Fixed chat history

app.py

@@ -2,8 +2,9 @@ import os
 import chainlit as cl
 from dotenv import load_dotenv
 from langchain_anthropic import ChatAnthropic
-from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.output_parsers import StrOutputParser
+from langchain_core.chat_history import InMemoryChatMessageHistory
 
 # Load environment variables (Hugging Face Spaces injects secrets automatically)
 load_dotenv()
@@ -40,7 +41,7 @@ SYSTEM_PROMPT = load_system_prompt()
 
 
 def get_chain():
-    """Create and return the LCEL chain."""
+    """Create and return the LCEL chain with conversation history support."""
     if not ANTHROPIC_API_KEY:
         return None
 
@@ -51,9 +52,11 @@ def get_chain():
         temperature=0.7
     )
 
-    # Create the prompt template with system message from prompt.md
+    # Create the prompt template with system message and conversation history placeholder
+    # Always include MessagesPlaceholder - we'll pass empty list if no history
     prompt = ChatPromptTemplate.from_messages([
         ("system", SYSTEM_PROMPT),
+        MessagesPlaceholder(variable_name="chat_history"),
         ("human", "{input}")
     ])
 
@@ -64,66 +67,99 @@ def get_chain():
 @cl.on_chat_start
 async def on_chat_start():
     """Initialize the chain when a chat session starts."""
-    # Store the chain in user session first (before any messages)
-    chain = get_chain()
-    if chain:
-        cl.user_session.set("chain", chain)
+    # Initialize chat history for this session
+    chat_history = InMemoryChatMessageHistory()
+    cl.user_session.set("chat_history", chat_history)
 
-    # Check if API key is available
-    if not ANTHROPIC_API_KEY:
-        try:
-            await cl.Message(
-                content="❌ Error: ANTHROPIC_API_KEY not configured. Please set it in Space settings → Variables and secrets."
-            ).send()
-        except LookupError:
-            # ContextVar error - chain will be initialized on first message instead
-            pass
-        return
+    # Mark that this is a new session (for welcome message)
+    cl.user_session.set("first_message", True)
 
-    # Create the chain if not already created
-    if chain is None:
-        try:
-            await cl.Message(
-                content="❌ Error: Could not initialize chain. Please check API key configuration."
-            ).send()
-        except LookupError:
-            # ContextVar error - chain will be initialized on first message instead
-            pass
-        return
+    # Don't send messages here to avoid ContextVar issues in deployment
+    # Messages will be handled in on_message instead
 
-    # Send welcome message - according to prompt section 1.6, ask ONE question: "What are you working on?"
-    try:
-        await cl.Message(content="What are you working on?").send()
-    except LookupError:
-        # ContextVar error - message will be sent on first user message instead
-        # The chain is already stored in user_session, so on_message will work
-        pass
+
+def is_simple_greeting(text: str) -> bool:
+    """Check if the message is just a simple greeting."""
+    text_lower = text.strip().lower()
+    simple_greetings = ["hi", "hello", "hey",
+                        "hey there", "hi there", "greetings"]
+    return text_lower in simple_greetings or len(text_lower) <= 3
 
 
 @cl.on_message
 async def on_message(message: cl.Message):
     """Handle incoming messages and stream responses."""
-    # Retrieve the chain from user session
-    chain = cl.user_session.get("chain")
+    # Get or initialize chat history
+    chat_history = cl.user_session.get("chat_history")
+    if chat_history is None:
+        chat_history = InMemoryChatMessageHistory()
+        cl.user_session.set("chat_history", chat_history)
+
+    # Check if this is the first message and send welcome message
+    is_first = cl.user_session.get("first_message", False)
+    if is_first:
+        cl.user_session.set("first_message", False)
+
+        # Check API key
+        if not ANTHROPIC_API_KEY:
+            await cl.Message(
+                content="❌ Error: ANTHROPIC_API_KEY not configured. Please set it in Space settings → Variables and secrets."
+            ).send()
+            return
 
-    # If chain is None, try to initialize it (in case on_chat_start had ContextVar issues)
-    if chain is None:
-        chain = get_chain()
-        if chain:
-            cl.user_session.set("chain", chain)
-        else:
-            await cl.Message(content="Error: Chain not initialized. Please refresh the page.").send()
+        # Send welcome message - according to prompt section 1.6, ask ONE question: "What are you working on?"
+        welcome_msg = "What are you working on?"
+        await cl.Message(content=welcome_msg).send()
+
+        # Add welcome message to chat history and persist back to session
+        from langchain_core.messages import AIMessage
+        chat_history.add_message(AIMessage(content=welcome_msg))
+        cl.user_session.set("chat_history", chat_history)  # Persist changes
+
+        # If the user's first message is just a greeting, don't process it
+        # Otherwise, continue to process their meaningful response
+        if is_simple_greeting(message.content):
             return
 
+    # Check API key
+    if not ANTHROPIC_API_KEY:
+        await cl.Message(
+            content="❌ Error: ANTHROPIC_API_KEY not configured. Please set it in Space settings → Variables and secrets."
+        ).send()
+        return
+
+    # Get the chain (it supports conversation history via MessagesPlaceholder)
+    chain = get_chain()
+    if chain is None:
+        await cl.Message(content="❌ Error: Chain not initialized. Please refresh the page.").send()
+        return
+
     # Create a message object for streaming
     msg = cl.Message(content="")
     await msg.send()
 
+    # Prepare input with chat history (previous messages only, current message goes in {input})
+    input_dict = {
+        "input": message.content,
+        "chat_history": chat_history.messages  # All previous messages
+    }
+
     # Invoke the chain asynchronously with streaming
     try:
-        async for chunk in chain.astream({"input": message.content}):
+        full_response = ""
+        async for chunk in chain.astream(input_dict):
             await msg.stream_token(chunk)
+            full_response += chunk
         await msg.update()
+
+        # Add both user message and assistant response to chat history AFTER processing
+        from langchain_core.messages import HumanMessage, AIMessage
+        chat_history.add_message(HumanMessage(content=message.content))
+        chat_history.add_message(AIMessage(content=full_response))
+
+        # Persist changes back to session
+        cl.user_session.set("chat_history", chat_history)
+
     except Exception as e:
         # Log the full error for debugging
         error_msg = f"❌ Error: {str(e)}"

requirements.txt

@@ -1,6 +1,7 @@
-chainlit
-langchain
-langchain-anthropic
-python-dotenv
-pydantic
-websockets
+chainlit>=2.9.4
+langchain>=1.2.0
+langchain-anthropic>=1.3.0
+python-dotenv>=1.0.1
+pydantic>=2.12.0
+websockets>=15.0
+typing-extensions>=4.15.0