Update app.py

app.py

@@ -8,7 +8,7 @@ from smolagents import CodeAgent, DuckDuckGoSearchTool, tool, InferenceClientMod
 from deep_translator import GoogleTranslator
 from llama_index.core.agent import ReActAgent
 from llama_index.core.tools import FunctionTool
-from llama_index.llms.huggingface import HuggingFaceInferenceAPI # Note: Import path might vary slightly based on version
+from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
 
 # ============ 1. SMOLAGENTS TOOLS ============
 
@@ -60,11 +60,7 @@ def weather_tool(location: str) -> str:
 
 # ============ AGENT CONFIGURATION ============
 
-HF_TOKEN = os.getenv("HF_TOKEN")
-if not HF_TOKEN:
-    raise ValueError("HF_TOKEN is missing! Please add it in Space Settings -> Secrets.")
-
-# SmolAgents Setup
+HF_TOKEN = os.getenv("HF_TOKEN", "")
 smol_model = InferenceClientModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct", token=HF_TOKEN)
 
 smol_agent = CodeAgent(
@@ -74,26 +70,16 @@ smol_agent = CodeAgent(
 )
 
 # LlamaIndex Setup
-# Use 'text-generation' for Instruct models
 llama_llm = HuggingFaceInferenceAPI(
     model_name="Qwen/Qwen2.5-7B-Instruct", 
     token=HF_TOKEN,
-    task="text-generation" 
+    task="conversational"
 )
 
-# Define real functions for LlamaIndex
-def get_tokyo_time() -> str:
-    """Get the current time in Tokyo."""
-    return f"Tokyo: {datetime.datetime.now(pytz.timezone('Asia/Tokyo'))}"
-
-def multiply(a: float, b: float) -> float:
-    """Multiply two numbers."""
-    return a * b
-
 llama_agent = ReActAgent.from_tools(
     [
-        FunctionTool.from_defaults(fn=get_tokyo_time),
-        FunctionTool.from_defaults(fn=multiply)
+        FunctionTool.from_defaults(fn=lambda: f"Tokyo: {datetime.datetime.now(pytz.timezone('Asia/Tokyo'))}", name="get_tokyo_time"),
+        FunctionTool.from_defaults(fn=lambda a, b: a * b, name="multiply")
     ],
     llm=llama_llm,
     verbose=True
@@ -102,28 +88,17 @@ llama_agent = ReActAgent.from_tools(
 # ============ GRADIO UI ============
 
 def chat_smol(message, history):
-    try:
-        # CodeAgent returns the result directly
-        return str(smol_agent.run(message))
-    except Exception as e:
-        return f"Agent Error: {str(e)}"
+    return str(smol_agent.run(message))
 
 def chat_llama(message, history):
-    try:
-        response = llama_agent.chat(message)
-        return str(response)
-    except Exception as e:
-        return f"Agent Error: {str(e)}"
+    response = llama_agent.chat(message)
+    return str(response)
 
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 🤖 Multi-Framework AI Agent Space")
-    
     with gr.Tab("Smolagents (Alfred)"):
-        gr.Markdown("Uses `Qwen2.5-Coder-32B`. Capable of writing code to solve problems.")
         gr.ChatInterface(chat_smol)
-        
     with gr.Tab("LlamaIndex (ReAct)"):
-        gr.Markdown("Uses `Qwen2.5-7B`. Good for reasoning and simple tool use.")
         gr.ChatInterface(chat_llama)
 
 if __name__ == "__main__":