Update app.py

app.py

@@ -5,19 +5,14 @@ import inspect
 import pandas as pd
 from langgraph.prebuilt import ToolNode, create_react_agent
 from tools import web_search, parse_excel, ocr_image
-# import langgraph
-from typing import TypedDict, Annotated
+
+from typing import Any, Dict
+# from typing import TypedDict, Annotated
 
 from langchain_openai import ChatOpenAI
 from langgraph.graph import StateGraph, START, END
 from langgraph.graph.message import add_messages
-import langgraph
-import importlib.metadata
-try:
-    lg_ver = importlib.metadata.version("langgraph")
-    print("▶︎ LangGraph version:", lg_ver)
-except importlib.metadata.PackageNotFoundError:
-    print("LangGraph is not installed.")
+from langchain.schema import HumanMessage, AIMessage
 # Create a ToolNode that knows about your web_search function
 
 # (Keep Constants as is)
@@ -50,27 +45,31 @@ compiled_graph = graph.compile()
 # ─── 5) Define `respond_to_input` to call `compiled_graph.invoke` ───
 def respond_to_input(user_input: str) -> str:
     """
-    We must supply `{"messages": [ { "role": "user", "content": ... } ]}`
-    because create_react_agent expects `state["messages"]` to be a list of
-    {role,content} dicts, not plain strings.
+    In v0.4.7, create_react_agent expects:
+      state["messages"] == list[BaseMessage], typically starting with a HumanMessage.
+
+    We feed it exactly that, then call compiled_graph.invoke().
+    Finally, we scan final_state["messages"] for the last AIMessage and return its .content.
     """
+    # 5.a) Build the initial state with a single HumanMessage
     initial_state: Dict[str, Any] = {
-        "messages": [
-            {"role": "user", "content": user_input}
-        ]
+        "messages": [ HumanMessage(content=user_input) ]
     }
-    # In langgraph 0.4.7, the compiled graph uses .invoke(...)
+
+    # 5.b) In LangGraph v0.4.7, use .invoke(...)
     final_state = compiled_graph.invoke(initial_state)
-    # The default agent appends its own assistant messages to state["messages"].
-    # Extract the **last** message where role == "assistant".
+
+    # 5.c) Extract the last AIMessage from final_state["messages"]
+    #     (create_react_agent always appends its assistant replies as AIMessage)
     assistant_messages = [
-        msg["content"]
+        msg.content
         for msg in final_state["messages"]
-        if msg.get("role") == "assistant"
+        if isinstance(msg, AIMessage)
     ]
     if not assistant_messages:
-        return "❗️Agent did not return any assistant message."
-    # Return the very last assistant “content”
+        return "❗️Agent did not return any AIMessage."
+
+    # Return the final AIMessage's content
     return assistant_messages[-1]
 
 class BasicAgent: