import gradio as gr
import aiohttp
import os
import json
from collections import deque
import asyncio

TOKEN = os.getenv("HUGGINGFACE_API_TOKEN")

if not TOKEN:
    raise ValueError("API token is not set. Please set the HUGGINGFACE_API_TOKEN environment variable.")

print(f"API Token: {TOKEN[:5]}...{TOKEN[-5:]}")  # Check API token

memory = deque(maxlen=10)

async def test_api():
    headers = {"Authorization": f"Bearer {TOKEN}"}
    async with aiohttp.ClientSession() as session:
        async with session.get("https://api-inference.huggingface.co/models/mistralai/Mistral-Nemo-Instruct-2407", headers=headers) as response:
            print(f"Test API response: {await response.text()}")

async def respond(
    message,
    history: list[tuple[str, str]],
    system_message="AI Assistant Role",
    max_tokens=512,
    temperature=0.7,
    top_p=0.95,
):
    system_prefix = "System: Respond in the same language as the input (English, Korean, Chinese, Japanese, etc.)."
    full_system_message = f"{system_prefix}{system_message}"

    memory.append((message, None))
    messages = [{"role": "system", "content": full_system_message}]
    for val in memory:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    headers = {
        "Authorization": f"Bearer {TOKEN}",
        "Content-Type": "application/json"
    }
    payload = {
        "model": "mistralai/Mistral-Nemo-Instruct-2407",
        "max_tokens": max_tokens,
        "temperature": temperature,
        "top_p": top_p,
        "messages": messages,
        "stream": True
    }

    try:
        async with aiohttp.ClientSession() as session:
            async with session.post("https://api-inference.huggingface.co/v1/chat/completions", headers=headers, json=payload) as response:
                print(f"Response status: {response.status}")
                if response.status != 200:
                    error_text = await response.text()
                    print(f"Error response: {error_text}")
                    yield "An API response error occurred. Please try again."
                    return

                response_text = ""
                async for chunk in response.content:
                    if chunk:
                        try:
                            chunk_data = chunk.decode('utf-8')
                            response_json = json.loads(chunk_data)
                            if "choices" in response_json:
                                content = response_json["choices"][0]["message"]["content"]
                                response_text += content
                                yield response_text
                        except json.JSONDecodeError:
                            continue
                
                if not response_text:
                    yield "I apologize, but I couldn't generate a response. Please try again."
    except Exception as e:
        print(f"Exception occurred: {str(e)}")
        yield f"An error occurred: {str(e)}"

    memory[-1] = (message, response_text)

async def chat(message, history, system_message, max_tokens, temperature, top_p):
    response = ""
    try:
        async for chunk in respond(message, history, system_message, max_tokens, temperature, top_p):
            response = chunk
            yield response
    except Exception as e:
        print(f"Chat function error: {str(e)}")
        yield f"An error occurred in the chat function: {str(e)}"

theme = "Nymbo/Nymbo_Theme"

css = """
footer {
    visibility: hidden;
}
"""

demo = gr.ChatInterface(
    css=css,
    fn=chat,
    theme=theme,
    additional_inputs=[
        gr.Textbox(value="AI Assistant Role", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
    ]
)

if __name__ == "__main__":
    asyncio.run(test_api())  # Run API test
    demo.queue().launch(max_threads=20, show_error=True)