Update app.py

app.py

@@ -1,145 +1,106 @@
-import json
 import os
-import time
-import uuid
 import tempfile
-from PIL import Image
 import gradio as gr
+import pandas as pd
+from urllib.parse import urlparse, parse_qs
+from PIL import Image
 from io import BytesIO
-from google import genai
-import gspread
-from oauth2client.service_account import ServiceAccountCredentials
 import requests
+from google import genai
 
-# Hugging Face Spaces 上從 Secrets 讀取服務帳戶金鑰
-try:
-    google_sheets_creds_json = os.environ.get("GOOGLE_SHEETS_SERVICE_ACCOUNT")
-    if not google_sheets_creds_json:
-        # Fallback to local file for local testing
-        SERVICE_ACCOUNT_FILE = "service_account.json"
-    else:
-        with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.json') as temp_key_file:
-            temp_key_file.write(google_sheets_creds_json)
-            SERVICE_ACCOUNT_FILE = temp_key_file.name
-except Exception as e:
-    print(f"Failed to load Google Sheets credentials from environment variable: {e}")
-    SERVICE_ACCOUNT_FILE = "service_account.json"
+# 請確保你的 requirements.txt 包含 pandas
+# pip install pandas
 
-# --- Google Sheets 相關函式 ---
-def get_sheet_data(spreadsheet_url):
-    """從 Google Sheet 讀取所有資料並返回 DataFrame 格式。"""
+# --- Google Sheets 相關函式 (已更新) ---
+def read_google_sheet(sheet_url: str):
+    """
+    從 Google Sheet 的 URL 讀取資料。
+    """
+    if not sheet_url:
+        raise gr.Error("請提供 Google Sheet URL。")
     try:
-        scope = ['https://spreadsheets.google.com/feeds', 'https://www.googleapis.com/auth/drive']
-        creds = ServiceAccountCredentials.from_json_keyfile_name(SERVICE_ACCOUNT_FILE, scope)
-        client = gspread.authorize(creds)
-        
-        spreadsheet = client.open_by_url(spreadsheet_url)
-        worksheet = spreadsheet.worksheet("Sheet1")
-        
-        list_of_lists = worksheet.get_all_values()
-        
-        if not list_of_lists or len(list_of_lists) < 2:
-            return [], "試算表為空或沒有資料。"
+        def build_csv_url(url: str) -> str:
+            parsed = urlparse(url)
+            doc_id = parsed.path.strip("/").split("/")[2] if len(parsed.path.strip("/").split("/")) >= 3 and parsed.path.strip("/").split("/")[1] == "d" else None
+            gid = parse_qs(parsed.query).get("gid", [None])[0] or parse_qs(parsed.fragment).get("gid", [None])[0] or "0"
+            if doc_id:
+                return f"https://docs.google.com/spreadsheets/d/{doc_id}/export?format=csv&gid={gid}"
+            if "/export" in parsed.path and "format=csv" in parsed.query:
+                return url
+            return url.replace("/edit#gid=0", "/export?format=csv&gid=0")
+
+        csv_url = build_csv_url(sheet_url)
+        df = pd.read_csv(csv_url, engine='python', on_bad_lines='warn', encoding='utf-8')
+        return df
+    except Exception as e:
+        raise gr.Error(f"讀取 Google Sheet 時發生錯誤: {e}")
 
-        headers = list_of_lists[0]
-        data = []
-        for i, row in enumerate(list_of_lists[1:], start=2):
-            if not any(row):
-                continue
-            row_dict = dict(zip(headers, row))
-            data.append({
-                "Index": i,
-                "白背圖URL": row_dict.get("White_Back_Image_URL", ""),
-                "參考圖URL": row_dict.get("Ref_Image_URL", ""),
-                "提示詞": row_dict.get("Prompt", "")
-            })
-            
-        dataframe_output = [[row['Index'], row['白背圖URL'], row['參考圖URL'], row['提示詞']] for row in data]
-        
-        log_message = f"成功讀取 {len(data)} 筆數據。"
-        return dataframe_output, log_message
-        
-    except FileNotFoundError:
-        raise gr.Error(f"錯誤：找不到金鑰檔案 '{SERVICE_ACCOUNT_FILE}'。請確認已正確放置或設定 Hugging Face Secrets。", duration=10)
-    except gspread.exceptions.SpreadsheetNotFound:
-        raise gr.Error(f"錯誤：Google Sheet not found at URL: {spreadsheet_url}", duration=10)
+def process_sheet_data(sheet_url):
+    """處理試算表資料，為 Gradio DataFrame 準備。"""
+    try:
+        df = read_google_sheet(sheet_url)
+        if df.shape[1] < 4:  # 檢查是否至少有 4 列 (索引, 白背圖URL, 參考圖URL, 提示詞)
+            error_msg = f"錯誤：Google Sheet 至少需要 4 列 (索引, 白背圖URL, 參考圖URL, 提示詞)。目前只有 {df.shape[1]} 列。"
+            raise gr.Error(error_msg)
+        
+        # 假設列順序為: White_Back_Image_URL, Ref_Image_URL, Prompt
+        headers = ["Index", "白背圖URL", "參考圖URL", "提示詞"]
+        data_list = []
+        for i, row in df.iterrows():
+            if pd.notna(row.iloc[0]):  # 檢查第一列 (白背圖URL) 是否有資料
+                data_list.append([i + 2, row.iloc[0], row.iloc[1], row.iloc[2]])
+        
+        log_message = f"成功讀取 {len(data_list)} 筆數據。"
+        return data_list, log_message
     except Exception as e:
-        raise gr.Error(f"讀取試算表時發生錯誤: {e}", duration=10)
+        raise gr.Error(f"處理試算表資料時發生錯誤: {e}")
 
