Update app.py

app.py

@@ -1,117 +1,56 @@
 import os
-import datetime
-import pytz
-import math
-import requests
 import gradio as gr
-from deep_translator import GoogleTranslator
-
-# --- LLAMAINDEX IMPORTS ---
 from llama_index.core.agent import ReActAgent
 from llama_index.core.tools import FunctionTool
 from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
+from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool
 
-# --- SMOLAGENTS IMPORTS ---
-from smolagents import CodeAgent, DuckDuckGoSearchTool, tool, InferenceClientModel
-
-# 1. SHARED SETUP & TOKENS
-# Ensure you set these in your Hugging Face Space Settings -> Secrets
+# 1. SETUP LLM
 HF_TOKEN = os.getenv("HF_TOKEN")
 
-# ==========================================
-# PART 1: LLAMAINDEX AGENT SETUP
-# ==========================================
+# --- LLAMAINDEX SETUP ---
 li_llm = HuggingFaceInferenceAPI(
     model_name="Qwen/Qwen2.5-7B-Instruct", 
     token=HF_TOKEN,
-    task="conversational", 
-    provider="together"
+    task="conversational"
 )
 
-def get_tokyo_time_li() -> str:
-    """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_li(a: float, b: float) -> float:
-    """Multiplies two numbers (a and b) and returns the result."""
+# Define simple tools for LlamaIndex
+def multiply(a: float, b: float) -> float:
+    """Multiplies two numbers."""
     return a * b
 
-li_tools = [
-    FunctionTool.from_defaults(fn=get_tokyo_time_li),
-    FunctionTool.from_defaults(fn=multiply_li)
-]
-
-RE_ACT_PROMPT = """You are a helpful assistant.
-For every query, you MUST follow this sequence:
-Thought: <your reasoning>
-Action: <tool_name>
-Action Input: {"arg1": value}
-Observation: <result from tool>
-... (repeat if needed)
-Thought: I have the final answer.
-Answer: <your final response to the user>
-"""
+li_tools = [FunctionTool.from_defaults(fn=multiply)]
 
+# Fix: Ensure correct initialization
 li_agent = ReActAgent.from_tools(
-    li_tools, 
+    tools=li_tools, 
     llm=li_llm, 
-    verbose=True,
-    context=RE_ACT_PROMPT
-)
-
-def li_chat_fn(message, history):
-    try:
-        return str(li_agent.chat(message))
-    except Exception as e:
-        return f"LlamaIndex Error: {str(e)}"
-
-li_interface = gr.ChatInterface(li_chat_fn, title="LlamaIndex Agent")
-
-# ==========================================
-# PART 2: SMOLAGENTS SETUP
-# ==========================================
-smol_model = InferenceClientModel(
-    model_id="Qwen/Qwen2.5-Coder-32B-Instruct",
-    token=HF_TOKEN 
-)
-
-@tool
-def weather_tool(location: str) -> str:
-    """Get current weather for any location.
-    Args:
-        location: The name of the city.
-    """
-    geo_url = f"https://geocoding-api.open-meteo.com/v1/search?name={location}&count=1"
-    geo_res = requests.get(geo_url).json()
-    if not geo_res.get('results'): return "Location not found."
-    data = geo_res['results'][0]
-    w_url = f"https://api.open-meteo.com/v1/forecast?latitude={data['latitude']}&longitude={data['longitude']}&current=temperature_2m"
-    w_res = requests.get(w_url).json()
-    return f"Temp in {location}: {w_res['current']['temperature_2m']}°C"
-
-smol_agent = CodeAgent(
-    model=smol_model,
-    tools=[weather_tool, DuckDuckGoSearchTool()],
-    additional_authorized_imports=['requests', 'math', 'pytz']
+    verbose=True
 )
 
-def smol_chat_fn(message, history):
-    try:
-        return str(smol_agent.run(message))
-    except Exception as e:
-        return f"Smolagents Error: {str(e)}"
-
-smol_interface = gr.ChatInterface(smol_chat_fn, title="Smolagents Assistant")
-
-# ==========================================
-# PART 3: COMBINE INTO TABS
-# ==========================================
-demo = gr.TabbedInterface(
-    [li_interface, smol_interface], 
-    ["LlamaIndex Agent", "Smolagents Agent"],
-    title="Multi-Framework Agent Comparison"
-)
+# --- SMOLAGENTS SETUP ---
+smol_model = HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct", token=HF_TOKEN)
+smol_agent = CodeAgent(tools=[DuckDuckGoSearchTool()], model=smol_model)
+
+# 2. DEFINE WRAPPER FUNCTIONS FOR GRADIO
+def chat_llama(message, history):
+    # LlamaIndex .chat() keeps its own history if using the same agent object
+    response = li_agent.chat(message)
+    return str(response)
+
+def chat_smol(message, history):
+    # smolagents .run()
+    response = smol_agent.run(message)
+    return str(response)
+
+# 3. COMBINE INTO TABS
+with gr.Blocks() as demo:
+    gr.Markdown("# Dual Agent Interface: LlamaIndex vs Smolagents")
+    with gr.Tab("LlamaIndex (ReAct)"):
+        gr.ChatInterface(chat_llama)
+    with gr.Tab("Smolagents (Code)"):
+        gr.ChatInterface(chat_smol)
 
 if __name__ == "__main__":
     demo.launch()