Update app.py
Browse files
app.py
CHANGED
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@@ -20,7 +20,7 @@ from deepface import DeepFace
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warnings.filterwarnings("ignore")
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# ==========================================
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#
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# ==========================================
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GROQ_API_KEY = os.getenv("GROQ_API_KEY")
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HF_TOKEN = os.getenv("HF_TOKEN")
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@@ -86,7 +86,7 @@ if not df.empty and 'RAG_Content' in df.columns:
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print(f"⚠️ RAG 初始化失敗: {e}")
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# ==========================================
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#
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# ==========================================
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def get_restaurant_data(mood_score_str, food_choice):
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@@ -208,7 +208,7 @@ def mood_agent_logic(score_input, food_input, diary_input, debug_mode):
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yield final_response, image_output, map_html
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# ==========================================
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#
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# ==========================================
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# 定義中文字典 (繪圖用)
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@@ -231,10 +231,23 @@ def putText(img, x, y, text, size=50, color=(255, 255, 255)):
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except:
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return img
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#
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def
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detected_emotion = "neutral"
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mapped_score = "3 (普通)"
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@@ -248,7 +261,7 @@ def detect_emotion_and_map(frame):
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# 2. 畫在圖片上
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frame = putText(frame, 20, 40, detected_emotion)
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# 3.
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if detected_emotion == 'happy':
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mapped_score = "5 (超棒)"
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elif detected_emotion == 'surprise':
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@@ -261,17 +274,19 @@ def detect_emotion_and_map(frame):
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mapped_score = "1 (心情差)"
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except Exception as e:
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print(f"DeepFace Error: {e}")
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pass
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return frame, mapped_score
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# ==========================================
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#
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# ==========================================
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with gr.Blocks(title="AI 心情食堂") as demo:
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with gr.Column(visible=True) as main_app_col:
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gr.Markdown(f"## 🍱 AI 心情食堂導航")
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gr.Markdown("請看著鏡頭,讓 AI 幫你判斷今天的心情分數!")
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@@ -280,23 +295,20 @@ with gr.Blocks(title="AI 心情食堂") as demo:
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# 左側:輸入區
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with gr.Column(scale=1):
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# ★ 修改重點:將鏡頭與結果分開顯示 ★
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gr.Markdown("### 📸 步驟 1:心情偵測 (選用)")
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# 這裡用 Row 把兩個影像並排 (左邊鏡頭,右邊截圖)
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with gr.Row():
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# 左邊:
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webcam_input = gr.Image(sources=["webcam"], label="即時鏡頭
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captured_image = gr.Image(label="偵測結果截圖", interactive=False)
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gr.Markdown("### 📝 步驟 2:確認與補充")
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score_input = gr.Radio(
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["1 (心情差)", "2 (不太好)", "3 (普通)", "4 (不錯)", "5 (超棒)"],
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label="1. 心情分數 (AI
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value="3 (普通)"
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)
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food_input = gr.Radio(["吃飯", "吃麵", "隨便"], label="2. 想吃什麼", value="隨便")
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@@ -305,7 +317,7 @@ with gr.Blocks(title="AI 心情食堂") as demo:
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debug_mode_btn = gr.Checkbox(label="🔧 顯示 Prompt 除錯資訊", value=False)
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submit_btn = gr.Button("🚀 送出給 Agent", variant="primary")
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# 右側:Agent 輸出區
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with gr.Column(scale=1):
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agent_output = gr.Markdown(label="AI 回應")
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image_output = gr.Image(label="AI 推薦美食圖", type="pil", width=400)
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@@ -313,11 +325,19 @@ with gr.Blocks(title="AI 心情食堂") as demo:
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# Events
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# ★
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detect_btn.click(
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fn=
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inputs=[
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outputs=[
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)
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# 提交按鈕
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warnings.filterwarnings("ignore")
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# ==========================================
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# 環境變數與 RAG 初始化
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# ==========================================
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GROQ_API_KEY = os.getenv("GROQ_API_KEY")
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HF_TOKEN = os.getenv("HF_TOKEN")
