improved tool calling , prompt enhance

app/main.py

@@ -143,7 +143,33 @@ async def chat_with_ai(request: ChatRequest):
         # Add system message to guide the AI
         system_message: ChatCompletionMessageParam = {
             "role": "system",
-            "content": "You are a helpful AI assistant. You have access to a RAG (Retrieval-Augmented Generation) pipeline that can answer questions about specific datasets. Use the rag_qa tool when users ask questions that would benefit from searching the dataset knowledge. For general conversation, respond normally. The available datasets are primarily focused on developer portfolio information, but can include other topics depending on what's loaded."
+            "content": """You are an AI assistant for Rohit's developer portfolio. You have access to a RAG (Retrieval-Augmented Generation) pipeline containing information about Rohit's professional background, skills, and experience.
+
+CRITICAL: The portfolio information is about ROHIT, not you. Always refer to Rohit in the third person ("he", "his", "Rohit") rather than first person ("I", "my", "me").
+
+When you use rag_qa tool, you MUST use retrieved information to answer about Rohit's background.
+
+Guidelines:
+- Use rag_qa tool for questions about Rohit's: work experience, skills, projects, achievements, contact info
+- For general greetings, introduce yourself as Rohit's AI assistant
+- Always refer to Rohit in third person (he/his/Rohit)
+- Synthesize RAG results into natural responses about Rohit
+- Format responses with markdown for readability
+
+Examples:
+❌ Wrong: "I am a Tech Lead at FleetEnable"
+✅ Right: "Rohit is currently working as a Tech Lead at FleetEnable"
+
+❌ Wrong: "My responsibilities include..."
+✅ Right: "His responsibilities include..."
+
+❌ Wrong: "I have 5+ years of experience..."
+✅ Right: "Rohit has 5+ years of experience..."
+
+❌ Wrong: "You can reach me at..."
+✅ Right: "You can reach Rohit at..."
+
+For greetings: "Hi! I'm Rohit's AI assistant. I can help you learn about his professional background, skills, and experience. What would you like to know about Rohit?"""
         }
         
         # Insert system message at the beginning
@@ -216,11 +242,10 @@ async def chat_with_ai(request: ChatRequest):
                 "tool_calls": [
                     {
                         "name": tc.function.name,
-                        "arguments": tc.function.arguments,
-                        "result": next(tr["result"] for tr in tool_results if tr["tool_call_id"] == tc.id)
+                        "arguments": tc.function.arguments
                     }
                     for tc in message.tool_calls
-                ] if message.tool_calls else None
+                ]
             }
         else:
             # Direct response without tool calls
@@ -232,26 +257,7 @@ async def chat_with_ai(request: ChatRequest):
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))
 
-@app.post("/answer")
-async def get_answer(question: Question):
-    try:
-        # Check if any pipelines are loaded
-        if not pipelines:
-            return {
-                "answer": "RAG Pipeline is running but datasets are still loading in the background. Please try again in a moment, or check /health for loading status.",
-                "dataset": question.dataset,
-                "status": "datasets_loading"
-            }
-        
-        # Select the appropriate pipeline based on dataset
-        if question.dataset not in pipelines:
-            raise HTTPException(status_code=400, detail=f"Dataset '{question.dataset}' not available. Available datasets: {list(pipelines.keys())}")
-        
-        selected_pipeline = pipelines[question.dataset]
-        answer = selected_pipeline.answer_question(question.text)
-        return {"answer": answer, "dataset": question.dataset}
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
+# /answer endpoint removed - use /chat for all interactions
 
 @app.get("/datasets")
 async def list_datasets():