatchNum} do projeto {ProjectId}",
+                                (i / batchSize) + 1, projectId);
+
+                            result.Errors.Add($"Projeto {projectId}, lote {(i / batchSize) + 1}: {ex.Message}");
+                        }
+                    }
+                }
+
+                // 4. Validação (se solicitada)
+                if (validateData)
+                {
+                    _logger.LogInformation("🔍 Validando dados migrados...");
+                    var validationResult = await ValidateMigration(mongoService, qdrantService);
+                    result.ValidationResult = validationResult;
+
+                    if (!validationResult.IsValid)
+                    {
+                        _logger.LogWarning("⚠️ Validação encontrou inconsistências: {Issues}",
+                            string.Join(", ", validationResult.Issues));
+                    }
+                    else
+                    {
+                        _logger.LogInformation("✅ Validação passou - dados consistentes");
+                    }
+                }
+
+                stopwatch.Stop();
+                result.Duration = stopwatch.Elapsed;
+                result.Success = true;
+                result.Message = $"Migração concluída: {result.MigratedDocuments}/{result.TotalDocuments} documentos";
+
+                _logger.LogInformation("🎉 Migração concluída em {Duration}s: {MigratedCount}/{TotalCount} documentos",
+                    result.Duration.TotalSeconds, result.MigratedDocuments, result.TotalDocuments);
+
+                return result;
+            }
+            catch (Exception ex)
+            {
+                stopwatch.Stop();
+                result.Duration = stopwatch.Elapsed;
+                result.Success = false;
+                result.Message = $"Erro na migração: {ex.Message}";
+                result.Errors.Add(ex.ToString());
+
+                _logger.LogError(ex, "💥 Erro fatal na migração");
+                return result;
+            }
+        }
+
+        /// <summary>
+        /// Rollback - remove todos os dados do Qdrant
+        /// </summary>
+        public async Task<bool> RollbackQdrantAsync()
+        {
+            try
+            {
+                _logger.LogWarning("🔄 Iniciando rollback - removendo dados do Qdrant...");
+
+                var qdrantService = CreateQdrantService();
+
+                // Busca todos os documentos
+                var allDocuments = await qdrantService.GetAll();
+                var documentIds = allDocuments.Select(d => d.Id).ToList();
+
+                if (!documentIds.Any())
+                {
+                    _logger.LogInformation("ℹ️ Nenhum documento encontrado no Qdrant para rollback");
+                    return true;
+                }
+
+                // Remove em lotes
+                var batchSize = 100;
+                for (int i = 0; i < documentIds.Count; i += batchSize)
+                {
+                    var batch = documentIds.Skip(i).Take(batchSize).ToList();
+                    await qdrantService.DeleteDocumentsBatchAsync(batch);
+
+                    _logger.LogDebug("🗑️ Lote {BatchNum}: {BatchCount} documentos removidos",
+                        (i / batchSize) + 1, batch.Count);
+                }
+
+                _logger.LogInformation("✅ Rollback concluído: {Count} documentos removidos do Qdrant", documentIds.Count);
+                return true;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "❌ Erro no rollback");
+                return false;
+            }
+        }
+
+        // ========================================
+        // MÉTODOS AUXILIARES
+        // ========================================
+
+        private async Task MigrateBatch(List<ChatRAG.Models.TextoComEmbedding> batch, ITextDataService qdrantService)
+        {
+            var documents = batch.Select(doc => new DocumentInput
+            {
+                Id = doc.Id,
+                Title = doc.Titulo,
+                Content = doc.Conteudo,
+                ProjectId = doc.ProjetoId,
+                CreatedAt = DateTime.UtcNow,
+                UpdatedAt = DateTime.UtcNow,
+                Metadata = new Dictionary<string, object>
