feat:qdrant

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_SelectedScaffolderID>MvcControllerEmptyScaffolder</Controller_SelectedScaffolderID>
-    <Controller_SelectedScaffolderCategoryPath>root/Common/Api</Controller_SelectedScaffolderCategoryPath>
+    <Controller_SelectedScaffolderCategoryPath>root/Common/MVC/Controller</Controller_SelectedScaffolderCategoryPath>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">
     <DebuggerFlavor>ProjectDebugger</DebuggerFlavor>

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.
 
@@ -21,23 +22,23 @@ namespace ChatApi.Controllers
         private readonly TextFilter _textFilter;
         private readonly UserDataRepository _userDataRepository;
         private readonly ProjectDataRepository _projectDataRepository;        
-        private readonly TextData _textData;
+        private readonly ITextDataService _textDataService;
         private readonly IHttpClientFactory _httpClientFactory;
 
         public ChatController(
             ILogger<ChatController> logger,
             IResponseService responseService,
             UserDataRepository userDataRepository,
-            TextData textData,
+            ITextDataService textDataService,
             ProjectDataRepository projectDataRepository,
             IHttpClientFactory httpClientFactory)
         {
             _logger = logger;
             _responseService = responseService;
             _userDataRepository = userDataRepository;
-            _textData = textData;
+            _textDataService = textDataService;
             _projectDataRepository = projectDataRepository;
-            this._httpClientFactory = httpClientFactory;
+            _httpClientFactory = httpClientFactory;
         }
 
         [HttpPost]
@@ -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

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/ProjectDataRepository.cs

@@ -1,5 +1,6 @@
 using ChatApi;
 using ChatRAG.Models;
+using ChatRAG.Settings.ChatRAG.Configuration;
 using Microsoft.Extensions.Options;
 using MongoDB.Driver;
 
@@ -10,16 +11,16 @@ namespace ChatRAG.Data
         private readonly IMongoCollection<Project> _textsCollection;
 
         public ProjectDataRepository(
-            IOptions<DomvsDatabaseSettings> databaseSettings)
+            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/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;
@@ -8,7 +9,7 @@ using System.Text;
 
 namespace ChatApi.Data
 {
-    public class TextData
+    public class TextData : ITextDataService
     {
         private readonly ITextEmbeddingGenerationService _textEmbeddingGenerationService;
         private readonly TextDataRepository _textDataService;
@@ -19,6 +20,12 @@ namespace ChatApi.Data
             _textDataService = textDataService;
         }
 
+        public string ProviderName => "MongoDB";
+
+        // ========================================
+        // MÉTODOS ORIGINAIS (já implementados)
+        // ========================================
+
         public async Task SalvarTextoComEmbeddingNoMongoDB(string textoCompleto, string projectId)
         {
             var textoArray = new List<string>();
@@ -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)
@@ -73,6 +80,7 @@ namespace ChatApi.Data
             {
                 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.

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() =>

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 +3,14 @@ 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.Contracts;
 using ChatRAG.Services.ResponseService;
+using ChatRAG.Services.SearchVectors;
+using ChatRAG.Settings.ChatRAG.Configuration;
 using Microsoft.AspNetCore.Authentication.JwtBearer;
 using Microsoft.AspNetCore.Http.Features;
 using Microsoft.AspNetCore.Server.Kestrel.Core;
@@ -16,6 +21,7 @@ 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.
 
@@ -69,12 +75,20 @@ builder.Services.AddSwaggerGen(c =>
     });
 });
 
-builder.Services.Configure<DomvsDatabaseSettings>(
-builder.Configuration.GetSection("DomvsDatabase"));
-
 builder.Services.Configure<ChatRHSettings>(
 builder.Configuration.GetSection("ChatRHSettings"));
 
+builder.Services.AddScoped<IVectorSearchService, MongoVectorSearchService>();
+
+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.AddSingleton<ChatHistoryService>();
 builder.Services.AddScoped<TextDataRepository>();
 builder.Services.AddScoped<ProjectDataRepository>();
@@ -90,7 +104,16 @@ builder.Services.AddSingleton<CryptUtil>();
 //var apiClient = new OllamaApiClient(new Uri("http://localhost:11435"), "tinydolphin");
 
