app.py

import os
import json
import gradio as gr
import requests
from dotenv import load_dotenv
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 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:
    """
    Get the current weather in a given location
    
    Args:
        location (str): The city name, e.g. San Francisco, Tokyo
        unit (str): The unit of temperature, either celsius or fahrenheit
        
    Returns:
        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:
        return {"location": "San Francisco", "temperature": "72", "unit": "fahrenheit"}
    elif "paris" in location:
        return {"location": "Paris", "temperature": "22", "unit": "celsius"}
    else:
        return {"location": location, "temperature": "unknown", "unit": unit}

# Create a tool for the agent
weather_tool = FunctionTool.from_defaults(
    name="get_current_weather",
    fn=get_current_weather,
    description="Get the current weather in a given location"
)

# 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,
    api_key=openrouter_token
)

# Create the agent with an appropriate system prompt
agent = ReActAgent.from_tools(
    [weather_tool],
    llm=llm,
    verbose=False
)

def respond(message, history):
    # Execute the agent with user input
    response = agent.chat(message)
    return str(response)

# Create Gradio interface
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=[
            "What's the weather like in Tokyo?",
            "How's the weather in San Francisco?",
            "Tell me about the current weather in Paris",
            "What should I wear in Tokyo based on the weather?",
            "Is it warm in San Francisco?"
        ],
        title="Chat with Weather Assistant"
    )
    gr.Markdown("### Built with LlamaIndex and OpenRouter API")

# Launch the application
if __name__ == "__main__":
    demo.launch()