app.py

import gradio as gr
import openai
import base64
import os
# ✅ 輸入你的 OpenAI API 金鑰
openai.api_key = os.environ.get("OPENAI_API_KEY")

# ✅ 圖片轉 base64
def image_to_base64(image_path):
    with open(image_path, "rb") as img_file:
        return base64.b64encode(img_file.read()).decode("utf-8")

# ✅ GPT-4o 分析餐點圖片
def analyze_diet(image_path, goal, gender, age):
    try:
        img_b64 = image_to_base64(image_path)
        messages = [
            {
                "role": "user",
                "content": [
                    {
                        "type": "text",
                        "text": f"這是使用者的餐點圖片。性別：{gender}，年齡：{age} 歲，目標：{goal}。請根據圖片中的內容，給出健康分析與一句鼓勵話。格式如下：\n建議：...\n鼓勵：..."
                    },
                    {
                        "type": "image_url",
                        "image_url": {
                            "url": f"data:image/jpeg;base64,{img_b64}"
                        }
                    }
                ]
            }
        ]

        response = openai.ChatCompletion.create(
            model="gpt-4o",
            messages=messages,
            temperature=0.7
        )
        result = response.choices[0].message.content.strip()

        if "建議：" in result and "鼓勵：" in result:
            suggestion = result.split("建議：")[1].split("鼓勵：")[0].strip()
            encouragement = result.split("鼓勵：")[1].strip()
        else:
            suggestion = result
            encouragement = "你的飲食選擇很棒！繼續保持～"

        return suggestion, encouragement

    except Exception as e:
        return "❌ 分析失敗：" + str(e), ""

# ✅ 運動分析（仍為文字輸入）
def analyze_workout(text, goal, gender, age):
    prompt = f"""
你是一位健身教練，使用者性別為 {gender}，年齡 {age} 歲，目標是「{goal}」。
以下是他的運動紀錄：
{text}
請給出運動分析與一句鼓勵話，格式如下：
建議：...
鼓勵：...
"""
    try:
        response = openai.ChatCompletion.create(
            model="gpt-4o",
            messages=[
                {"role": "system", "content": "你是一位健身教練"},
                {"role": "user", "content": prompt}
            ],
            temperature=0.7
        )
        result = response.choices[0].message.content.strip()

        if "建議：" in result and "鼓勵：" in result:
            suggestion = result.split("建議：")[1].split("鼓勵：")[0].strip()
            encouragement = result.split("鼓勵：")[1].strip()
        else:
            suggestion = result
            encouragement = "保持運動習慣，健康就靠你！"

        return suggestion, encouragement

    except Exception as e:
        return "❌ 分析失敗：" + str(e), ""

# ✅ Gradio UI
with gr.Blocks() as health_ai:
    gr.Markdown("# 🧠 我的健康管家 AI")
    gr.Markdown("上傳你的餐點圖片或輸入運動內容，AI 幫你分析健康狀況並給鼓勵 💪")

    with gr.Tabs():
        with gr.Tab("🍱 飲食分析（圖片）"):
            diet_input = gr.Image(label="上傳你的餐點圖片", type="filepath")
            diet_goal = gr.Radio(["減脂", "增肌", "維持體態"], label="你的目標")
            diet_gender = gr.Radio(["男", "女"], label="你的性別")
            diet_age = gr.Textbox(label="你的年齡", placeholder="例如：22")
            diet_button = gr.Button("開始分析")
            diet_output = gr.Textbox(label="AI 分析建議")
            diet_encourage = gr.Textbox(label="AI 鼓勵語")

        with gr.Tab("🏃‍♂️ 運動分析（文字）"):
            workout_input = gr.Textbox(lines=5, placeholder="例如：慢跑30分鐘，核心訓練15分鐘...")
            workout_goal = gr.Radio(["減脂", "增肌", "維持體態"], label="你的目標")
            workout_gender = gr.Radio(["男", "女"], label="你的性別")
            workout_age = gr.Textbox(label="你的年齡", placeholder="例如：22")
            workout_button = gr.Button("開始分析")
            workout_output = gr.Textbox(label="AI 評估與建議")
            workout_encourage = gr.Textbox(label="AI 鼓勵語")

    diet_button.click(analyze_diet,
                      inputs=[diet_input, diet_goal, diet_gender, diet_age],
                      outputs=[diet_output, diet_encourage])

    workout_button.click(analyze_workout,
                         inputs=[workout_input, workout_goal, workout_gender, workout_age],
                         outputs=[workout_output, workout_encourage])

health_ai.launch()