 //Olllama 
-builder.Services.AddOllamaChatCompletion("llama3.2", new Uri("http://localhost:11434"));
+//Desktop
+//builder.Services.AddOllamaChatCompletion("llama3.2", new Uri("http://localhost:11434"));
+//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 +126,13 @@ 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/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/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.
@@ -19,6 +22,7 @@ namespace ChatRAG.Services.ResponseService
         private readonly TextDataRepository _textDataRepository;
         private readonly ProjectDataRepository _projectDataRepository;
         private readonly IChatCompletionService _chatCompletionService;
+        private readonly IVectorSearchService _vectorSearchService;
 
         public ResponseRAGService(
             ChatHistoryService chatHistoryService,
@@ -26,7 +30,9 @@ namespace ChatRAG.Services.ResponseService
             TextFilter textFilter,
             TextDataRepository textDataRepository,
             ProjectDataRepository projectDataRepository,
-            IChatCompletionService chatCompletionService)
+            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 searchStrategy = await ClassificarEstrategiaDeBusca(question, language);
-            //var resposta = await BuscarTopTextosRelacionados(question, projectId);
-            var resposta = await BuscarTopTextosRelacionadosDinamico(question, projectId);
 
-            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/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 +1,527 @@
+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;
+
+#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 bool _collectionInitialized = false;
+
+        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;
+
+            try
+            {
+                var collectionExists = await _client.CollectionExistsAsync(_settings.CollectionName);
+
+                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 opcionais
+                    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
+                    );
+
+                    _logger.LogInformation("✅ Collection {CollectionName} criada", _settings.CollectionName);
+                }
+
+                _collectionInitialized = true;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao inicializar collection {CollectionName}", _settings.CollectionName);
+                throw;
+            }
+        }
+
+        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: true
+                );
+
+                return searchResult.Select(point => 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)
+                }).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 = new Dictionary<string, Value>
+                {
+                    ["title"] = title,
+                    ["content"] = content,
+                    ["project_id"] = projectId,
+                    ["created_at"] = DateTime.UtcNow.ToString("O"),
+                    ["updated_at"] = DateTime.UtcNow.ToString("O")
+                };
+
+                if (metadata?.Any() == true)
+                {
+                    foreach (var kvp in metadata)
+                    {
+                        payload[$"meta_{kvp.Key}"] = ConvertToValue(kvp.Value);
+                    }
+                }
+
+                var point = new PointStruct
+                {
+                    Id = new PointId { Uuid = id },  
+                    Vectors = vector,  
+                    Payload = { payload }
+                };
+
+                await _client.UpsertAsync(
+                    collectionName: _settings.CollectionName,
+                    points: new[] { point }
+                );
+
+                _logger.LogDebug("Documento {Id} adicionado ao Qdrant", id);
+                return id;
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao adicionar documento no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task UpdateDocumentAsync(
+            string id,
+            string title,
+            string content,
+            string projectId,
+            double[] embedding,
+            Dictionary<string, object>? metadata = null)
+        {
+            await EnsureCollectionExistsAsync();
+
+            try
+            {
+                var vector = embedding.Select(x => (float)x).ToArray();
+
+                var payload = new Dictionary<string, Value>
+                {
+                    ["title"] = title,
+                    ["content"] = content,
+                    ["project_id"] = projectId,
+                    ["updated_at"] = DateTime.UtcNow.ToString("O")
+                };
+
+                if (metadata?.Any() == true)
+                {
+                    foreach (var kvp in metadata)
+                    {
+                        payload[$"meta_{kvp.Key}"] = ConvertToValue(kvp.Value);
+                    }
+                }
+
+                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
+            {
+                var result = await GetDocumentAsync(id);
+                return result != null;
+            }
+            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();
+                if (point == null) return null;
+
+                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)
+                };
+            }
+            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 results = await _client.ScrollAsync(
+                    collectionName: _settings.CollectionName,
+                    filter: filter,
+                    limit: 10000,
+                    payloadSelector: true,
+                    vectorsSelector: true
+                );
+
+                return results.Result.Select(point => 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)
+                }).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
+                };
+            }
+        }
+
+        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()
+        {
+            _client?.Dispose();
+        }
+    }
+}
+
+#pragma warning restore SKEXP0001