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print(f"⚠️ RAG 初始化失敗: {e}")
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# ==========================================
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# 核心功能函式 (餐廳推薦邏輯)
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# ==========================================
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def get_restaurant_data(mood_score_str, food_choice):
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yield final_response, image_output, map_html
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# ==========================================
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# [修改] 情緒辨識整合模組
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# ==========================================
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# 定義中文字典 (繪圖用)
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except:
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return img
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# ★ 新增:按鈕切換函式 (控制按鈕的文字與顏色)
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def toggle_recording(is_recording):
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# 切換狀態 (True <-> False)
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new_state = not is_recording
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if new_state:
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# 如果變成錄製中,按鈕變成紅色「停止」
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return new_state, gr.Button(value="🛑 停止錄製 (鎖定結果)", variant="stop")
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else:
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# 如果變成停止,按鈕變成綠色「開始」
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return new_state, gr.Button(value="📸 開始即時偵測", variant="secondary")
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# ★ 修改:偵測邏輯 (加入 is_recording 判斷)
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def detect_emotion_stream(frame, is_recording):
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# 如果沒有在錄製,或是沒有畫面,就什麼都不更新 (讓畫面凍結在最後一幀)
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if not is_recording or frame is None:
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return gr.update(), gr.update()
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detected_emotion = "neutral"
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mapped_score = "3 (普通)"
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# 2. 畫在圖片上
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frame = putText(frame, 20, 40, detected_emotion)
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# 3. 分數轉換
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if detected_emotion == 'happy':
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mapped_score = "5 (超棒)"
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elif detected_emotion == 'surprise':
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mapped_score = "1 (心情差)"
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except Exception as e:
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pass
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return frame, mapped_score
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# ==========================================
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# Gradio 介面建構 (修改版)
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# ==========================================
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with gr.Blocks(title="AI 心情食堂") as demo:
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# ★ 1. 定義一個變數來記錄狀態 (預設是 False 停止中)
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recording_state = gr.State(value=False)
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with gr.Column(visible=True) as main_app_col:
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gr.Markdown(f"## 🍱 AI 心情食堂導航")
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gr.Markdown("請看著鏡頭,讓 AI 幫你判斷今天的心情分數!")
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# 左側:輸入區
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with gr.Column(scale=1):
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gr.Markdown("### 📸 步驟 1:心情偵測 (選用)")
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with gr.Row():
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# 左邊:即時鏡頭
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webcam_input = gr.Image(sources=["webcam"], label="即時鏡頭", streaming=True)
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# 右邊:結果畫面 (互動模式設為 False)
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captured_image = gr.Image(label="即時偵測結果", interactive=False)
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# 按鈕預設為「開始」
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detect_btn = gr.Button("📸 開始即時偵測", variant="secondary")
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gr.Markdown("### 📝 步驟 2:確認與補充")
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score_input = gr.Radio(
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["1 (心情差)", "2 (不太好)", "3 (普通)", "4 (不錯)", "5 (超棒)"],
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label="1. 心情分數 (AI 自���填入)",
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value="3 (普通)"
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)
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food_input = gr.Radio(["吃飯", "吃麵", "隨便"], label="2. 想吃什麼", value="隨便")
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debug_mode_btn = gr.Checkbox(label="🔧 顯示 Prompt 除錯資訊", value=False)
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submit_btn = gr.Button("🚀 送出給 Agent", variant="primary")
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# 右側:Agent 輸出區
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with gr.Column(scale=1):
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agent_output = gr.Markdown(label="AI 回應")
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image_output = gr.Image(label="AI 推薦美食圖", type="pil", width=400)
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# Events
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# ★ 事件 1:按鈕點擊 -> 切換錄製狀態 -> 更新按鈕樣子
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detect_btn.click(
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fn=toggle_recording,
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inputs=[recording_state],
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outputs=[recording_state, detect_btn]
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)
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# ★ 事件 2:鏡頭串流 (Stream) -> 只要鏡頭有畫面就會觸發
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# 它會檢查 recording_state,如果是 True 才會更新右邊的圖
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webcam_input.stream(
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fn=detect_emotion_stream,
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inputs=[webcam_input, recording_state],
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outputs=[captured_image, score_input]
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)
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# 提交按鈕
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