import os
import requests
import gradio as gr

HUGGINGFACE_API_TOKEN = os.getenv("HUGGINGFACE_API_TOKEN")
MODEL_NAME = "deepseek-ai/DeepSeek-Coder-V2-Instruct"  # ✅ 直接可用的免费模型

def query_huggingface_api(prompt):
    API_URL = f"https://api-inference.huggingface.co/models/{MODEL_NAME}"
    headers = {"Authorization": f"Bearer {HUGGINGFACE_API_TOKEN}"}
    
    payload = {
        "inputs": prompt,
        "parameters": {"max_length": 150, "temperature": 0.7}
    }
    
    response = requests.post(API_URL, headers=headers, json=payload)
    
    if response.status_code == 200:
        return response.json()[0]["generated_text"]
    else:
        return f"API Error: {response.status_code} - {response.text}"

# ✅ Gradio 界面
with gr.Blocks() as demo:
    gr.Markdown("# 🤖 免费 Hugging Face AI Chatbot")
    chatbot = gr.Chatbot()
    msg = gr.Textbox(placeholder="请输入你的问题...", lines=2)
    send = gr.Button("发送")
    clear = gr.Button("清除")

    chat_history = []

    def chat(query, chat_history):
        response = query_huggingface_api(query)
        chat_history.append((query, response))
        return "", chat_history

    send.click(chat, [msg, chatbot], [msg, chatbot], queue=False)
    msg.submit(chat, [msg, chatbot], [msg, chatbot], queue=False)
    clear.click(lambda: None, None, chatbot, queue=False)

demo.launch()