Services/SearchVectors/VectorDatabaseFactory.cs

@@ -0,0 +1,114 @@
+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
+{
+    /// <summary>
+    /// Factory principal que cria implementações baseadas na configuração
+    /// </summary>
+    /// <summary>
+    /// Factory principal que cria implementações baseadas na configuração
+    /// </summary>
+    public class VectorDatabaseFactory : IVectorDatabaseFactory
+    {
+        private readonly VectorDatabaseSettings _settings;
+        private readonly IServiceProvider _serviceProvider;
+        private readonly ILogger<VectorDatabaseFactory> _logger;
+
+        public VectorDatabaseFactory(
+            IOptions<VectorDatabaseSettings> settings,
+            IServiceProvider serviceProvider,
+            ILogger<VectorDatabaseFactory> logger)
+        {
+            _settings = settings.Value;
+            _serviceProvider = serviceProvider;
+            _logger = logger;
+
+            // Valida configurações na inicialização
+            ValidateSettings();
+        }
+
+        public string GetActiveProvider() => _settings.Provider;
+        public VectorDatabaseSettings GetSettings() => _settings;
+
+        public IVectorSearchService CreateVectorSearchService()
+        {
+            _logger.LogInformation("Criando VectorSearchService para provider: {Provider}", _settings.Provider);
+
+            return _settings.Provider.ToLower() switch
+            {
+                "qdrant" => GetService<ChatRAG.Services.SearchVectors.QdrantVectorSearchService>(),
+                "mongodb" => GetService<ChatRAG.Services.SearchVectors.MongoVectorSearchService>(),
+                _ => throw new ArgumentException($"Provider de VectorSearch não suportado: {_settings.Provider}")
+            };
+        }
+
+        public ITextDataService CreateTextDataService()
+        {
+            _logger.LogInformation("Criando TextDataService para provider: {Provider}", _settings.Provider);
+
+            return _settings.Provider.ToLower() switch
+            {
+                // ✅ CORRIGIDO: Usa os namespaces corretos
+                "qdrant" => GetService<ChatRAG.Services.TextServices.QdrantTextDataService>(),
+                "mongodb" => GetService<ChatApi.Data.TextData>(), // Sua classe atual!
+                _ => throw new ArgumentException($"Provider de TextData não suportado: {_settings.Provider}")
+            };
+        }
+
+        public IResponseService CreateResponseService()
+        {
+            _logger.LogInformation("Criando ResponseService para provider: {Provider}", _settings.Provider);
+
+            return _settings.Provider.ToLower() switch
+            {
+                // ✅ CORRIGIDO: Usa os namespaces corretos
+                "qdrant" => GetService<ChatRAG.Services.ResponseService.QdrantResponseService>(),
+                "mongodb" => GetService<ChatRAG.Services.ResponseService.ResponseRAGService>(), // Sua classe atual!
+                _ => throw new ArgumentException($"Provider de Response não suportado: {_settings.Provider}")
+            };
+        }
+
+        // ========================================
+        // MÉTODOS AUXILIARES
+        // ========================================
+
+        private T GetService<T>() where T : class
+        {
+            try
+            {
+                var service = _serviceProvider.GetRequiredService<T>();
+                _logger.LogDebug("Serviço {ServiceType} criado com sucesso", typeof(T).Name);
+                return service;
+            }
+            catch (InvalidOperationException ex)
+            {
+                _logger.LogError(ex, "Erro ao criar serviço {ServiceType} para provider {Provider}",
+                    typeof(T).Name, _settings.Provider);
+
+                throw new InvalidOperationException(
+                    $"Serviço {typeof(T).Name} não está registrado para provider {_settings.Provider}. " +
+                    $"Certifique-se de chamar services.Add{_settings.Provider}Provider() no DI.", ex);
+            }
+        }
+
+        private void ValidateSettings()
+        {
+            if (!_settings.IsValid())
+            {
+                var errors = _settings.GetValidationErrors();
+                var errorMessage = $"Configurações inválidas para VectorDatabase: {string.Join(", ", errors)}";
+
+                _logger.LogError(errorMessage);
+                throw new InvalidOperationException(errorMessage);
+            }
+
+            _logger.LogInformation("Configurações validadas com sucesso para provider: {Provider}", _settings.Provider);
+        }
+    }
+}