+                {
+                    ["migrated_from"] = "mongodb",
+                    ["migration_date"] = DateTime.UtcNow.ToString("O"),
+                    ["original_id"] = doc.Id,
+                    ["project_name"] = doc.ProjetoNome ?? "",
+                    ["document_type"] = doc.TipoDocumento ?? "",
+                    ["category"] = doc.Categoria ?? ""
+                }
+            }).ToList();
+
+            await qdrantService.SaveDocumentsBatchAsync(documents);
+        }
+
+        private async Task<ValidationResult> ValidateMigration(ITextDataService mongoService, ITextDataService qdrantService)
+        {
+            var result = new ValidationResult();
+
+            try
+            {
+                // Compara contagens
+                var mongoCount = await mongoService.GetDocumentCountAsync();
+                var qdrantCount = await qdrantService.GetDocumentCountAsync();
+
+                if (mongoCount != qdrantCount)
+                {
+                    result.Issues.Add($"Contagem divergente: MongoDB({mongoCount}) vs Qdrant({qdrantCount})");
+                }
+
+                // Valida alguns documentos aleatoriamente
+                var mongoDocuments = await mongoService.GetAll();
+                var sampleDocs = mongoDocuments.Take(10).ToList();
+
+                foreach (var mongoDoc in sampleDocs)
+                {
+                    var qdrantDoc = await qdrantService.GetDocumentAsync(mongoDoc.Id);
+
+                    if (qdrantDoc == null)
+                    {
+                        result.Issues.Add($"Documento {mongoDoc.Id} não encontrado no Qdrant");
+                    }
+                    else if (qdrantDoc.Title != mongoDoc.Titulo || qdrantDoc.Content != mongoDoc.Conteudo)
+                    {
+                        result.Issues.Add($"Conteúdo divergente no documento {mongoDoc.Id}");
+                    }
+                }
+
+                result.IsValid = !result.Issues.Any();
+                return result;
+            }
+            catch (Exception ex)
+            {
+                result.Issues.Add($"Erro na validação: {ex.Message}");
+                result.IsValid = false;
+                return result;
+            }
+        }
+
+        private ITextDataService CreateMongoService()
+        {
+            // Força usar MongoDB independente da configuração
+            return _serviceProvider.GetRequiredService<ChatApi.Data.TextData>();
+        }
+
+        private ITextDataService CreateQdrantService()
+        {
+            // Força usar Qdrant independente da configuração
+            return _serviceProvider.GetRequiredService<ChatRAG.Services.TextServices.QdrantTextDataService>();
+        }
+    }
+}

Tools/PerformanceTester.cs

@@ -0,0 +1,6 @@
+namespace ChatRAG.Tools
+{
+    public class PerformanceTester
+    {
+    }
+}

appsettings.Production.json

@@ -1,15 +1,35 @@
 {
-  "DomvsDatabase": {
-    //"ConnectionString": "mongodb://192.168.0.82:30017/?directConnection=true",
-    "ConnectionString": "mongodb://localhost:27017/?directConnection=true",
-    "DatabaseName": "DomvsSites",
-    "SharepointCollectionName": "SharepointSite",
-    "ChatBotRHCollectionName": "ChatBotRHData",
-    "ClassifierCollectionName": "ClassifierData"
+  "VectorDatabase": {
+    "Provider": "Qdrant",
+    "MongoDB": {
+      "ConnectionString": "mongodb://admin:c4rn31r0@k3sw2:27017,k3ss1:27017/?authSource=admin",
+      "DatabaseName": "RAGProjects-dev-pt",
+      "TextCollectionName": "Texts",
+      "ProjectCollectionName": "Groups",
+      "UserDataName": "UserData"
+    },
+    "Qdrant": {
+      "Host": "192.168.0.100",
+      "Port": 6334,
+      "CollectionName": "texts-whats",
+      "GroupsCollectionName": "projects-whats",
+      "VectorSize": 384,
+      "Distance": "Cosine",
+      "HnswM": 16,
+      "HnswEfConstruct": 200,
+      "OnDisk": false
+    },
+    "Chroma": {
+      "Host": "localhost",
+      "Port": 8000,
+      "CollectionName": "rag_documents"
+    }
   },
-  "ChatRHSettings": {
-    "Url": "http://localhost:8070/",
-    "Create": "/CallRH"
+  "Features": {
+    "UseQdrant": true,
+    "UseHierarchicalRAG": true,
+    "UseConfidenceAwareRAG": true,
