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import os |
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from openai import OpenAI |
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import gradio as gr |
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OpenAI.api_key = os.getenv("OPENAI_API_KEY") |
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api_key = os.getenv("OPENAI_API_KEY") |
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client = OpenAI(api_key=api_key) |
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def predict(message, history): |
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history_openai_format = [] |
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history_openai_format.append({"role": "assistant", "content":"你是一个专业的中国心理咨询师与心理陪伴师，你的所有内容都需要用【中文】回答，你必须对你的患者耐心，你需要以【朋友】的身份和患者交流，这意味着你需要用更加【口语化】的文字回答，并且【不要长篇大论】，更【不要分点作答】。可以偶尔针对用户的回答进行【提问】，并给予必要的【建议和引导】。"}) |
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for human, assistant in history: |
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history_openai_format.append({"role": "user", "content": human }) |
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history_openai_format.append({"role": "assistant", "content":assistant}) |
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history_openai_format.append({"role": "user", "content": message}) |
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response = client.chat.completions.create(model='gpt-3.5-turbo', |
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messages= history_openai_format, |
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temperature=1.0, |
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stream=True) |
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partial_message = "" |
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for chunk in response: |
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if chunk.choices[0].delta.content is not None: |
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partial_message = partial_message + chunk.choices[0].delta.content |
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yield partial_message |
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chat=gr.ChatInterface( |
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predict, |
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chatbot=gr.Chatbot( |
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height=400, |
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bubble_full_width=False, |
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avatar_images=(os.path.join(os.path.dirname(__file__), "patient_ava.png"), os.path.join(os.path.dirname(__file__), "docter_ava.png")), |
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likeable=True, |
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), |
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retry_btn="🔄重新生成", |
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undo_btn="↩️撤回信息", |
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clear_btn="🗑️清空信息", |
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stop_btn="停止生成", |
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submit_btn="发送", |
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) |
