Update app.py

app.py

@@ -703,6 +703,56 @@ async def reset():
                 return {"response": expert_response}
             except Exception as e:
                 print(f"⚠️ Expert coding failed: {e}")
+@app.post("/chat")
+async def chat(message: str = Form(...)):
+    """Main chat endpoint"""
+    if not app.state.groq_available:
+        return {"response": "Error: Groq API not configured."}
+    
+    try:
+        from core.language_detector import detect_input_language, get_system_prompt
+        from core.memory_db import tidb_memory
+    except ImportError as e:
+        return {"response": f"Error: {str(e)}"}
+    
+    lang_mode = detect_input_language(message)
+    system_prompt = get_system_prompt(lang_mode, AumCoreConfig.USERNAME)
+    
+    # Get chat history
+    recent_chats = []
+    try:
+        recent_chats = tidb_memory.get_recent_chats(limit=10)
+    except:
+        pass
+    
+    # Prepare messages
+    api_messages = [{"role": "system", "content": system_prompt}]
+    for chat_row in recent_chats:
+        user_input, ai_response, _ = chat_row
+        api_messages.append({"role": "user", "content": user_input})
+        api_messages.append({"role": "assistant", "content": ai_response})
+    api_messages.append({"role": "user", "content": message})
+    
+    # Call Groq API
+    try:
+        completion = client.chat.completions.create(
+            model="llama-3.3-70b-versatile",
+            messages=api_messages,
+            temperature=0.3,
+            max_tokens=1000
+        )
+        ai_response = completion.choices[0].message.content.strip()
+        
+        # Save to database
+        try:
+            tidb_memory.save_chat(message, ai_response, lang_mode)
+        except:
+            pass
+        
+        return {"response": ai_response}
+        
+    except Exception as e:
+        return {"response": f"Error: {str(e)}"}
         
         # Fallback to basic code
         code_response = generate_basic_code(message)