app.py

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

TOKEN = os.getenv("HUGGINGFACE_API_TOKEN")

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

memory = deque(maxlen=10)

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: 입력어의 언어(영어, 한국어, 중국어, 일본어 등)에 따라 동일한 언어로 답변하라."
    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
    }

    async with aiohttp.ClientSession() as session:
        async with session.post("https://api-inference.huggingface.co/v1/chat/completions", headers=headers, json=payload) as response:
            try:
                async for chunk in response.content:
                    if chunk:
                        chunk_data = chunk.decode('utf-8')
                        response_json = json.loads(chunk_data)
                        if "choices" in response_json:
                            content = response_json["choices"][0]["message"]["content"]
                            yield content
            except json.JSONDecodeError:
                # Log the error or handle it appropriately
                pass
            except StopAsyncIteration:
                # Handle the case where the stream is prematurely terminated
                pass
            finally:
                # Ensure that the generator is properly closed
                yield "Stream ended"

theme = "Nymbo/Nymbo_Theme"

demo = gr.ChatInterface(
    fn=respond,
    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__":
    demo.launch()