import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
import torch
import requests
import json
import time

def auto_refresh_sensor():
    while True:
        sensor_box.value = sensor_display_text()
        time.sleep(5)

        demo.load(auto_refresh_sensor, None, None)

model_id = "deepseek-ai/deepseek-coder-1.3b-base"
lora_id = "Seunggg/lora-plant"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)

base = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float32,  # Hugging Face Spaces 一般用 float32
    trust_remote_code=True
)

model = PeftModel.from_pretrained(
    base,
    lora_id,
    torch_dtype=torch.float32
)
model.eval()

from transformers import pipeline
pipe = pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
    max_new_tokens=256
)

def get_sensor_data():
    try:
        res = requests.get("https://arduino-realtime.onrender.com/api/data", timeout=5)
        sensor_data = res.json().get("sensorData", None)
        return sensor_data if sensor_data else {}
    except Exception as e:
        return {"错误": str(e)}

def sensor_display_text():
    sensor_data = get_sensor_data()
    return json.dumps(sensor_data, ensure_ascii=False, indent=2) if sensor_data else "暂无传感器数据"

def generate_answer(user_input):
    if not user_input.strip():
        return "请输入植物相关的问题 😊"
    prompt = f"用户提问：{user_input}\n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："
    try:
        result = pipe(prompt)
        output = result[0]["generated_text"]
        return output.replace(prompt, "").strip()
    except Exception as e:
        return f"生成建议时出错：{str(e)}"

def update_chart():
    sensor_data = get_sensor_data()
    if not sensor_data or "温度" not in sensor_data:
        return gr.LinePlot.update(value=None)
    return {
        "data": [
            {"x": [0], "y": [sensor_data.get("温度", 0)], "name": "温度"},
            {"x": [0], "y": [sensor_data.get("湿度", 0)], "name": "湿度"}
        ],
        "layout": {"title": "实时传感器数据"}
    }

# 在 Blocks 里这样写：
with gr.Blocks() as demo:
    gr.Markdown("# 🌱 植物助手 - 实时传感器联动")

    with gr.Row():
        sensor_box = gr.Textbox(label="🧪 当前传感器数据", lines=6, interactive=False)
        chart = gr.LinePlot(label="📈 实时数据图表", x="x", y="y", overlay=True)

    question = gr.Textbox(label="🌿 植物问题", lines=4, placeholder="请输入植物相关的问题 😊")
    answer_box = gr.Textbox(label="🤖 回答建议", lines=8, interactive=False)
    send_btn = gr.Button("发送")
    send_btn.click(fn=generate_answer, inputs=question, outputs=answer_box)
    # 启动后台线程更新数据
    demo.launch()