Update app.py

app.py

@@ -1,105 +1,91 @@
 import os
+import gradio as gr
 import datetime
 import pytz
-import math
-import requests
-import gradio as gr
-from smolagents import CodeAgent, DuckDuckGoSearchTool, tool, InferenceClientModel
-from deep_translator import GoogleTranslator
-from llama_index.core.agent import ReActAgent
+import asyncio
+
+# Framework 1: LlamaIndex
+from llama_index.core.agent.workflow import AgentWorkflow
 from llama_index.core.tools import FunctionTool
 from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
 
-# ============ 1. SMOLAGENTS TOOLS ============
+# Framework 2: smolagents
+from smolagents import CodeAgent, DuckDuckGoSearchTool, tool, InferenceClientModel
 
-@tool
-def time_tool(timezone: str = "UTC") -> str:
-    """
-    Get current time in a specific timezone.
-    Args:
-        timezone: The timezone to check (e.g., 'Asia/Tokyo').
-    """
-    try:
-        tz = pytz.timezone(timezone)
-        now = datetime.datetime.now(tz)
-        return f"⏰ Time in {timezone}: {now.strftime('%Y-%m-%d %H:%M:%S')}"
-    except Exception as e:
-        return f"Error: {str(e)}"
+# 0. SHARED CONFIG
+HF_TOKEN = os.getenv("HF_TOKEN")
+# 7B is the sweet spot for free serverless inference in 2026
+MODEL_ID = "Qwen/Qwen2.5-7B-Instruct"
 
-@tool
-def translator_tool(text: str, target_language: str) -> str:
-    """
-    Translates text into a specified language.
-    Args:
-        text: The text or phrase to translate.
-        target_language: The destination language (e.g., 'french', 'german').
-    """
+# ==========================================
+# PART 1: LLAMAINDEX AGENT
+# ==========================================
+li_llm = HuggingFaceInferenceAPI(
+    model_name=MODEL_ID,
+    token=HF_TOKEN,
+    provider="together" 
+)
+
+def get_tokyo_time() -> 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')}"
+
+li_tools = [FunctionTool.from_defaults(fn=get_tokyo_time)]
+
+li_agent = AgentWorkflow.from_tools_or_functions(
+    li_tools,
+    llm=li_llm,
+)
+
+async def chat_llama(message, history):
     try:
-        translation = GoogleTranslator(source='auto', target=target_language).translate(text)
-        return f"Translated to {target_language.title()}: {translation}"
+        result = await li_agent.run(user_msg=message)
+        return str(result)
     except Exception as e:
-        return f"Translation error: {str(e)}"
+        return f"LlamaIndex Error: {str(e)}"
+
+# ==========================================
+# PART 2: SMOLAGENTS
+# ==========================================
+smol_model = InferenceClientModel(
+    model_id=MODEL_ID,
+    token=HF_TOKEN,
+    provider="together"
+)
 
 @tool
 def weather_tool(location: str) -> str:
-    """
-    Get the current weather for any location worldwide.
+    """Get the current weather for a location.
     Args:
-        location: The name of the city or place (e.g., 'London' or 'Tokyo').
+        location: The city name.
     """
-    try:
-        geo_url = f"https://geocoding-api.open-meteo.com/v1/search?name={location}&count=1&language=en&format=json"
-        geo_res = requests.get(geo_url).json()
-        if not geo_res.get('results'): return "Location not found."
-        data = geo_res['results'][0]
-        weather_url = f"https://api.open-meteo.com/v1/forecast?latitude={data['latitude']}&longitude={data['longitude']}&current=temperature_2m"
-        w_res = requests.get(weather_url).json()
-        return f"🌤️ {data['name']}: {w_res['current']['temperature_2m']}°C"
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-# ============ AGENT CONFIGURATION ============
-
-HF_TOKEN = os.getenv("HF_TOKEN", "")
-smol_model = InferenceClientModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct", token=HF_TOKEN)
+    return f"The weather in {location} is currently sunny and 22°C."
 
 smol_agent = CodeAgent(
     model=smol_model,
-    tools=[DuckDuckGoSearchTool(), time_tool, translator_tool, weather_tool],
-    max_steps=5
+    tools=[weather_tool, DuckDuckGoSearchTool()]
 )
 
-# LlamaIndex Setup
-llama_llm = HuggingFaceInferenceAPI(
-    model_name="Qwen/Qwen2.5-7B-Instruct", 
-    token=HF_TOKEN,
-    task="conversational"
-)
-
-llama_agent = ReActAgent.from_tools(
-    [
-        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
-)
-
-# ============ GRADIO UI ============
-
 def chat_smol(message, history):
-    return str(smol_agent.run(message))
-
-def chat_llama(message, history):
-    response = llama_agent.chat(message)
-    return str(response)
+    try:
+        response = smol_agent.run(message)
+        return str(response)
+    except Exception as e:
+        return f"Smolagents Error: {str(e)}"
 
+# ==========================================
+# PART 3: UNIFIED GRADIO UI
+# ==========================================
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🤖 Multi-Framework AI Agent Space")
-    with gr.Tab("Smolagents (Alfred)"):
-        gr.ChatInterface(chat_smol)
-    with gr.Tab("LlamaIndex (ReAct)"):
-        gr.ChatInterface(chat_llama)
+    gr.Markdown("# 🤖 Consolidated AI Agent Space")
+    gr.Markdown(f"Currently using **{MODEL_ID}** via Together AI Provider.")
+    
+    with gr.Tab("LlamaIndex (Workflow)"):
+        gr.ChatInterface(fn=chat_llama)
+        
+    with gr.Tab("smolagents (CodeAgent)"):
+        gr.ChatInterface(fn=chat_smol)
 
 if __name__ == "__main__":
     demo.launch()