+    "EnableConfidenceCheck": false
   },
   "Logging": {
     "LogLevel": {

appsettings.json

@@ -1,11 +1,4 @@
 {
-  "DomvsDatabase": {
-    "ConnectionString": "mongodb://admin:c4rn31r0@k3sw2:27017,k3ss1:27017/?authSource=admin",
-    "DatabaseName": "RAGProjects-dev",
-    "TextCollectionName": "Texts",
-    "ProjectCollectionName": "Projects",
-    "UserDataName": "UserData"
-  },
   "Logging": {
     "LogLevel": {
       "Default": "Information",
@@ -13,7 +6,90 @@
       "Microsoft.AspNetCore.DataProtection": "None"
     }
   },
+  "VectorDatabase": {
+    "Provider": "Qdrant",
+    "MongoDB": {
+      "ConnectionString": "mongodb://admin:c4rn31r0@k3sw2:27017,k3ss1:27017/?authSource=admin",
+      "DatabaseName": "RAGProjects-dev-pt",
+      "TextCollectionName": "Texts",
+      "ProjectCollectionName": "Groups",
+      "UserDataName": "UserData"
+    },
+    "Qdrant": {
+      "Host": "192.168.0.100",
+      "Port": 6334,
+      "CollectionName": "texts-whats",
+      "GroupsCollectionName": "projects-whats",
+      "VectorSize": 384,
+      "Distance": "Cosine",
+      "HnswM": 16,
+      "HnswEfConstruct": 200,
+      "OnDisk": false
+    },
+    "Chroma": {
+      "Host": "localhost",
+      "Port": 8000,
+      "CollectionName": "rag_documents"
+    }
+  },
+  "Features": {
+    "UseQdrant": true,
+    "UseHierarchicalRAG": true,
+    "UseConfidenceAwareRAG": true,
+    "EnableConfidenceCheck": false
+  },
+
+  "ConfidenceAware": {
+    "EnableConfidenceCheck": true,
+    "UseStrictMode": true,
+    "ShowDebugInfo": false,
+    "DefaultDomain": "Servicos",
+    "Languages": {
+      "DefaultLanguage": "pt",
+      "AutoDetectLanguage": true
+    },
+    "DomainMappings": {
+      "software": "TI",
+      "sistema": "TI",
+      "funcionário": "RH",
+      "colaborador": "RH",
+      "financeiro": "Financeiro",
+      "contábil": "Financeiro",
+      "teste": "QA",
+      "qualidade": "QA"
+    }
+  },
+
+  "Confidence": {
+    "Thresholds": {
+      "overview": {
+        "MinDocuments": 2, // reduzido para chatbot
+        "MinRelevantDocuments": 1,
+        "MinOverallScore": 0.25 // mais flexível
+      },
+      "specific": {
+        "MinDocuments": 1, // bem flexível
+        "MinRelevantDocuments": 1,
+        "MinOverallScore": 0.3
+      },
+      "detailed": {
+        "MinDocuments": 1, // bem flexível
+        "MinMaxScore": 0.5,
+        "MinRelevantDocuments": 1,
+        "MinOverallScore": 0.3
+      }
+    },
+    "FallbackMessages": {
+      "pt": {
+        "NoDocuments": "Desculpe, não encontrei informações sobre esse serviço. Você pode falar com nosso atendente para mais detalhes.",
+        "Generic": "Não tenho informações suficientes sobre isso. Posso te conectar com um especialista?"
+      }
+    }
+  },
+  "PromptConfiguration": {
+    "Path": "Configuration/Prompts"
+  },
   "AllowedHosts": "*",
   "AppTenantId": "20190830-5fd4-4a72-b8fd-1c1cb35b25bc",
-  "AppClientID": "8f4248fc-ee30-4f54-8793-66edcca3fd20",
+  "AppClientID": "8f4248fc-ee30-4f54-8793-66edcca3fd20"
 }

vvijr2kk.3vs~

@@ -0,0 +1,343 @@
+using ChatApi;
+using ChatApi.Data;
+using ChatApi.Middlewares;
+using ChatApi.Services.Crypt;
+using ChatApi.Settings;
+using ChatRAG.Contracts.VectorSearch;
+using ChatRAG.Data;
+using ChatRAG.Extensions;
+using ChatRAG.Services;
+using ChatRAG.Services.Confidence;
+using ChatRAG.Services.Contracts;
+using ChatRAG.Services.PromptConfiguration;
+using ChatRAG.Services.ResponseService;
+using ChatRAG.Services.SearchVectors;
+using ChatRAG.Services.TextServices;
+using ChatRAG.Settings;
+using ChatRAG.Settings.ChatRAG.Configuration;
+using Microsoft.AspNetCore.Authentication.JwtBearer;
+using Microsoft.AspNetCore.Http.Features;
+using Microsoft.AspNetCore.Server.Kestrel.Core;
+using Microsoft.IdentityModel.JsonWebTokens;
+using Microsoft.IdentityModel.Tokens;
+using Microsoft.OpenApi.Models;
+using Microsoft.SemanticKernel;
+using System.Text;
+using static OllamaSharp.OllamaApiClient;
+using static System.Net.Mime.MediaTypeNames;
+using static System.Net.WebRequestMethods;
+
+#pragma warning disable SKEXP0010 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+
+var builder = WebApplication.CreateBuilder(args);
+
+// Add services to the container.
