| import os, gradio as gr, openai | |
| openai.api_key = os.getenv("DEEPSEEK_API_KEY") | |
| def analyze_env(temperature, light, soil_humidity): | |
| msg = [ | |
| {"role": "system", "content": "You are a plant care assistant."}, | |
| {"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" | |
| ) | |
| demo.launch() | |