Update app.py

app.py

@@ -42,44 +42,67 @@ pipe = pipeline(
 
 from ask_api import ask_with_sensor  # 引入调用函数
 
-def respond(user_input):
-    if not user_input.strip():
-        return "暂无传感器数据", "请输入植物相关的问题 😊"
-
-    # 获取 Render 实时传感器数据
+def get_sensor_data():
     try:
         sensor_response = requests.get("https://arduino-realtime.onrender.com/api/data", timeout=5)
         sensor_data = sensor_response.json().get("sensorData", None)
         sensor_display = json.dumps(sensor_data, ensure_ascii=False, indent=2) if sensor_data else "暂无传感器数据"
     except Exception as e:
         sensor_display = "⚠️ 获取失败：" + str(e)
-        sensor_data = None
+    return sensor_display
 
-    # 构建提示词
-    prompt = f"用户提问：{user_input}\n"
-    if sensor_data:
-        prompt += f"当前传感器数据：{json.dumps(sensor_data, ensure_ascii=False)}\n"
-    prompt += "请用更人性化的语言生成建议，并推荐相关植物文献或资料。\n回答："
+    def show_sensor_data(_=None):
+    return get_sensor_data()
+
+def respond(user_input):
+    sensor_display = get_sensor_data()
+    if not user_input.strip():
+        return sensor_display, "请输入植物相关的问题 😊"
 
-    # 模型生成
+    prompt = f"用户提问：{user_input}\n"
     try:
+        sensor_response = requests.get("https://arduino-realtime.onrender.com/api/data", timeout=5)
+        sensor_data = sensor_response.json().get("sensorData", None)
+        if sensor_data:
+            prompt += f"当前传感器数据：{json.dumps(sensor_data, ensure_ascii=False)}\n"
+        prompt += "请用更人性化的语言生成建议，并推荐相关植物文献或资料。\n回答："
+
         result = pipe(prompt)
-        answer = result[0]["generated_text"]
+        full_output = result[0]["generated_text"]
+        answer = full_output.replace(prompt, "").strip()
     except Exception as e:
         answer = f"生成建议时出错：{str(e)}"
 
     return sensor_display, answer
 
+    # 构建提示词
+    prompt = f"用户提问：{user_input}\n"
+    if sensor_data:
+        prompt += f"当前传感器数据：{json.dumps(sensor_data, ensure_ascii=False)}\n"
+    prompt += "请用更人性化的语言生成建议，并推荐相关植物文献或资料。\n回答："
+
+ # 模型生成
+try:
+    result = pipe(prompt)
+    full_output = result[0]["generated_text"]
+    # 删除重复的提问部分，只保留回答段
+    answer = full_output.replace(prompt, "").strip()
+except Exception as e:
+    answer = f"生成建议时出错：{str(e)}"
+
 # Gradio 界面
-gr.Interface(
-    fn=respond,
-    inputs=gr.Textbox(lines=4, label="植物问题"),
-    outputs=[
-        gr.Textbox(label="🧪 当前传感器数据", lines=6, interactive=False),
-        gr.Textbox(label="🤖 回答建议", lines=8, interactive=False)
-    ],
-    title="🌱 植物助手 - 实时联动版",
-    description="结合 Render 实时传感器数据 + 本地 LoRA 模型，生成更合理建议。"
-).launch()
+with gr.Blocks() as demo:
+    with gr.Row():
+        sensor_box = gr.Textbox(label="🧪 当前传感器数据", lines=6, interactive=False)
+        question_box = gr.Textbox(label="🌿 植物问题", lines=4)
+    answer_box = gr.Textbox(label="🤖 回答建议", lines=8, interactive=False)
+
+    # 实时轮询，每 2 秒自动更新
+    sensor_box.change(fn=show_sensor_data, inputs=None, outputs=sensor_box).every(2)
+
+    # 用户提问后，更新传感器 + 回答
+    question_box.submit(fn=respond, inputs=question_box, outputs=[sensor_box, answer_box])
+
+demo.launch()