app.py

import os
import requests
import gradio as gr

# -------------------------
# Configuration (edit here)
# -------------------------
# Option A (recommended): set an environment variable named OPENROUTER_API_KEY
# Option B: paste your key directly (not recommended for production)
API_KEY = os.getenv("Open_Router") or ""  # read from env
# If you prefer to paste manually, replace the line above with e.g.
# API_KEY = "sk-or-v1-your-openrouter-key-here"

if not API_KEY:
    raise ValueError(
        "OPENROUTER_API_KEY not found. "
        "Set it in your shell, or paste the key directly in the script (not recommended)."
    )

MODEL_URL = "https://openrouter.ai/api/v1/chat/completions"
HEADERS = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json",
}

# -------------------------
# Helper: call OpenRouter
# -------------------------
def query_gpt35(messages, max_tokens=500, temperature=0.7, timeout=30):
    """
    Send OpenAI-style messages to OpenRouter and return assistant text.
    messages: list of {"role": "...", "content": "..."}
    """
    payload = {
        "model": "openai/gpt-3.5-turbo",
        "messages": messages,
        "max_tokens": max_tokens,
        "temperature": temperature,
    }

    try:
        resp = requests.post(MODEL_URL, headers=HEADERS, json=payload, timeout=timeout)
        resp.raise_for_status()
        data = resp.json()
        # Support both typical "choices[0].message.content" and possible alternative formats
        if "choices" in data and len(data["choices"]) > 0:
            choice = data["choices"][0]
            # Typical OpenAI-style response:
            msg = choice.get("message", {}).get("content")
            if msg:
                return msg.strip()
            # Fall back to 'text' or other fields if present
            if "text" in choice:
                return choice["text"].strip()
        # fallback: try to find a top-level text
        if isinstance(data, dict) and "text" in data:
            return data["text"].strip()
        return "Error: Unexpected response format from API"
    except requests.exceptions.RequestException as e:
        return f"Error: Could not connect to the API - {e}"
    except ValueError:
        return "Error: Could not decode JSON response from API"

# -------------------------
# Gradio response function
# -------------------------
def respond(user_message, chat_history):
    """
    Gradio passes chat_history as a list of (user, bot) tuples, or None.
    Return updated history and an empty string to clear the input box.
    """
    if chat_history is None:
        chat_history = []

    # Build messages for the model
    messages = [
        {"role": "system", "content": "You are LocoBot, a helpful assistant. Answer concisely and politely."}
    ]

    # Re-add previous messages so model has context
    for user, bot in chat_history:
        messages.append({"role": "user", "content": user})
        messages.append({"role": "assistant", "content": bot})

    # Add current user message
    messages.append({"role": "user", "content": user_message})

    assistant_reply = query_gpt35(messages)

    # Append to history and return (and clear the input textbox)
    new_history = chat_history + [(user_message, assistant_reply)]
    return new_history, ""

# -------------------------
# Build and launch UI
# -------------------------
with gr.Blocks() as demo:
    gr.Markdown("## LocoBot — Your AI Companion (OpenRouter)")
    chatbot = gr.Chatbot()
    message = gr.Textbox(placeholder="Type your message and press Enter", lines=2)
    send = gr.Button("Send")

    send.click(fn=respond, inputs=[message, chatbot], outputs=[chatbot, message])
    message.submit(fn=respond, inputs=[message, chatbot], outputs=[chatbot, message])

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)