Update app.py

app.py

@@ -2,14 +2,11 @@ import os
 import gradio as gr
 import datetime
 import pytz
-import os
-from llama_index.core.agent import ReActAgent  # <--- MUST be this exact import
+from llama_index.core.agent import ReActAgent
 from llama_index.core.tools import FunctionTool
 from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
-# ... rest of your imports
 
 # 1. Setup LLM
-# Reminder: Add HF_TOKEN to your Space "Secrets" in Settings
 hf_token = os.getenv("HF_TOKEN")
 
 llm = HuggingFaceInferenceAPI(
@@ -17,9 +14,9 @@ llm = HuggingFaceInferenceAPI(
     token=hf_token
 )
 
-# 2. Define your Tools
+# 2. Define Tools
 def get_tokyo_time() -> str:
-    """Returns the current time in Tokyo, Japan."""
+    """Useful for when you need to know the current time in Tokyo, Japan."""
     tz = pytz.timezone('Asia/Tokyo')
     return f"The current time in Tokyo is {datetime.datetime.now(tz).strftime('%H:%M:%S')}"
 
@@ -27,14 +24,13 @@ def multiply(a: float, b: float) -> float:
     """Multiplies two numbers and returns the result."""
     return a * b
 
-# Wrap tools
 tools = [
     FunctionTool.from_defaults(fn=get_tokyo_time),
     FunctionTool.from_defaults(fn=multiply)
 ]
 
-# 3. Create the Agent 
-# Note: Using ReActAgent.from_tools is correct for the core class
+# 3. Create the Agent (The "Classic" Core version)
+# This will now work correctly with .from_tools()
 agent = ReActAgent.from_tools(
     tools, 
     llm=llm, 
@@ -43,15 +39,8 @@ agent = ReActAgent.from_tools(
 
 # 4. Gradio Interface
 def chat(message, history):
-    # The agent handles the conversation state internally
+    # ReActAgent.chat() is synchronous and preserves conversation history
     response = agent.chat(message)
     return str(response)
 
-demo = gr.ChatInterface(
-    fn=chat, 
-    title="Unit 2: LlamaIndex Agent",
-    description="I am a LlamaIndex agent with access to Tokyo time and multiplication tools."
-)
-
-if __name__ == "__main__":
-    demo.launch()
+gr.ChatInterface(chat, title="Unit 2: LlamaIndex Agent").launch()