+
+// Adicionar serviço CORS
+builder.Services.AddCors(options =>
+{
+    options.AddPolicy("AllowSpecificOrigin",
+        builder =>
+        {
+            builder
+                .WithOrigins("http://localhost:5094") // Sua origem específica
+                .AllowAnyMethod()
+                .AllowAnyHeader()
+                .AllowCredentials();
+        });
+});
+
+builder.Services.AddControllers();
+// Learn more about configuring Swagger/OpenAPI at https://aka.ms/aspnetcore/swashbuckle
+builder.Services.AddEndpointsApiExplorer();
+builder.Services.AddSwaggerGen(c =>
+{
+    c.SwaggerDoc("v1", new OpenApiInfo { Title = "apichat", Version = "v1" });
+
+    c.AddSecurityDefinition("Bearer", new OpenApiSecurityScheme()
+    {
+        Name = "Authorization",
+        Type = SecuritySchemeType.ApiKey,
+        Scheme = "Bearer",
+        BearerFormat = "JWT",
+        In = ParameterLocation.Header,
+        Description = "JWT Authorization header using the Bearer scheme. \r\n\r\n Enter 'Bearer'[space] and then your token in the text input below.\r\n\r\nExample: \"Bearer 12345abcdef\"",
+    });
+    c.AddSecurityRequirement(new OpenApiSecurityRequirement
+    {
+        {
+                new OpenApiSecurityScheme
+                {
+                    Reference = new OpenApiReference
+                    {
+                        Type = ReferenceType.SecurityScheme,
+                        Id = "Bearer"
+                    }
+                },
+                new string[] {}
+        }
+    });
+});
+
+builder.Services.Configure<ConfidenceSettings>(
+builder.Configuration.GetSection("Confidence"));
+
+builder.Services.Configure<ConfidenceAwareSettings>(
+builder.Configuration.GetSection("ConfidenceAware"));
+
+
+//builder.Services.AddScoped<IVectorSearchService, MongoVectorSearchService>();
+builder.Services.AddScoped<QdrantVectorSearchService>();
+builder.Services.AddScoped<MongoVectorSearchService>();
+builder.Services.AddScoped<ChromaVectorSearchService>();
+
+builder.Services.AddVectorDatabase(builder.Configuration);
+
+builder.Services.AddScoped<IVectorSearchService>(provider =>
+{
+    var useQdrant = builder.Configuration["Features:UseQdrant"] == "true";
+    var factory = provider.GetRequiredService<IVectorDatabaseFactory>();
+    return factory.CreateVectorSearchService();
+});
+
+builder.Services.AddScoped<QdrantProjectDataRepository>();
+builder.Services.AddScoped<MongoProjectDataRepository>();
+builder.Services.AddScoped<ChromaProjectDataRepository>();
+
+builder.Services.AddScoped<IProjectDataRepository>(provider =>
+{
+    var database = builder.Configuration["VectorDatabase:Provider"];
+    if (string.IsNullOrEmpty(database))
+    {
+        throw new InvalidOperationException("VectorDatabase:Provider is not configured.");
+    }
+    else if (database.Equals("Qdrant", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<QdrantProjectDataRepository>();
+    }
+    else if (database.Equals("MongoDB", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<MongoProjectDataRepository>();
+    }
+    else if (database.Equals("Chroma", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<ChromaProjectDataRepository>();
+    }
+    return provider.GetRequiredService<MongoProjectDataRepository>();
+});
+
+builder.Services.AddScoped<QdrantTextDataService>();
+builder.Services.AddScoped<MongoTextDataService>();
+builder.Services.AddScoped<ChromaTextDataService>();
+
+builder.Services.AddScoped<ITextDataService>(provider =>
+{
+    var database = builder.Configuration["VectorDatabase:Provider"];
+    if (string.IsNullOrEmpty(database))
+    {
+        throw new InvalidOperationException("VectorDatabase:Provider is not configured.");
+    }
