chatbot

app.py

@@ -55,6 +55,7 @@ llm = HuggingFaceEndpoint(
 
 model = ChatHuggingFace(llm=llm, verbose=True)
 
+"""
 def predict(message, history):
     history_langchain_format = []
     for msg in history:
@@ -65,7 +66,28 @@ def predict(message, history):
     history_langchain_format.append(HumanMessage(content=message))
     gpt_response = model.invoke(history_langchain_format)
     return gpt_response.content
+"""
 
+def predict(message, history):
+    # Convert Gradio history to LangChain message format
+    history_langchain_format = []
+    for msg in history:
+        if msg['role'] == "user":
+            history_langchain_format.append(HumanMessage(content=msg['content']))
+        elif msg['role'] == "assistant":
+            history_langchain_format.append(AIMessage(content=msg['content"]))
+    
+    # Add new user message
+    history_langchain_format.append(HumanMessage(content=message))
+    
+    # Invoke Alfred agent with full message history
+    response = alfred.invoke(
+        input={"messages": history_langchain_format},
+        config={"recursion_limit": 100}
+    )
+    
+    # Extract final assistant message
+    return response["messages"][-1].content
 
 # setup agents