Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| import requests | |
| # 设置第三方 API 基本 URL | |
| API_BASE_URL = "http://key.aistory.uk/v1/chat/completions" # 替换为正确的API URL | |
| API_KEY = "sk-HfD4NYIN6bq2DkSfIiUcciRvo9MkgMdFCsahP9NWEOUPHe8H" # 替换为你自己的 API 密钥 | |
| # 定义 AI 响应函数，调用第三方 API | |
| def ai_response(message, chat_history): | |
| # 定义系统提示词 | |
| system_prompt = "You are a helpful assistant. Please assist the user with their inquiries." | |
| # 组合历史聊天记录和用户输入的信息 | |
| conversation = [{"role": "system", "content": system_prompt}] | |
| for msg in chat_history: | |
| conversation.append({"role": msg[0], "content": msg[1]}) | |
| conversation.append({"role": "user", "content": message}) | |
| # 构建请求体 | |
| payload = { | |
| "model": "gpt-4o", # 使用 gpt-4o 模型（如果此模型为该 API 支持的模型） | |
| "messages": conversation, | |
| "max_tokens": 150 | |
| } | |
| # 设置请求头，包括 API 密钥 | |
| headers = { | |
| "Authorization": f"Bearer {API_KEY}", | |
| "Content-Type": "application/json" | |
| } | |
| # 发送请求到第三方 API | |
| try: | |
| response = requests.post(API_BASE_URL, json=payload, headers=headers) | |
| response.raise_for_status() # 如果响应状态码不是 2xx，会抛出异常 | |
| if response.status_code == 200: | |
| # 获取 API 响应内容 | |
| response_data = response.json() | |
| assistant_message = response_data['choices'][0]['message']['content'] | |
| # 返回新的聊天记录，转换为符合 gr.Chatbot 期望的元组格式 | |
| chat_history.append(("user", message)) | |
| chat_history.append(("assistant", assistant_message)) | |
| return chat_history | |
| else: | |
| # 如果请求失败，输出错误信息 | |
| return chat_history + [("assistant", f"API error: {response.status_code}, {response.text}")] | |
| except requests.exceptions.RequestException as e: | |
| # 捕获任何请求错误，并输出详细错误信息 | |
| return chat_history + [("assistant", f"Request failed: {str(e)}")] | |
| # 创建 Gradio 应用 | |
| def create_interface(): | |
| with gr.Blocks() as demo: | |
| # 页面标题 | |
| gr.Markdown("<h1 style='text-align: center; color: #4CAF50;'>AI驱动的孕产期用药咨询系统</h1>") | |
| # 创建一个 Column 布局，用于将聊天记录和输入框放在同一列 | |
| with gr.Column(): | |
| # 创建一个聊天机器人输出组件，用于显示对话 | |
| chat_output = gr.Chatbot() | |
| # 创建一个文本框用于输入消息 | |
| message_input = gr.Textbox(label="请输入你的问题", placeholder="输入你的问题并按回车发送", lines=1) | |
| # 提交按钮，发送用户消息并获取AI回复 | |
| message_input.submit(ai_response, inputs=[message_input, chat_output], outputs=[chat_output]) | |
| return demo | |
| # 启动 Gradio 应用 | |
| demo = create_interface() | |
| demo.launch() | |