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>();
-                PromptEn(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;
@@ -62,13 +67,21 @@ namespace ChatApi
         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. Consider the project context and requirements above to generate accurate and relevant information."));
+            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.System, "If you have a task list request for more than one developer: Organize tasks by priority and estimated effort for a every 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."));
+        }
     }
 }

Controllers/ChatController.cs

@@ -62,7 +62,7 @@ namespace ChatApi.Controllers
         [Route("savegroup")]
         public async Task SaveSingleProject([FromBody] ProjectRequest project)
         {
-            var projectSave = project.MapTo<ProjectRequest, Project>(); 
+            var projectSave = project.MapTo<ProjectRequest, Project>();
             await _projectDataRepository.SaveAsync(projectSave);
         }
 
@@ -122,9 +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 _textDataService.GetAll();
+            var texts = await _textDataService.GetByPorjectId(groupId);
             return texts.Select(t => {
                 return new TextResponse
                 {

Program.cs

@@ -21,6 +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.
 
@@ -106,7 +107,12 @@ builder.Services.AddSingleton<CryptUtil>();
 //Desktop
 //builder.Services.AddOllamaChatCompletion("llama3.2", new Uri("http://localhost:11434"));
 //Notebook
-builder.Services.AddOllamaChatCompletion("llama3.2:3b", new Uri("http://localhost:11435"));
+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"));

Services/Contracts/IResponseService.cs

@@ -5,5 +5,6 @@ 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/ResponseService/MongoResponseService.cs

@@ -31,7 +31,7 @@ namespace ChatRAG.Services.ResponseService
         // ========================================
         // MÉTODO ORIGINAL - Delega para ResponseRAGService
         // ========================================
-        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")
         {
             return await _originalService.GetResponse(userData, projectId, sessionId, question);
         }
@@ -108,6 +108,11 @@ namespace ChatRAG.Services.ResponseService
                 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

@@ -35,7 +35,8 @@ namespace ChatRAG.Services.ResponseService
             UserData userData,
             string projectId,
             string sessionId,
-            string userMessage)
+            string userMessage,
+            string language = "pt")
         {
             try
             {
@@ -200,6 +201,11 @@ namespace ChatRAG.Services.ResponseService
                 return false;
             }
         }
+
+        public Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        {
+            return this.GetResponse(userData, projectId, sessionId, question, "pt");
+        }
     }
 }
 

Services/ResponseService/ResponseCompanyService.cs

@@ -7,6 +7,7 @@ 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.
@@ -42,32 +43,52 @@ namespace ChatRAG.Services.ResponseService
             this._vectorSearchService = vectorSearchService;
         }
 
-        public async Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question)
+        public async Task<string> GetResponse(UserData userData, string projectId, string sessionId, string question, string language = "pt")
         {
             var stopWatch = new System.Diagnostics.Stopwatch();
             stopWatch.Start();
 
-            //var resposta = await BuscarTextoRelacionado(question);
-            //var resposta = await BuscarTopTextosRelacionados(question, projectId);
-            //var resposta = await BuscarTopTextosRelacionadosDinamico(question, projectId);
-            var resposta = await BuscarTopTextosRelacionadosComInterface(question, projectId);
-            
+            var searchStrategy = await ClassificarEstrategiaDeBusca(question, language);
 
-            var projectData = (await _projectDataRepository.GetAsync()).FirstOrDefault();
+            string resposta;
+            switch (searchStrategy)
+            {
+                case SearchStrategy.TodosProjeto:
+                    resposta = await BuscarTodosRequisitosDoProjeto(question, projectId);
+                    break;
+                case SearchStrategy.SimilaridadeComFiltro:
+                    resposta = await BuscarTopTextosRelacionadosComInterface(question, projectId);
+                    break;
+                case SearchStrategy.SimilaridadeGlobal:
+                    resposta = await BuscarTopTextosRelacionados(question, projectId);
+                    break;
+                default:
+                    resposta = await BuscarTopTextosRelacionadosComInterface(question, projectId);
+                    break;
+            }
+
+            var projectData = await _projectDataRepository.GetAsync(projectId);
 
             var project = $"Nome: {projectData.Nome} \n\n Descrição:{projectData.Descricao}";
 
             //question = $"Para responder à solicitação/pergunta: \"{question}\" por favor, considere o projeto: \"{project}\" e os requisitos: \"{resposta}\"";
             // Base prompt template
-            string basePrompt = @"You are an expert software analyst and QA professional. 
+            string basePrompt = @"You are a QA professional. Generate ONLY what the user requests.
+            Project Context: {0}
+            Requirements: {1}
+            User Request: ""{2}""
 
-                    Project Context: {0}
-                    Requirements: {1}
-
-                    User Request: ""{2}""
-
-                    Please answer the question above from User Request with a comprehensive response in English. Consider the project context and requirements above to generate accurate and relevant information.";
+            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);
             
@@ -75,7 +96,15 @@ namespace ChatRAG.Services.ResponseService
 
             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);
@@ -85,6 +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>();
@@ -133,6 +224,25 @@ namespace ChatRAG.Services.ResponseService
             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)
         {
@@ -265,6 +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
     }
 }
 

appsettings.json

@@ -1,11 +1,4 @@
 {
-  "DomvsDatabase": {
-    "ConnectionString": "mongodb://admin:c4rn31r0@k3sw2:27017,k3ss1:27017/?authSource=admin",
-    "DatabaseName": "RAGProjects-dev-en",
-    "TextCollectionName": "Texts",
-    "ProjectCollectionName": "Groups",
-    "UserDataName": "UserData"
-  },
   "Logging": {
     "LogLevel": {
       "Default": "Information",
@@ -14,10 +7,10 @@
     }
   },
   "VectorDatabase": {
-    "Provider": "Qdrant", // 👈 Mude para "Qdrant" quando quiser testar
+    "Provider": "Qdrant", 
     "MongoDB": {
       "ConnectionString": "mongodb://admin:c4rn31r0@k3sw2:27017,k3ss1:27017/?authSource=admin",
-      "DatabaseName": "RAGProjects-dev-en",
+      "DatabaseName": "RAGProjects-dev-pt",
       "TextCollectionName": "Texts",
       "ProjectCollectionName": "Groups",
       "UserDataName": "UserData"