app.py

import os
import gradio as gr
import requests
import json

# API key
OPENROUTER_API_KEY = os.environ.get("OPENROUTER_API_KEY", "")

# Basic model list
MODELS = [
    ("Gemini Pro 2.0", "google/gemini-2.0-pro-exp-02-05:free"),
    ("Llama 3.2 Vision", "meta-llama/llama-3.2-11b-vision-instruct:free")
]

def format_to_message_dict(history):
    """Convert history to proper message format"""
    messages = []
    for pair in history:
        if len(pair) == 2:
            human, ai = pair
            if human:
                messages.append({"role": "user", "content": human})
            if ai:
                messages.append({"role": "assistant", "content": ai})
    return messages

def ask_ai(message, chatbot, model_choice):
    """Basic AI query function"""
    if not message.strip():
        return chatbot, ""
    
    # Get model ID
    model_id = MODELS[0][1]  # Default
    for name, model_id_value in MODELS:
        if name == model_choice:
            model_id = model_id_value
            break
    
    # Create messages from chatbot history
    messages = format_to_message_dict(chatbot)
    
    # Add current message
    messages.append({"role": "user", "content": message})
    
    # Call API
    try:
        response = requests.post(
            "https://openrouter.ai/api/v1/chat/completions",
            headers={
                "Content-Type": "application/json",
                "Authorization": f"Bearer {OPENROUTER_API_KEY}",
                "HTTP-Referer": "https://huggingface.co/spaces"
            },
            json={
                "model": model_id,
                "messages": messages,
                "temperature": 0.7,
                "max_tokens": 1000
            },
            timeout=60
        )
        
        if response.status_code == 200:
            result = response.json()
            ai_response = result.get("choices", [{}])[0].get("message", {}).get("content", "")
            chatbot = chatbot + [[message, ai_response]]
        else:
            chatbot = chatbot + [[message, f"Error: Status code {response.status_code}"]]
    except Exception as e:
        chatbot = chatbot + [[message, f"Error: {str(e)}"]]
    
    return chatbot, ""

def clear_chat():
    return [], ""

# Create minimal interface
with gr.Blocks() as demo:
    gr.Markdown("# Simple AI Chat")
    
    chatbot = gr.Chatbot(height=400)
    
    with gr.Row():
        message = gr.Textbox(
            placeholder="Type your message here...",
            label="Message",
            lines=2
        )
    
    with gr.Row():
        model_choice = gr.Radio(
            [name for name, _ in MODELS],
            value=MODELS[0][0],
            label="Model"
        )
        
    with gr.Row():
        submit_btn = gr.Button("Send")
        clear_btn = gr.Button("Clear Chat")
    
    # Set up events
    submit_btn.click(
        fn=ask_ai,
        inputs=[message, chatbot, model_choice],
        outputs=[chatbot, message]
    )
    
    message.submit(
        fn=ask_ai,
        inputs=[message, chatbot, model_choice],
        outputs=[chatbot, message]
    )
    
    clear_btn.click(
        fn=clear_chat,
        inputs=[],
        outputs=[chatbot, message]
    )

# Launch directly with Gradio's built-in server
if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)