app.py

import os
import gradio as gr
from openai import OpenAI
from dotenv import load_dotenv
import datetime
import tempfile

# Load environment variables from .env file (for local testing)
load_dotenv()

# Get API key from environment variables
OPENROUTER_API_KEY = os.environ.get("OPENROUTER_API_KEY")

# Initialize OpenAI client with OpenRouter base URL
client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key=OPENROUTER_API_KEY
)

# Permanent system prompt (your specific instructions)
SYSTEM_PROMPT = """You are an **AI Code Generator**. Your task is to **write complete, production-ready code** with no explanations unless explicitly asked. Follow these rules:

1. **Always prioritize code** over text. If the user asks for a solution, respond ONLY with:  
   - A full code block (with imports, error handling, and tests if applicable).  
   - Brief comments in the code (no paragraphs).  

2. **Never provide summaries, plans, or step-by-step guides** unless the user requests them with:  
   - "Explain..." or "How does this work?"  

3. **Assume technical proficiency**: Skip introductory notes (e.g., "Here's how to...")."""

# List of available models
AVAILABLE_MODELS = [
    "deepseek/deepseek-chat-v3-0324:free"
]

def generate_response(message, model_name, temperature=0.7, history=None):
    """Generate a response using the selected model via OpenRouter."""
    if not message:
        return "", []
    
    try:
        messages = [{"role": "system", "content": SYSTEM_PROMPT}]
        
        # Add conversation history if available
        if history:
            for user_msg, bot_msg in history:
                messages.append({"role": "user", "content": user_msg})
                messages.append({"role": "assistant", "content": bot_msg})
        
        # Add current message
        messages.append({"role": "user", "content": message})
        
        response = client.chat.completions.create(
            model=model_name,
            messages=messages,
            temperature=temperature
        )
        return response.choices[0].message.content
    except Exception as e:
        return f"Error: {str(e)}"

def save_chat_history(history):
    """Save chat history to a temporary file for download."""
    chat_text = f"System Prompt:\n{SYSTEM_PROMPT}\n\n"
    chat_text += "Chat History:\n\n"
    for user_msg, bot_msg in history:
        chat_text += f"User: {user_msg}\n"
        chat_text += f"Assistant: {bot_msg}\n\n"
    
    timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
    filename = f"code_generator_chat_{timestamp}.txt"
    
    temp_file = tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".txt")
    temp_file.write(chat_text)
    temp_file.close()
    
    return temp_file.name

with gr.Blocks(title="AI Code Generator") as demo:
    gr.Markdown("# AI Code Generator (via OpenRouter)")
    gr.Markdown("### System prompt is locked to code-generation mode")
    
    # Store chat history
    chat_history = gr.State([])
    download_file = gr.State(None)
    
    with gr.Row():
        with gr.Column(scale=3):
            model_dropdown = gr.Dropdown(
                choices=AVAILABLE_MODELS,
                value=AVAILABLE_MODELS[0],
                label="Select Model"
            )
            
            temperature_slider = gr.Slider(
                minimum=0.1,
                maximum=1.0,
                value=0.7,
                step=0.1,
                label="Temperature"
            )
    
    with gr.Row():
        with gr.Column(scale=4):
            chatbot = gr.Chatbot(height=400)
            user_input = gr.Textbox(
                label="Your Message",
                placeholder="Type your coding request here...",
                lines=3
            )
    
    with gr.Row():
        submit_btn = gr.Button("Generate Code", variant="primary")
        download_btn = gr.DownloadButton("Download Chat", visible=False)
        clear_btn = gr.ClearButton([user_input, chatbot])
    
    def respond(message, history, model_name, temperature):
        response = generate_response(message, model_name, temperature, history)
        updated_history = history + [(message, response)]
        file_path = save_chat_history(updated_history)
        return updated_history, updated_history, gr.DownloadButton(value=file_path, visible=True)
    
    submit_btn.click(
        respond,
        [user_input, chat_history, model_dropdown, temperature_slider],
        [chat_history, chatbot, download_btn]
    ).then(
        lambda: "", None, user_input
    )
    
    user_input.submit(
        respond,
        [user_input, chat_history, model_dropdown, temperature_slider],
        [chat_history, chatbot, download_btn]
    ).then(
        lambda: "", None, user_input
    )

demo.launch()