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import gradio as gr
import requests
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)

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": "meta-llama/Meta-Llama-3.1-70B-Instruct",
        "max_tokens": max_tokens,
        "temperature": temperature,
        "top_p": top_p,
        "messages": messages,
        "stream": True  # 스트리밍 모드 활성화
    }
    
    response = requests.post("https://api-inference.huggingface.co/v1/chat/completions", headers=headers, json=payload, stream=True)
    
    partial_words = ""
    for chunk in response.iter_lines():
        if chunk:
            chunk_data = chunk.decode('utf-8')
            if chunk_data.startswith("data: "):
                chunk_data = chunk_data[6:]  # "data: " 제거
            try:
                response_json = json.loads(chunk_data)
                if "choices" in response_json:
                    delta = response_json["choices"][0].get("delta", {})
                    if "content" in delta:
                        content = delta["content"]
                        partial_words += content
                        yield partial_words
            except json.JSONDecodeError:
                continue

theme = "Nymbo/Nymbo_Theme"

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

demo = gr.ChatInterface(
    css=css,
    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)