chat with memory removed

ai_chat.py

@@ -3,39 +3,29 @@ from langchain_core.runnables import RunnableLambda
 from typing import TypedDict
 from config import llm, OPENAI_API_KEY
 
-# Simple in-memory chat history (no deprecation warnings)
-chat_history = []
-
-def chat_with_memory(state):
-    """Chat function with memory and user context"""
+def chat_without_memory(state):
+    """Chat function without memory - stateless responses"""
     user_message = state["user_message"]
     user_info = state.get("user_info", {})
     
-    # Add user message to history
-    chat_history.append({"role": "user", "content": user_message})
-    
-    # Keep only last 6 messages for context
-    recent_messages = chat_history[-6:] if len(chat_history) > 6 else chat_history
-    
     # Add system message with user context
     system_message = "You are a helpful and concise assistant."
     if user_info.get("name") and user_info["name"] != "Unknown":
         system_message += f" The user's name is {user_info['name']}."
     
-    messages = [{"role": "system", "content": system_message}] + recent_messages
+    messages = [
+        {"role": "system", "content": system_message},
+        {"role": "user", "content": user_message}
+    ]
 
     try:
         if not OPENAI_API_KEY:
             return {"response": "Sorry, AI chat is not available. Please check your OpenAI API key configuration."}
         
         response = llm.invoke(messages)
-        
-        # Add AI response to history
-        chat_history.append({"role": "assistant", "content": response.content})
-        
         return {"response": response.content}
     except Exception as e:
-        print(f"Error in chat_with_memory: {e}")
+        print(f"Error in chat_without_memory: {e}")
         return {"response": "Sorry, something went wrong: " + str(e)}
 
 class ChatState(TypedDict):
@@ -45,7 +35,7 @@ class ChatState(TypedDict):
 
 # --- Build LangGraph ---
 graph = StateGraph(ChatState)
-graph.add_node("chat", RunnableLambda(chat_with_memory))
+graph.add_node("chat", RunnableLambda(chat_without_memory))
 graph.set_entry_point("chat")
 graph.add_edge("chat", END)
 chat_graph = graph.compile()