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

# ํ™˜๊ฒฝ ๋ณ€์ˆ˜์—์„œ API ํ† ํฐ ๊ฐ€์ ธ์˜ค๊ธฐ
TOKEN = os.getenv("HUGGINGFACE_API_TOKEN")

# API ํ† ํฐ์ด ์„ค์ •๋˜์–ด ์žˆ๋Š”์ง€ ํ™•์ธ
if not TOKEN:
    raise ValueError("API token is not set. Please set the HUGGINGFACE_API_TOKEN environment variable.")

# ๋Œ€ํ™” ๊ธฐ๋ก์„ ๊ด€๋ฆฌํ•˜๋Š” ํ (์ตœ๋Œ€ 10๊ฐœ์˜ ๋Œ€ํ™” ๊ธฐ๋ก์„ ์œ ์ง€)
memory = deque(maxlen=10)

def respond(
    message,
    history: list[tuple[str, str]],
    system_message="AI Assistant Role",
    max_tokens=512,
    temperature=0.7,
    top_p=0.95,
):
    # ์‹œ์Šคํ…œ ๋ฉ”์‹œ์ง€์— ์ ‘๋‘์‚ฌ ์ถ”๊ฐ€
    system_prefix = "System: ์ž…๋ ฅ์–ด์˜ ์–ธ์–ด(์˜์–ด, ํ•œ๊ตญ์–ด, ์ค‘๊ตญ์–ด, ์ผ๋ณธ์–ด ๋“ฑ)์— ๋”ฐ๋ผ ๋™์ผํ•œ ์–ธ์–ด๋กœ ๋‹ต๋ณ€ํ•˜๋ผ."
    full_system_message = f"{system_prefix}{system_message}"

    # ํ˜„์žฌ ๋Œ€ํ™” ๋‚ด์šฉ์„ ๋ฉ”๋ชจ๋ฆฌ์— ์ถ”๊ฐ€
    memory.append((message, None))

    messages = [{"role": "system", "content": full_system_message}]
    # ๋ฉ”๋ชจ๋ฆฌ์—์„œ ๋Œ€ํ™” ๊ธฐ๋ก์„ ๊ฐ€์ ธ์™€ ๋ฉ”์‹œ์ง€ ๋ชฉ๋ก์— ์ถ”๊ฐ€
    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": "meta-llama/Meta-Llama-3.1-405B-Instruct",
        "max_tokens": max_tokens,
        "temperature": temperature,
        "top_p": top_p,
        "messages": messages
    }
    response = requests.post("https://api-inference.huggingface.co/v1/chat/completions", headers=headers, json=payload, stream=True)
    
    # Stream ๋ฐฉ์‹์œผ๋กœ ๋ฐ์ดํ„ฐ๋ฅผ ์ถœ๋ ฅ
    response_text = ""
    for chunk in response.iter_content(chunk_size=None):
        if chunk:
            chunk_data = chunk.decode('utf-8')
            try:
                response_json = json.loads(chunk_data)
                # content ์˜์—ญ๋งŒ ์ถœ๋ ฅ
                if "choices" in response_json:
                    content = response_json["choices"][0]["message"]["content"]
                    response_text += content
                    yield response_text  # ๋ˆ„์ ๋œ ์‘๋‹ต์„ ์ŠคํŠธ๋ฆผ ๋ฐฉ์‹์œผ๋กœ ๋ฐ˜ํ™˜
            except json.JSONDecodeError:
                continue  # ์œ ํšจํ•˜์ง€ ์•Š์€ JSON์ด ์žˆ์„ ๊ฒฝ์šฐ ๋ฌด์‹œํ•˜๊ณ  ๋‹ค์Œ ์ฒญํฌ๋กœ ๋„˜์–ด๊ฐ

theme = "Nymbo/Nymbo_Theme"

# Gradio ChatInterface ์„ค์ •
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.queue().launch(max_threads=20)