Services/TextServices/QdrantTextDataService.cs

@@ -0,0 +1,523 @@
+#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;
+
+namespace ChatRAG.Services.TextServices
+{
+    public class QdrantTextDataService : ITextDataService
+    {
+        private readonly IVectorSearchService _vectorSearchService;
+        private readonly ITextEmbeddingGenerationService _embeddingService;
+        private readonly ILogger<QdrantTextDataService> _logger;
+
+        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
+                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 Qdrant", titulo);
+                }
+                else
+                {
+                    // Atualiza documento existente
+                    await _vectorSearchService.UpdateDocumentAsync(id, titulo, texto, projectId, embeddingArray);
+                    _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 = 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 Qdrant", textoArray.Count);
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao processar texto completo no Qdrant");
+                throw;
+            }
+        }
+
+        public async Task<IEnumerable<TextoComEmbedding>> GetAll()
+        {
+            try
+            {
+                // Busca todos os projetos e depois todos os documentos
+                var allDocuments = new List<VectorSearchResult>();
+
+                // Como Qdrant 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 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 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 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 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 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
+        // ========================================
+
+        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 Qdrant",
+                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 Qdrant", 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"] = "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
+                };
+
+                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
+        // ========================================
+
+        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>()
+            };
+        }
+
+        private async Task<List<string>> GetAllProjectIds()
+        {
+            try
+            {
+                // Esta é uma operação custosa no Qdrant
+                // 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[1536]; // Assumindo embeddings OpenAI
+                var allResults = await _vectorSearchService.SearchSimilarAsync(
+                    dummyVector,
+                    projectId: null,
+                    threshold: 0.0,
+                    limit: 10000);
+
+                return allResults
+                    .Select(r => r.ProjectId)
+                    .Where(pid => !string.IsNullOrEmpty(pid))
+                    .Distinct()
+                    .ToList();
+            }
+            catch (Exception ex)
+            {
+                _logger.LogError(ex, "Erro ao recuperar IDs de projetos do Qdrant");
+                return new List<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/VectorDatabaseSettings.cs

