main.py

from fastapi import FastAPI
import gradio as gr
import google.generativeai as genai
from weather import get_current_weather
import os
import uvicorn
import json

app = FastAPI()
genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
model = genai.GenerativeModel('gemini-pro')

# Tools configuration
tools = [
    {
        "name": "get_current_weather",
        "description": "Get current weather information",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {
                    "type": "string",
                    "description": "City name, e.g. Paris, France"
                }
            },
            "required": ["location"]
        }
    }
]

def execute_tool_call(tool_call):
    func_name = tool_call["name"]
    args = json.loads(tool_call["arguments"])
    
    if func_name == "get_current_weather":
        return get_current_weather(args["location"])
    else:
        return f"Error: Unknown function {func_name}"

def process_message(message):
    # Generate tool use suggestions
    response = model.generate_content(
        f"Analyze if user needs weather info: {message}. Respond ONLY with JSON:"
        '{{"needs_weather": true|false, "location": "city"}}'
    )
    
    try:
        analysis = json.loads(response.text)
        if analysis.get("needs_weather", False):
            location = analysis.get("location", "London")
            return get_current_weather(location)
    except:
        pass
    
    # Regular response
    chat = model.start_chat(history=[])
    response = chat.send_message(message)
    return response.text

# Gradio Interface with new message format
with gr.Blocks() as demo:
    chatbot = gr.Chatbot(height=500, type="messages")
    msg = gr.Textbox(label="Message")
    clear = gr.Button("Clear")

    def respond(message, chat_history):
        bot_message = process_message(message)
        # Append user and bot messages
        chat_history.append({"role": "user", "content": message})
        chat_history.append({"role": "assistant", "content": bot_message})
        return "", chat_history

    msg.submit(respond, [msg, chatbot], [msg, chatbot])
    clear.click(lambda: None, None, chatbot, queue=False)

app = gr.mount_gradio_app(app, demo, path="/")

if __name__ == "__main__":
    port = int(os.getenv("PORT", 8000))
    uvicorn.run(app, host="0.0.0.0", port=port)