-def get_row_data(spreadsheet_url, row_number):
+def get_row_data(sheet_url, row_number):
     """從 Google Sheet 讀取指定列的資料。"""
     try:
-        scope = ['https://spreadsheets.google.com/feeds', 'https://www.googleapis.com/auth/drive']
-        creds = ServiceAccountCredentials.from_json_keyfile_name(SERVICE_ACCOUNT_FILE, scope)
-        client = gspread.authorize(creds)
-
-        spreadsheet = client.open_by_url(spreadsheet_url)
-        worksheet = spreadsheet.worksheet("Sheet1")
+        df = read_google_sheet(sheet_url)
+        row_index = int(row_number) - 2 # 由於DataFrame索引從0開始，而Gradio顯示的行數從2開始
+        if row_index < 0 or row_index >= df.shape[0]:
+            raise gr.Error(f"指定的行數 {row_number} 不存在。")
         
-        headers = worksheet.row_values(1)
-        row_data = worksheet.row_values(row_number)
-        
-        row_dict = dict(zip(headers, row_data))
-        
-        white_back_image_url = row_dict.get("White_Back_Image_URL", "")
-        ref_image_url = row_dict.get("Ref_Image_URL", "")
-        prompt_text = row_dict.get("Prompt", "")
+        row_data = df.iloc[row_index]
+        white_back_image_url = row_data.iloc[0] if pd.notna(row_data.iloc[0]) else ""
+        ref_image_url = row_data.iloc[1] if pd.notna(row_data.iloc[1]) else ""
+        prompt_text = row_data.iloc[2] if pd.notna(row_data.iloc[2]) else ""
         
         return white_back_image_url, ref_image_url, prompt_text
-
-    except FileNotFoundError:
-        raise gr.Error(f"錯誤：找不到金鑰檔案 '{SERVICE_ACCOUNT_FILE}'。", duration=10)
-    except gspread.exceptions.SpreadsheetNotFound:
-        raise gr.Error(f"錯誤：Google Sheet not found at URL: {spreadsheet_url}", duration=10)
-    except IndexError:
-        raise gr.Error(f"錯誤：指定的行數 {row_number} 不存在。", duration=10)
     except Exception as e:
-        raise gr.Error(f"讀取指定行時發生錯誤: {e}", duration=10)
+        raise gr.Error(f"讀取指定行時發生錯誤: {e}")
 
 # --- 下載圖片函式 ---
 def load_image_from_url(url: str):
-    """
-    從 URL 下載圖片並以 PIL Image 格式回傳，使用更穩健的請求標頭。
-    """
-    if not url:
+    """從 URL 下載圖片並以 PIL Image 格式回傳。"""
+    if not url or not isinstance(url, str):
         return None
     try:
         headers = {
             'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
-            'Referer': 'https://www.google.com/',
-            'Accept-Encoding': 'gzip, deflate, br',
-            'Accept-Language': 'en-US,en;q=0.9',
-            'Connection': 'keep-alive',
         }
-        
         response = requests.get(url, timeout=20, headers=headers)
         response.raise_for_status()
-
         image = Image.open(BytesIO(response.content)).convert("RGB")
-        print(f"Debug: Successfully loaded image from URL: {url}")
         return image
     except requests.exceptions.HTTPError as e:
-        print(f"Error downloading image from {url}: HTTP Error {e.response.status_code}")
-        gr.Warning(f"從 URL '{url}' 下載圖片失敗：HTTP 錯誤 {e.response.status_code}", duration=10)
+        gr.Warning(f"下載圖片失敗：HTTP 錯誤 {e.response.status_code}")
         return None
     except Exception as e:
-        print(f"An unexpected error occurred: {e}")
-        gr.Warning(f"從 URL '{url}' 下載圖片時發生意外錯誤：{e}", duration=10)
+        gr.Warning(f"下載圖片時發生意外錯誤：{e}")
         return None
 
