app.py

import gradio as gr
from transformers import Conversation, pipeline

# 创建聊天机器人pipeline，使用你的 api key
chatbot_pipeline = pipeline("conversational", model="Llama-2-70b-chat-hf", use_auth_token="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")

def chatbot_response(input_text, history=[]):
    # 添加新的用户输入到对话历史
    history.append(input_text)
    
    # 使用 Hugging Face's Conversation API 创建对话
    conversation = Conversation(input_text)
    
    # 获取模型的回答
    responses = chatbot_pipeline([conversation])
    model_response = responses[-1].generated_responses[-1]
    
    # 添加模型的回答到对话历史
    history.append(model_response)

    # 创建用于显示在 Gradio UI 的聊天历史
    chat_log = [(u,b) for u,b in zip(history[::2], history[1::2])]

    return chat_log, history

# 创建 Gradio 接口
iface = gr.Interface(
    fn=chatbot_response, 
    inputs=gr.inputs.Textbox(lines=2, placeholder='Type a message...'), 
    outputs=[gr.outputs.Textbox(label="Chat History"), gr.outputs.Textbox(label="Chat Log")]
)

# 启动 Gradio 应用
iface.launch()