Update app.py

app.py

@@ -1,27 +1,41 @@
 import os
 import gradio as gr
-import datetime
-import pytz
 from llama_index.core.agent import ReActAgent
 from llama_index.core.tools import FunctionTool
 from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
+import datetime
+import pytz
 
-# 1. Setup LLM
+# 1. SETUP LLM
 hf_token = os.getenv("HF_TOKEN")
 
+# We use a system prompt to tell the model EXACTLY how to use tools
+SYSTEM_PROMPT = """You are a helpful assistant that can use tools.
+For any tool call, you MUST use this format:
+Thought: I need to use a tool to answer this.
+Action: tool_name
+Action Input: {"arg1": "value"}
+Observation: tool_result
+... (repeat if needed)
+Thought: I now know the final answer
+Answer: your final response
+"""
+
 llm = HuggingFaceInferenceAPI(
     model_name="Qwen/Qwen2.5-Coder-32B-Instruct", 
-    token=hf_token
+    token=hf_token,
+    # This ensures the model doesn't try to use 'native' tools that HF might not support
+    is_function_calling_model=False 
 )
 
-# 2. Define Tools
+# 2. TOOLS
 def get_tokyo_time() -> str:
-    """Useful for when you need to know the current time in Tokyo, Japan."""
+    """Returns 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')}"
 
 def multiply(a: float, b: float) -> float:
-    """Multiplies two numbers and returns the result."""
+    """Multiplies two numbers (a and b) and returns the result."""
     return a * b
 
 tools = [
@@ -29,18 +43,20 @@ tools = [
     FunctionTool.from_defaults(fn=multiply)
 ]
 
-# 3. Create the Agent (The "Classic" Core version)
-# This will now work correctly with .from_tools()
+# 3. AGENT
 agent = ReActAgent.from_tools(
     tools, 
     llm=llm, 
-    verbose=True
+    verbose=True,
+    context=SYSTEM_PROMPT # This keeps the agent from crashing
 )
 
-# 4. Gradio Interface
+# 4. GRADIO
 def chat(message, history):
-    # ReActAgent.chat() is synchronous and preserves conversation history
-    response = agent.chat(message)
-    return str(response)
+    try:
+        response = agent.chat(message)
+        return str(response)
+    except Exception as e:
+        return f"Error: {str(e)}. Please try asking again."
 
-gr.ChatInterface(chat, title="Unit 2: LlamaIndex Agent").launch()
+demo = gr.ChatInterface(chat, title="LlamaIndex Unit 2 Fix").launch()