Update app.py

app.py

@@ -1,22 +1,19 @@
 import os
 import json
 import gradio as gr
+import requests
 from dotenv import load_dotenv
-from huggingface_hub import login
-from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
 from llama_index.core.agent import ReActAgent
 from llama_index.core.tools import FunctionTool
+from llama_index.llms.openai import OpenAI
 
 # Load environment variables
 load_dotenv()
 
-# Get Hugging Face token
-hf_token = os.getenv("HUGGINGFACE_TOKEN")
-if not hf_token:
-    raise ValueError("Hugging Face token not found. Configure HUGGINGFACE_TOKEN in your environment variables")
-
-# Authenticate with Hugging Face
-login(token=hf_token)
+# Get OpenRouter token
+openrouter_token = os.getenv("OPENROUTER_API_KEY")
+if not openrouter_token:
+    raise ValueError("OpenRouter token not found. Configure OPENROUTER_API_KEY in your environment variables")
 
 # Define weather function with static data
 def get_current_weather(location: str, unit: str = "fahrenheit") -> dict:
@@ -31,7 +28,6 @@ def get_current_weather(location: str, unit: str = "fahrenheit") -> dict:
         dict: Weather information including location, temperature and unit
     """
     location = location.lower()
-    
     if "tokyo" in location:
         return {"location": "Tokyo", "temperature": "10", "unit": "celsius"}
     elif "san francisco" in location:
@@ -48,12 +44,28 @@ weather_tool = FunctionTool.from_defaults(
     description="Get the current weather in a given location"
 )
 
-# Configure the language model
-llm = HuggingFaceInferenceAPI(
-    model_name="Qwen/Qwen2.5-Coder-32B-Instruct",
+# Custom OpenRouter implementation using OpenAI-compatible interface
+class OpenRouterLLM(OpenAI):
+    def __init__(self, model_name="qwen/qwen-2.5-coder-32b-instruct:free", temperature=0.7, max_tokens=512, api_key=None):
+        # Initialize with custom base URL and model name
+        super().__init__(
+            model=model_name,
+            temperature=temperature,
+            max_tokens=max_tokens,
+            api_key=api_key,
+            api_base="https://openrouter.ai/api/v1",
+            additional_headers={
+                "HTTP-Referer": "weather-assistant-app",
+                "X-Title": "Weather Assistant"
+            }
+        )
+
+# Configure the language model with OpenRouter
+llm = OpenRouterLLM(
+    model_name="qwen/qwen-2.5-coder-32b-instruct:free",
     temperature=0.7,
     max_tokens=512,
-    token=hf_token,
+    api_key=openrouter_token
 )
 
 # Create the agent with an appropriate system prompt
@@ -72,7 +84,6 @@ def respond(message, history):
 with gr.Blocks(title="Weather Assistant") as demo:
     gr.Markdown("# 🌤️ Weather Assistant")
     gr.Markdown("### Ask about the weather in Tokyo, San Francisco, or Paris")
-    
     chatbot = gr.ChatInterface(
         respond,
         examples=[
@@ -84,8 +95,7 @@ with gr.Blocks(title="Weather Assistant") as demo:
         ],
         title="Chat with Weather Assistant"
     )
-    
-    gr.Markdown("### Built with LlamaIndex and Qwen2.5-Coder-32B-Instruct")
+    gr.Markdown("### Built with LlamaIndex and OpenRouter API")
 
 # Launch the application
 if __name__ == "__main__":