 # --- Gemini 核心函式 ---
 def generate_image(text, images, api_key, model="gemini-2.5-flash-image-preview"):
     """使用 Gemini 模型生成圖片。"""
     if not api_key or api_key.strip() == "":
-        raise gr.Error("錯誤：請輸入有效的 Gemini API 金鑰。", duration=10)
-
+        raise gr.Error("請輸入有效的 Gemini API 金鑰。", duration=10)
     try:
         client = genai.Client(api_key=api_key.strip())
         contents = images + [text]
-        response = client.models.generate_content(
-            model=model,
-            contents=contents,
-        )
+        response = client.models.generate_content(model=model, contents=contents)
         text_response = ""
         image_path = None
         for part in response.candidates[0].content.parts:
@@ -156,15 +117,7 @@ def generate_image(text, images, api_key, model="gemini-2.5-flash-image-preview"
         raise gr.Error(f"Gemini API 呼叫失敗: {e}", duration=10)
 
 # --- Gradio 互動函式 ---
-def process_sheet_data(sheet_url):
-    """處理試算表，讀取所有數據並更新 DataFrame。"""
-    if not sheet_url:
-        raise gr.Error("請輸入 Google Sheet URL。", duration=5)
-    
-    data, log_message = get_sheet_data(sheet_url)
-    return data, log_message
-
-def generate_image_from_row(sheet_url, row_number):
+def generate_image_from_row(sheet_url, row_number, gemini_api_key):
     """根據指定的行數，生成圖片。"""
     if not sheet_url:
         raise gr.Error("請先輸入 Google Sheet URL。", duration=5)
@@ -172,16 +125,14 @@ def generate_image_from_row(sheet_url, row_number):
         raise gr.Error("請輸入有效的行數 (大於 1)。", duration=5)
         
     try:
-        row_num = int(row_number)
-        white_back_url, ref_image_url, prompt_text = get_row_data(sheet_url, row_num)
+        white_back_url, ref_image_url, prompt_text = get_row_data(sheet_url, row_number)
         
-        log_message = f"開始處理第 {row_num} 行...\n"
+        log_message = f"開始處理第 {row_number} 行...\n"
         log_message += f"白背圖URL: {white_back_url}\n"
         log_message += f"參考圖URL: {ref_image_url}\n"
         log_message += f"提示詞: {prompt_text}\n"
 
         images_for_gemini = []
-        
         if white_back_url:
             wb_img = load_image_from_url(white_back_url)
             if wb_img:
@@ -196,11 +147,6 @@ def generate_image_from_row(sheet_url, row_number):
         
         log_message += "圖片已下載，開始呼叫 Gemini 模型...\n"
         
-        # 優先從環境變數讀取 Gemini API 金鑰
-        gemini_api_key = os.environ.get("GEMINI_API_KEY")
-        if not gemini_api_key:
-            raise gr.Error("錯誤：找不到 Gemini API 金鑰。請確認已設定 Hugging Face Secrets。", duration=10)
-
         image_path, text_response = generate_image(text=prompt_text, images=images_for_gemini, api_key=gemini_api_key)
 
         if image_path:
@@ -210,7 +156,6 @@ def generate_image_from_row(sheet_url, row_number):
             log_message += "圖片生成失敗。\n"
             log_message += f"Gemini 文字回應: {text_response}"
             return None, log_message
-            
     except ValueError:
         raise gr.Error("行數必須為數字。", duration=5)
     except Exception as e:
@@ -222,11 +167,12 @@ with gr.Blocks() as demo:
     
     with gr.Row(elem_classes="main-content"):
         with gr.Column(elem_classes="input-column"):
-            # 由於金鑰將從 Secrets 讀取，這個輸入框可以移除或僅用於顯示
-            gr.Markdown("### ⚠️ 請在 Hugging Face Spaces 專案設定中設定 Secrets")
-            gr.Markdown("金鑰名稱：`GOOGLE_SHEETS_SERVICE_ACCOUNT`")
-            gr.Markdown("金鑰名稱：`GEMINI_API_KEY`")
-            
+            gemini_api_key = gr.Textbox(
+                lines=1,
+                placeholder="請在此輸入你的 Gemini API 金鑰",
+                label="Gemini API 金鑰",
+                elem_classes="api-key-input"
+            )
             sheet_url_input = gr.Textbox(
                 label="Google Sheet URL", 
                 value="https://docs.google.com/spreadsheets/d/1G3olHxydDIbnyXdh5nnw5TG0akZFeMeYm-25JmCGDLg/edit?gid=0#gid=0"
@@ -260,7 +206,7 @@ with gr.Blocks() as demo:
 
     generate_selected_button.click(
         fn=generate_image_from_row,
-        inputs=[sheet_url_input, row_index_input],
+        inputs=[sheet_url_input, row_index_input, gemini_api_key],
         outputs=[generated_image_output, operation_log_output]
     )