@@ -0,0 +1,494 @@
+namespace ChatRAG.Settings
+{
+    // ============================================================================
+    // 📁 Configuration/VectorDatabaseSettings.cs  
+    // Settings unificados para todos os providers (MongoDB, Qdrant, etc.)
+    // ============================================================================
+
+    namespace ChatRAG.Configuration
+    {
+        /// <summary>
+        /// Configurações principais do sistema de Vector Database
+        /// </summary>
+        public class VectorDatabaseSettings
+        {
+            /// <summary>
+            /// Provider ativo (MongoDB, Qdrant, Pinecone, etc.)
+            /// </summary>
+            public string Provider { get; set; } = "MongoDB";
+
+            /// <summary>
+            /// Configurações específicas do MongoDB
+            /// </summary>
+            public MongoDbSettings MongoDB { get; set; } = new();
+
+            /// <summary>
+            /// Configurações específicas do Qdrant
+            /// </summary>
+            public QdrantSettings Qdrant { get; set; } = new();
+
+            /// <summary>
+            /// Configurações globais de embedding
+            /// </summary>
+            public EmbeddingSettings Embedding { get; set; } = new();
+
+            /// <summary>
+            /// Configurações de performance e cache
+            /// </summary>
+            public PerformanceSettings Performance { get; set; } = new();
+
+            /// <summary>
+            /// Configurações de logging e monitoramento
+            /// </summary>
+            public MonitoringSettings Monitoring { get; set; } = new();
+
+            /// <summary>
+            /// Valida se as configurações estão corretas
+            /// </summary>
+            public bool IsValid()
+            {
+                if (string.IsNullOrWhiteSpace(Provider))
+                    return false;
+
+                return Provider.ToLower() switch
+                {
+                    "mongodb" => MongoDB.IsValid(),
+                    "qdrant" => Qdrant.IsValid(),
+                    _ => false
+                };
+            }
+
+            /// <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;
+            }
+        }
+
+        /// <summary>
+        /// Configurações específicas do MongoDB
+        /// </summary>
+        public class MongoDbSettings
+        {
+            /// <summary>
+            /// String de conexão do MongoDB
+            /// </summary>
+            public string ConnectionString { get; set; } = string.Empty;
+
+            /// <summary>
+            /// Nome do banco de dados
+            /// </summary>
+            public string DatabaseName { get; set; } = string.Empty;
+
+            /// <summary>
+            /// Nome da coleção de textos/documentos
+            /// </summary>
+            public string TextCollectionName { get; set; } = "texts";
+
+            /// <summary>
+            /// Nome da coleção de projetos
+            /// </summary>
+            public string ProjectCollectionName { get; set; } = "projects";
+
+            /// <summary>
+            /// Nome da coleção de dados de usuário
+            /// </summary>
+            public string UserDataName { get; set; } = "users";
+
+            /// <summary>
+            /// Timeout de conexão em segundos
+            /// </summary>
+            public int ConnectionTimeoutSeconds { get; set; } = 30;
+
+            /// <summary>
+            /// Timeout de operação em segundos
+            /// </summary>
+            public int OperationTimeoutSeconds { get; set; } = 60;
+
+            /// <summary>
+            /// Tamanho máximo do pool de conexões
+            /// </summary>
+            public int MaxConnectionPoolSize { get; set; } = 100;
+
+            /// <summary>
+            /// Habilitar índices de busca vetorial
+            /// </summary>
+            public bool EnableVectorSearch { get; set; } = true;
+
+            /// <summary>
+            /// Configurações específicas do Atlas Search
+            /// </summary>
+            public MongoAtlasSearchSettings AtlasSearch { get; set; } = new();
+
+            public bool IsValid()
+            {
+                return !string.IsNullOrWhiteSpace(ConnectionString) &&
+                       !string.IsNullOrWhiteSpace(DatabaseName) &&
+                       !string.IsNullOrWhiteSpace(TextCollectionName);
+            }
+
+            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;
+            }
+        }
+
+        /// <summary>
+        /// Configurações do MongoDB Atlas Search
+        /// </summary>
+        public class MongoAtlasSearchSettings
+        {
+            /// <summary>
+            /// Nome do índice de busca vetorial
+            /// </summary>
+            public string VectorIndexName { get; set; } = "vector_index";
+
+            /// <summary>
+            /// Número de candidatos para busca aproximada
