Update app.py

app.py

@@ -6,7 +6,8 @@ import asyncio
 import aiohttp
 import subprocess
 
-# pip 升級
+# --- 1. 環境設定 ---
+# pip 升級 (通常 Space 啟動時跑一次即可)
 def upgrade_pip():
     try:
         subprocess.check_call([os.sys.executable, "-m", "pip", "install", "--upgrade", "pip"])
@@ -17,14 +18,54 @@ def upgrade_pip():
 upgrade_pip()
 
 LLM_API = os.environ.get("LLM_API", "").strip()
-LLM_URL = os.environ.get("LLM_URL")
+LLM_URL = os.environ.get("LLM_URL", "").strip() # 確保去除空格
 USER_ID = "HuggingFace Space"
 
-async def send_chat_message(LLM_URL, LLM_API, category, file_url):
-    print(f"--- 開始請求 ---")
-    print(f"URL: {LLM_URL}/chat-messages")
-    print(f"File URL: {file_url}") # 檢查這裡產生的 URL 是否真的公開可讀取
+# --- 2. 上傳檔案函式 (修正版) ---
+async def upload_file(LLM_URL, LLM_API, file_path, user_id):
+    """
+    將本地暫存檔案上傳到 LLM Server，取得 file_id
+    """
+    if not os.path.exists(file_path):
+        return {"error": f"File {file_path} not found"}
+
+    mime_type, _ = mimetypes.guess_type(file_path)
+    if mime_type is None:
+        mime_type = 'application/octet-stream'
+        
+    filename = os.path.basename(file_path)
+    print(f"正在上傳檔案: {filename} ({mime_type})")
+
+    try:
+        data = aiohttp.FormData()
+        # 注意: 這裡必須再次 open file，aiohttp 會自動處理串流
+        data.add_field('file', open(file_path, 'rb'), filename=filename, content_type=mime_type)
+        data.add_field('user', user_id)
+
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{LLM_URL}/files/upload",
+                headers={"Authorization": f"Bearer {LLM_API}"},
+                data=data
+            ) as response:
+                response_text = await response.text()
+                print(f"上傳回應狀態: {response.status}")
+                
+                if response.status != 200 and response.status != 201:
+                    print(f"上傳失敗回應: {response_text}")
+                    return {"error": f"Upload failed: {response.status} - {response_text}"}
+                
+                return json.loads(response_text)
 
+    except Exception as e:
+        print(f"上傳過程發生例外: {e}")
+        return {"error": str(e)}
+
+# --- 3. 對話請求函式 (改用 file_id) ---
+async def send_chat_message(LLM_URL, LLM_API, category, file_id):
+    """
+    使用 file_id 發送對話請求
+    """
     payload = {
         "inputs": {},
         "query": category,
@@ -34,13 +75,15 @@ async def send_chat_message(LLM_URL, LLM_API, category, file_url):
         "files": [
             {
                 "type": "image",
-                "transfer_method": "remote_url",
-                "url": file_url
+                "transfer_method": "local_file", # 注意：使用 ID 時這裡通常是 local_file
+                "upload_file_id": file_id
             }
         ]
     }
 
+    print(f"發送請求中... (File ID: {file_id})")
     answer = ""
+    
     try:
         async with aiohttp.ClientSession() as session:
             async with session.post(
@@ -52,94 +95,45 @@ async def send_chat_message(LLM_URL, LLM_API, category, file_url):
                 json=payload
             ) as response:
                 
-                # [DEBUG 1] 檢查狀態碼
-                print(f"HTTP Status: {response.status}")
-                
                 if response.status != 200:
-                    # 如果出錯，讀取錯誤訊息並回傳
                     error_text = await response.text()
-                    print(f"API Error Response: {error_text}")
-                    return f"API Error {response.status}: {error_text}"
+                    return f"Chat Error {response.status}: {error_text}"
 
-                # [DEBUG 2] 逐行監看回傳內容
                 async for line_bytes in response.content:
                     line = line_bytes.decode("utf-8").strip()
-                    
-                    # 印出原始資料 (Debug 用，確認有東西回來)
-                    if line: 
-                        print(f"Raw Line: {line}") 
-
                     if line.startswith("data: "):
                         try:
                             data = json.loads(line[6:])
                             if "answer" in data:
                                 answer += data["answer"]
-                                # print(f"Current Answer chunk: {data['answer']}") # 選用：即時看片段
                             if "error" in data:
-                                print(f"Data Error: {data}") # Dify 有時會在 data 裡回傳 error
-                        except Exception as e:
-                            print(f"JSON Parse Error: {e} | Content: {line}")
+                                return f"Stream Error: {data}"
+                        except:
                             continue
                             
     except Exception as e:
-        print(f"Request Exception: {e}")
-        return f"System Error: {str(e)}"
-
-    if not answer:
-        print("警告: 請求結束但 answer 為空")
-        
-    return answer or "No answer returned (Empty Response)"
-
-async def upload_file(LLM_URL, LLM_API, file_path, user_id):
-    if not os.path.exists(file_path):
-        return f"Error: File {file_path} not found"
-
-    # ✅ 先定義 filename 和 mime_type
-    mime_type, _ = mimetypes.guess_type(file_path)
-    filename = os.path.basename(file_path)
-
-    # ✅ print 放在這裡
-    print("Uploading file:", filename, "mime_type:", mime_type)
+        return f"Request Exception: {str(e)}"
 