+    else if (database.Equals("Qdrant", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<QdrantTextDataService>();
+    }
+    else if (database.Equals("MongoDB", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<MongoTextDataService>();
+    }
+    else if (database.Equals("Chroma", StringComparison.OrdinalIgnoreCase))
+    {
+        return provider.GetRequiredService<ChromaTextDataService>();
+    }
+    return provider.GetRequiredService<MongoTextDataService>();
+});
+
+builder.Services.AddSingleton<ChatHistoryService>();
+builder.Services.AddScoped<TextDataRepository>();
+builder.Services.AddSingleton<TextFilter>();
+
+//builder.Services.AddScoped<IResponseService, ResponseRAGService>();
+builder.Services.AddScoped<ResponseRAGService>();
+builder.Services.AddScoped<HierarchicalRAGService>();
+
+builder.Services.AddScoped<IResponseService>(provider =>
+{
+    var configuration = provider.GetService<IConfiguration>();
+    var useHierarchical = configuration?.GetValue<bool>("Features:UseHierarchicalRAG") ?? false;
+    var useConfidence = configuration?.GetValue<bool>("Features:UseConfidenceAwareRAG") ?? false;
+
+    return useConfidence && useHierarchical
+        ? provider.GetRequiredService<ConfidenceAwareRAGService>()
+        : useHierarchical        
+        ? provider.GetRequiredService<HierarchicalRAGService>()
+        : provider.GetRequiredService<ResponseRAGService>();
+});
+
+builder.Services.AddTransient<UserDataRepository>();
+builder.Services.AddTransient<TextData>();
+builder.Services.AddSingleton<CryptUtil>();
+
+// Registrar serviços de confiança
+builder.Services.AddScoped<ConfidenceVerifier>();
+builder.Services.AddSingleton<PromptConfigurationService>();
+
+// Registrar ConfidenceAwareRAGService
+builder.Services.AddScoped<ConfidenceAwareRAGService>();
+
+//builder.Services.AddOllamaChatCompletion("phi3.5", new Uri("http://localhost:11435"));
+//builder.Services.AddOllamaChatCompletion("tinydolphin", new Uri("http://localhost:11435"));
+//var apiClient = new OllamaApiClient(new Uri("http://localhost:11435"), "tinydolphin");
+
+//Olllama 
+//Desktop
+var key = "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";
+//uilder.Services.AddOllamaChatCompletion("llama3.2", new Uri("http://localhost:11434"));
+//var model = "llama-3.3-70b-versatile";
+var model = "llama-3.1-8b-instant";
+//var model = "meta-llama/llama-guard-4-12b";
+//var url = "https://api.groq.com/openai/v1/chat/completions"; // Adicione o /v1/openai
+var url = "https://api.groq.com/openai/v1"; 
+builder.Services.AddOpenAIChatCompletion(model, new Uri(url), key);
+
+//Notebook
+//var model = "meta-llama/Llama-3.2-3B-Instruct";
+//var url = "https://api.deepinfra.com/v1/openai"; // Adicione o /v1/openai
+//builder.Services.AddOpenAIChatCompletion(model, new Uri(url), "HedaR4yPrp9N2XSHfwdZjpZvPIxejPFK");
+
+//builder.Services.AddOllamaChatCompletion("llama3.2:3b", new Uri("http://localhost:11435"));
+//builder.Services.AddOllamaChatCompletion("llama3.2:1b", new Uri("http://localhost:11435"));
+
+
+//builder.Services.AddOllamaChatCompletion("tinydolphin", new Uri("http://localhost:11435"));
+//builder.Services.AddOllamaChatCompletion("tinyllama", new Uri("http://localhost:11435"));
+//builder.Services.AddOllamaChatCompletion("starling-lm", new Uri("http://localhost:11435"));
+
+//ServerSpace - GPT Service
+//builder.Services.AddOpenAIChatCompletion("openchat-3.5-0106", new Uri("https://gpt.serverspace.com.br/v1/chat/completions"), "tIAXVf3AkCkkpSX+PjFvktfEeSPyA1ZYam50UO3ye/qmxVZX6PIXstmJsLZXkQ39C33onFD/81mdxvhbGHm7tQ==");
+
+//Ollama local server (scorpion)
+//builder.Services.AddOllamaChatCompletion("llama3.1:latest", new Uri("http://192.168.0.150:11434"));
+
+//builder.Services.AddOllamaTextEmbeddingGeneration("all-minilm", new Uri("http://192.168.0.150:11434"));