+            /// </summary>
+            public int NumCandidates { get; set; } = 200;
+
+            /// <summary>
+            /// Limite de resultados do Atlas Search
+            /// </summary>
+            public int SearchLimit { get; set; } = 100;
+        }
+
+        /// <summary>
+        /// Configurações específicas do Qdrant
+        /// </summary>
+        public class QdrantSettings
+        {
+            /// <summary>
+            /// Host do servidor Qdrant
+            /// </summary>
+            public string Host { get; set; } = "localhost";
+
+            /// <summary>
+            /// Porta do servidor Qdrant (REST API)
+            /// </summary>
+            public int Port { get; set; } = 6333;
+
+            /// <summary>
+            /// Porta gRPC (opcional, para performance)
+            /// </summary>
+            public int? GrpcPort { get; set; } = 6334;
+
+            /// <summary>
+            /// Chave de API (se autenticação estiver habilitada)
+            /// </summary>
+            public string? ApiKey { get; set; }
+
+            /// <summary>
+            /// Usar TLS/SSL
+            /// </summary>
+            public bool UseTls { get; set; } = false;
+
+            /// <summary>
+            /// Nome da coleção principal
+            /// </summary>
+            public string CollectionName { get; set; } = "documents";
+
+            /// <summary>
+            /// Tamanho do vetor de embedding
+            /// </summary>
+            public int VectorSize { get; set; } = 1536; // OpenAI embedding size
+
+            /// <summary>
+            /// Métrica de distância (Cosine, Euclid, Dot, Manhattan)
+            /// </summary>
+            public string Distance { get; set; } = "Cosine";
+
+            // ========================================
+            // CONFIGURAÇÕES DE PERFORMANCE
+            // ========================================
+
+            /// <summary>
+            /// Parâmetro M do algoritmo HNSW (conectividade)
+            /// Valores típicos: 16-48, maior = melhor recall, mais memória
+            /// </summary>
+            public int HnswM { get; set; } = 16;
+
+            /// <summary>
+            /// Parâmetro ef_construct do HNSW (construção do índice)
+            /// Valores típicos: 100-800, maior = melhor qualidade, mais lento
+            /// </summary>
+            public int HnswEfConstruct { get; set; } = 200;
+
+            /// <summary>
+            /// Parâmetro ef do HNSW (busca)
+            /// Valores típicos: igual ou maior que o número de resultados desejados
+            /// </summary>
+            public int HnswEf { get; set; } = 128;
+
+            /// <summary>
+            /// Armazenar vetores em disco (economiza RAM)
+            /// </summary>
+            public bool OnDisk { get; set; } = false;
+
+            /// <summary>
+            /// Fator de replicação (para clusters)
+            /// </summary>
+            public int ReplicationFactor { get; set; } = 1;
+
+            /// <summary>
+            /// Número de shards (para distribuição)
+            /// </summary>
+            public int ShardNumber { get; set; } = 1;
+
+            /// <summary>
+            /// Usar quantização para reduzir uso de memória
+            /// </summary>
+            public bool UseQuantization { get; set; } = false;
+
+            /// <summary>
+            /// Configurações de quantização
+            /// </summary>
+            public QuantizationSettings Quantization { get; set; } = new();
+
+            /// <summary>
+            /// Timeout de conexão em segundos
+            /// </summary>
+            public int ConnectionTimeoutSeconds { get; set; } = 30;
+
+            /// <summary>
+            /// Timeout de operação em segundos
+            /// </summary>
+            public int OperationTimeoutSeconds { get; set; } = 60;
+
+            /// <summary>
+            /// URL completa calculada
+            /// </summary>
+            public string GetConnectionUrl()
+            {
+                var protocol = UseTls ? "https" : "http";
+                return $"{protocol}://{Host}:{Port}";
+            }
+
+            public bool IsValid()
+            {
+                return !string.IsNullOrWhiteSpace(Host) &&
+                       Port > 0 &&
+                       !string.IsNullOrWhiteSpace(CollectionName) &&
+                       VectorSize > 0;
+            }
+
+            public List<string> GetValidationErrors()
+            {
+                var errors = new List<string>();
+
+                if (string.IsNullOrWhiteSpace(Host))
+                    errors.Add("Qdrant Host é obrigatório");
+
+                if (Port <= 0)
+                    errors.Add("Qdrant Port deve ser maior que 0");
+
+                if (string.IsNullOrWhiteSpace(CollectionName))
+                    errors.Add("Qdrant CollectionName é obrigatório");
+
+                if (VectorSize <= 0)
