Update app.py

app.py

@@ -1,64 +1,40 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# 使用 Hugging Face Inference API 调用云端模型（无需本地加载）
+client = InferenceClient(token="hf_your_token")
+
+def medical_chat(user_input, history):
+    # 构建医学对话 prompt
+    prompt = f"患者：{user_input}\n医生："
+    
+    # 调用云端模型（示例使用微软BioGPT）
+    response = client.text_generation(
+        prompt=prompt,
+        model="microsoft/BioGPT-Large",
+        max_new_tokens=150,
+        temperature=0.7,
+        repetition_penalty=1.2
+    )
+    
+    # 提取医生回复部分
+    doctor_response = response.split("医生：")[-1].strip()
+    
+    # 添加安全过滤
+    if "死亡" in doctor_response or "癌症" in doctor_response:
+        return "⚠️ 请及时联系线下医疗机构进行专业诊断！"
+    
+    return doctor_response
+
+# 构建 Gradio 界面
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🏥 在线医疗问诊系统 (AI版)")
+    gr.ChatInterface(
+        fn=medical_chat,
+        examples=["头痛三天了怎么办？", "接种疫苗后发烧正常吗？"],
+        title="症状咨询示例"
+    )
+
+# 启动应用（Hugging Face Spaces 会自动处理）
+demo.launch(debug=False)
 
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", 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.launch()