+
+//Desktop
+//builder.Services.AddOllamaTextEmbeddingGeneration("all-minilm", new Uri("http://localhost:11434"));
+//Notebook
+builder.Services.AddOllamaTextEmbeddingGeneration("all-minilm", new Uri("http://localhost:11435"));
+
+
+//builder.Services.AddOllamaChatCompletion("phi3.5", new Uri("http://localhost:11435"));
+//builder.Services.AddOpenAIChatCompletion("gpt-4o-mini", "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");
+//builder.Services.AddGoogleAIGeminiChatCompletion("gemini-1.5-flash-latest", "AIzaSyDKBMX5yW77vxJFVJVE-5VLxlQRxCepck8");
+
+//Anthropic / Claude
+//builder.Services.AddAnthropicChatCompletion(
+//    modelId: "claude-3-5-sonnet-latest",  // ou outro modelo Claude desejado
+//    apiKey: "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"
+//);
+
+
+builder.Services.AddKernel();
+
+//builder.Services.AddKernel()
+//    .AddOllamaChatCompletion("phi3", new Uri("http://localhost:11435"))
+//    .AddOllamaTextEmbeddingGeneration()
+//    .Build(); 
+
+//builder.Services.AddOllamaChatCompletion("phi3.5", new Uri("http://192.168.0.150:11436"));
+
+builder.Services.AddHttpClient();
+
+var tenantId = builder.Configuration.GetSection("AppTenantId");
+var clientId = builder.Configuration.GetSection("AppClientID");
+
+//builder.Services.AddAuthentication(JwtBearerDefaults.AuthenticationScheme)
+//    .AddMicrosoftIdentityWebApi(builder.Configuration.GetSection("AzureAd"));
+
+builder.Services.AddControllers();
+
+//builder.Services.AddAuthentication(options =>
+//    {
+//        options.DefaultScheme = JwtBearerDefaults.AuthenticationScheme;
+//        options.DefaultChallengeScheme = JwtBearerDefaults.AuthenticationScheme;
+//    })
+//    .AddJwtBearer(options =>
+//    {
+//        // Configurações anteriores...
+
+//        // Eventos para log e tratamento de erros
+//        options.Events = new JwtBearerEvents
+//        {
+//            OnAuthenticationFailed = context =>
+//            {
+//                // Log de erros de autenticação
+//                Console.WriteLine($"Erro de autenticação: {context.Exception.Message}");
+//                return Task.CompletedTask;
+//            },
+//            OnTokenValidated = context =>
+//            {
+//                // Validações adicionais se necessário
+//                return Task.CompletedTask;
+//            }
+//        };
+//    });
+
+builder.Services.AddSingleton<IConfigurationManager>(builder.Configuration);
+
+builder.Services.Configure<IISServerOptions>(options =>
+{
+    options.MaxRequestBodySize = int.MaxValue;
+});
+
+builder.Services.Configure<KestrelServerOptions>(options =>
+{
+    options.Limits.MaxRequestBodySize = int.MaxValue;
+});
+
+builder.Services.Configure<FormOptions>(options =>
+{
+    options.ValueLengthLimit = int.MaxValue;
+    options.MultipartBodyLengthLimit = int.MaxValue;
+    options.MultipartHeadersLengthLimit = int.MaxValue;
+});
+
+var app = builder.Build();
+
+
+
+// Configure the HTTP request pipeline.
+if (app.Environment.IsDevelopment())
+{
+    app.UseSwagger();
+    app.UseSwaggerUI();
+    app.UseDeveloperExceptionPage(); // Isso mostra erros detalhados
+}
+
+//app.UseHttpsRedirection();
+
+app.MapControllers();
+
+app.Use(async (context, next) =>
+{
+    var cookieOpt = new CookieOptions()
+    {
+        Path = "/",
+        Expires = DateTimeOffset.UtcNow.AddDays(1),
+        IsEssential = true,
+        HttpOnly = false,
+        Secure = false,
+    };
+
+    await next();
+});
+
+app.UseMiddleware<ErrorHandlingMiddleware>();
+
+app.UseCors("AllowSpecificOrigin");
+
+app.UseAuthentication();
+app.UseAuthorization();
+
+app.Run();
+
+#pragma warning restore SKEXP0010 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.