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

# ν™˜κ²½ λ³€μˆ˜μ—μ„œ API 토큰 κ°€μ Έμ˜€κΈ°
TOKEN = os.getenv("HUGGINGFACE_API_TOKEN")

# API 토큰이 μ„€μ •λ˜μ–΄ μžˆλŠ”μ§€ 확인
if not TOKEN:
    raise ValueError("API token is not set. Please set the HUGGINGFACE_API_TOKEN environment variable.")

# λŒ€ν™” 기둝을 κ΄€λ¦¬ν•˜λŠ” 큐 (μ΅œλŒ€ 10개의 λŒ€ν™” 기둝을 μœ μ§€)
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,
):
    # μ‹œμŠ€ν…œ λ©”μ‹œμ§€μ— 접두사 μΆ”κ°€
    system_prefix = "System: μž…λ ₯μ–΄μ˜ μ–Έμ–΄(μ˜μ–΄, ν•œκ΅­μ–΄, 쀑ꡭ어, 일본어 λ“±)에 따라 λ™μΌν•œ μ–Έμ–΄λ‘œ λ‹΅λ³€ν•˜λΌ."
    full_system_message = f"{system_prefix}{system_message}"

    # ν˜„μž¬ λŒ€ν™” λ‚΄μš©μ„ λ©”λͺ¨λ¦¬μ— μΆ”κ°€
    memory.append((message, None))

    messages = [{"role": "system", "content": full_system_message}]

    # λ©”λͺ¨λ¦¬μ—μ„œ λŒ€ν™” 기둝을 가져와 λ©”μ‹œμ§€ λͺ©λ‘μ— μΆ”κ°€
    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)
    
    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 μ˜μ—­λ§Œ 좜λ ₯
                if "choices" in response_json:
                    content = response_json["choices"][0]["message"]["content"]
                    response_text = content
                    # λ§ˆμ§€λ§‰ λŒ€ν™”μ— λͺ¨λΈμ˜ 응닡을 μΆ”κ°€ν•˜μ—¬ λ©”λͺ¨λ¦¬μ— μ €μž₯
                    memory[-1] = (message, response_text)
                    yield content
            except json.JSONDecodeError:
                continue  # μœ νš¨ν•˜μ§€ μ•Šμ€ JSON이 μžˆμ„ 경우 λ¬΄μ‹œν•˜κ³  λ‹€μŒ 청크둜 λ„˜μ–΄κ°

theme = "Nymbo/Nymbo_Theme"

# Gradio ChatInterface μ„€μ •
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)