-    with open(file_path, 'rb') as f:
-        async with aiohttp.ClientSession() as session:
-            form_data = aiohttp.FormData()
-            form_data.add_field('file', f, filename=filename, content_type=mime_type)
-            form_data.add_field('user', user_id)
-            async with session.post(
-                f"{LLM_URL}/files/upload",
-                headers={"Authorization": f"Bearer {LLM_API}"},
-                data=form_data
-            ) as response:
-                if response.status == 404:
-                    return "Error: Endpoint not found (404)"
-                response_text = await response.text()
-                print("Upload response:", response_text)
-                try:
-                    return json.loads(response_text)
-                except json.JSONDecodeError:
-                    return "Error: Invalid JSON response"
+    return answer or "No answer returned."
 
+# --- 4. 主處理邏輯 ---
 async def handle_input(file_path, category):
-    # 取得檔名
-    filename = os.path.basename(file_path)
-
-    # 直接用 HuggingFace repo URL
-    file_url = f"https://huggingface.co/spaces/DeepLearning101/Multimodal-Playground/blob/main/DEMO/{filename}?raw=true"
+    if not file_path:
+        return "請先上傳圖片"
 
-    return await send_chat_message(LLM_URL, LLM_API, category, file_url)
-# async def handle_input(file_path, category):
-#     # 如果 tmp 路徑不存在，改成 repo 內的 DEMO 路徑
-#     if not os.path.exists(file_path):
-#         file_path = os.path.join("DEMO", os.path.basename(file_path))
+    # 步驟 1: 上傳檔案
+    upload_result = await upload_file(LLM_URL, LLM_API, file_path, USER_ID)
     
-#     upload_response = await upload_file(LLM_URL, LLM_API, file_path, USER_ID)
-#     if isinstance(upload_response, str) and upload_response.startswith("Error"):
-#         return upload_response
-#     file_id = upload_response.get("id")
-#     if not file_id:
-#         return "Error: No file ID returned from upload"
-#     return await send_chat_message(LLM_URL, LLM_API, category, file_id)
+    # 檢查上傳是否成功
+    if "error" in upload_result:
+        return f"上傳錯誤: {upload_result['error']}"
+    
+    file_id = upload_result.get("id")
+    if not file_id:
+        return f"錯誤: 上傳成功但未回傳 ID。回應: {upload_result}"
+
+    # 步驟 2: 發送對話
+    return await send_chat_message(LLM_URL, LLM_API, category, file_id)
 
 # UI 元件 & 資料
 examples = [
@@ -180,21 +174,19 @@ LINKS = """
 <a href='https://blog.twman.org/2023/07/HugIE.html' target='_blank'>基於機器閱讀理解和指令微調的統一信息抽取框架之診斷書醫囑資訊擷取分析</a><br>
 """
 
-# Gradio Blocks 寫法（全新修正）
 with gr.Blocks() as iface:
     gr.HTML(TITLE)
-    gr.HTML(SUBTITLE)
-    gr.HTML(LINKS)
+    # gr.HTML(LINKS) # 需要時取消註解
 
     with gr.Row():
-        file_input = gr.Image(label='圖片上傳', type='filepath')
-        category = gr.Radio(label="Message Category", choices=[
+        file_input = gr.Image(label='圖片上傳', type='filepath') # type='filepath' 很重要
+        category = gr.Radio(label="文件類型", choices=[
             "機票", "計程車乘車證明", "通行明細 (etag)", "QRCODE發票",
-            "超商高鐵車票", "高鐵車票", "超商台鐵車票", "台鐵車票", "旅行業代收轉付收據", "電子發票證明", "收據", "診斷證明書", 
-            "身份證正面", "身份證反面", "健保卡", "護照", "居留證", "行照", "勞保個人加保"
+            "超商高鐵車票", "高鐵車票", "超商台鐵車票", "台鐵車票", 
+            "診斷證明書", "身份證正面", "身份證反面", "健保卡", "護照", "居留證"
         ])
     
-    submit_btn = gr.Button("解析")
+    submit_btn = gr.Button("解析", variant="primary")
     output_text = gr.Textbox(label="解析結果", lines=10)
 
     submit_btn.click(fn=handle_input, inputs=[file_input, category], outputs=output_text)
@@ -202,7 +194,7 @@ with gr.Blocks() as iface:
     gr.Examples(
         examples=examples,
         inputs=[file_input, category],
-        label="範例圖片與類型"
+        label="點擊範例直接測試"
     )
 
 iface.launch()