Update app.py

app.py

@@ -1,15 +1,46 @@
-import os, gradio as gr, openai
-openai.api_key = os.getenv("DEEPSEEK_API_KEY")
-def analyze_env(temperature, light, soil_humidity):
-    msg = [
+import os, gradio as gr
+from openai import OpenAI
+
+# 初始化 DeepSeek 客户端
+client = OpenAI(
+    api_key=os.getenv("DEEPSEEK_API_KEY"),
+    base_url="https://api.deepseek.com/v1"
+)
+
+def analyze_stream(temperature, light, soil_humidity):
+    """
+    接收三个环境数据指标，调用 DeepSeek chat 模型进行流式分析。
+    将生成的 token 实时 yield 回前端。
+    """
+    messages = [
         {"role": "system", "content": "You are a plant care assistant."},
-        {"role": "user", "content": f"Temperature: {temperature}°C, Light: {light} lux, Soil Humidity: {soil_humidity}%."}
+        {"role": "user", "content": 
+            f"Temperature: {temperature}°C, Light: {light} lux, Soil Humidity: {soil_humidity}%."}
     ]
-    resp = openai.ChatCompletion.create(model="deepseek-chat", messages=msg, temperature=0.7)
-    return resp.choices[0].message.content
-demo = gr.Interface(fn=analyze_env,
-    inputs=[gr.Number(label="Temperature (°C)"), gr.Number(label="Light (lux)"), gr.Number(label="Soil Humidity (%)")],
-    outputs="text",
-    title="植物环境分析"
+    stream = client.chat.completions.create(
+        model="deepseek-chat",
+        messages=messages,
+        temperature=0.7,
+        stream=True
+    )
+    partial = ""
+    for chunk in stream:
+        delta = chunk.choices[0].delta.content or ""
+        partial += delta
+        yield partial  # 持续输出拼接中的内容
+
+# 定义 Gradio 界面
+demo = gr.Interface(
+    fn=analyze_stream,
+    inputs=[
+        gr.Number(label="Temperature (°C)"),
+        gr.Number(label="Light (lux)"),
+        gr.Number(label="Soil Humidity (%)")
+    ],
+    outputs=gr.Textbox(label="DeepSeek 分析结果"),
+    title="🌱 实时植物环境分析",
+    description="输入当前环境参数后，系统将流式返回 DeepSeek 的分析建议。",
 )
-demo.launch()
+
+# 启用 Gradio 的队列和流式输出
+demo.queue(concurrency_count=2).launch(server_name="0.0.0.0")