+                    errors.Add("Qdrant VectorSize deve ser maior que 0");
+
+                if (HnswM <= 0)
+                    errors.Add("Qdrant HnswM deve ser maior que 0");
+
+                if (HnswEfConstruct <= 0)
+                    errors.Add("Qdrant HnswEfConstruct deve ser maior que 0");
+
+                var validDistances = new[] { "Cosine", "Euclid", "Dot", "Manhattan" };
+                if (!validDistances.Contains(Distance))
+                    errors.Add($"Qdrant Distance deve ser um de: {string.Join(", ", validDistances)}");
+
+                return errors;
+            }
+        }
+
+        /// <summary>
+        /// Configurações de quantização para Qdrant
+        /// </summary>
+        public class QuantizationSettings
+        {
+            /// <summary>
+            /// Tipo de quantização (scalar, product, binary)
+            /// </summary>
+            public string Type { get; set; } = "scalar";
+
+            /// <summary>
+            /// Quantil para quantização scalar
+            /// </summary>
+            public double Quantile { get; set; } = 0.99;
+
+            /// <summary>
+            /// Sempre usar RAM para quantização
+            /// </summary>
+            public bool AlwaysRam { get; set; } = false;
+        }
+
+        /// <summary>
+        /// Configurações globais de embedding
+        /// </summary>
+        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;
+            }
+        }
+
+        /// <summary>
+        /// Configurações de performance e otimização
+        /// </summary>
+        public class PerformanceSettings
+        {
+            /// <summary>
+            /// Habilitar paralelização em operações de lote
+            /// </summary>
+            public bool EnableParallelization { get; set; } = true;
+
+            /// <summary>
+            /// Número máximo de threads paralelas
+            /// </summary>
+            public int MaxParallelism { get; set; } = Environment.ProcessorCount;
+
+            /// <summary>
+            /// Tamanho do batch para operações em lote
+            /// </summary>
+            public int BatchSize { get; set; } = 100;
+
+            /// <summary>
+            /// Timeout padrão para operações em segundos
+            /// </summary>
+            public int DefaultTimeoutSeconds { get; set; } = 30;
+
+            /// <summary>
+            /// Habilitar retry automático
+            /// </summary>
+            public bool EnableRetry { get; set; } = true;
+
+            /// <summary>
+            /// Número máximo de tentativas
+            /// </summary>
+            public int MaxRetryAttempts { get; set; } = 3;
+
+            /// <summary>
+            /// Delay entre tentativas em segundos
+            /// </summary>
+            public int RetryDelaySeconds { get; set; } = 2;
+        }
+
+        /// <summary>
+        /// Configurações de monitoramento e logging
+        /// </summary>
+        public class MonitoringSettings
+        {
+            /// <summary>
+            /// Habilitar logging detalhado
+            /// </summary>
+            public bool EnableDetailedLogging { get; set; } = false;
+
+            /// <summary>
+            /// Logar tempos de operação
+            /// </summary>
+            public bool LogOperationTimes { get; set; } = true;
+
+            /// <summary>
+            /// Threshold para log de operações lentas (ms)
+            /// </summary>
+            public int SlowOperationThresholdMs { get; set; } = 1000;
+
+            /// <summary>
+            /// Habilitar métricas de performance
+            /// </summary>
+            public bool EnableMetrics { get; set; } = true;
+
+            /// <summary>
+            /// Intervalo de coleta de métricas em segundos
+            /// </summary>
+            public int MetricsIntervalSeconds { get; set; } = 60;
+
+            /// <summary>
+            /// Habilitar health checks
+            /// </summary>
+            public bool EnableHealthChecks { get; set; } = true;
+
+            /// <summary>
+            /// Intervalo de health check em segundos
+            /// </summary>
+            public int HealthCheckIntervalSeconds { get; set; } = 30;
+        }
+    }
+}

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;
+        }
+    }
+}

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.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 +6,30 @@
       "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": "localhost",
+      "Port": 6334,
+      "CollectionName": "texts",
+      "VectorSize": 384,
+      "Distance": "Cosine",
+      "HnswM": 16,
+      "HnswEfConstruct": 200,
+      "OnDisk": false
+    }
+  },
+  "Features": {
+    "UseQdrant": true
+  },
   "AllowedHosts": "*",
   "AppTenantId": "20190830-5fd4-4a72-b8fd-1c1cb35b25bc",
-  "AppClientID": "8f4248fc-ee30-4f54-8793-66edcca3fd20",
+  "AppClientID": "8f4248fc-ee30-4f54-8793-66edcca3fd20"
 }