app.py

import gradio as gr
import requests
import os

API_KEY = os.environ.get("PLANTNET_API_KEY")
PROJECT = "all"
API_URL = f"https://my-api.plantnet.org/v2/identify/{PROJECT}?api-key={API_KEY}"


def identify_plant(image, organ):
    if not API_KEY:
        return "⚠️ 未检测到 API Key，请检查 Space 的 Secrets 配置"
    if image is None:
        return "请先上传一张植物照片"
    try:
        with open(image, "rb") as f:
            files = [("images", ("image.jpg", f, "image/jpeg"))]
            data = {"organs": [organ]}
            response = requests.post(API_URL, files=files, data=data, timeout=20)
    except requests.exceptions.Timeout:
        return "请求超时，请稍后重试"
    except requests.exceptions.RequestException as e:
        return f"网络请求失败：{e}"

    if response.status_code == 401:
        return "❌ API Key 无效或已过期"
    elif response.status_code == 429:
        return "⚠️ 已超出当日调用配额"
    elif response.status_code != 200:
        return f"识别失败，状态码：{response.status_code}"

    result = response.json()
    results = result.get("results", [])
    if not results:
        return "未识别到匹配物种，建议换一张更清晰的照片重试"

    output = []
    for i, r in enumerate(results[:5], start=1):
        name = r["species"]["scientificNameWithoutAuthor"]
        family = r["species"].get("family", {}).get("scientificNameWithoutAuthor", "")
        common_names = r["species"].get("commonNames", [])
        common = "、".join(common_names[:2]) if common_names else "暂无常用名"
        score = r["score"]
        output.append(f"**{i}. {name}**（{family}）\n常用名：{common}　置信度：{score:.1%}")

    return "\n\n---\n\n".join(output)


with gr.Blocks(title="植物识别助手") as demo:
    gr.Markdown("# 🌿 植物识别助手\n上传一张植物照片，识别引擎来自 [Pl@ntNet](https://plantnet.org)")
    with gr.Row():
        with gr.Column():
            image_input = gr.Image(type="filepath", label="上传植物照片")
            organ_input = gr.Dropdown(
                choices=["auto", "leaf", "flower", "fruit", "bark", "habit"],
                value="auto",
                label="拍摄部位",
                info="明确指定部位（如leaf/flower）通常比auto识别更准确"
            )
            submit_btn = gr.Button("开始识别", variant="primary")
        with gr.Column():
            output_text = gr.Markdown(label="识别结果")

    submit_btn.click(fn=identify_plant, inputs=[image_input, organ_input], outputs=output_text)
    gr.Markdown("---\n数据与识别能力来自 Pl@ntNet 官方 API，遵循 CC BY-SA / CC BY 授权协议。识别结果仅供参考。")

demo.launch(server_name="0.0.0.0", server_port=7860)