Update app.py

app.py

@@ -1,8 +1,9 @@
-import gradio as gr # 我们实际没用它，但可以保留这个导入以防万一
+import gradio as gr
 import time
 import json
 import uuid
-import uvicorn # 必须导入 uvicorn
+import uvicorn
+import traceback # 导入用于打印详细错误信息的库
 from fastapi import FastAPI, Request, HTTPException, Depends
 from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
 from starlette.responses import StreamingResponse
@@ -20,56 +21,69 @@ from selenium.webdriver.support import expected_conditions as EC
 app = FastAPI(
     title="SAI-ChatBot OpenAI-Compatible API",
     description="使用 Selenium 自动化在后台与 SAI-ChatBot 交互，并以 OpenAI API 格式返回结果。",
-    version="1.0.0"
+    version="1.1.0-debug"
 )
 auth_scheme = HTTPBearer()
 
 def api_key_auth(credentials: HTTPAuthorizationCredentials = Depends(auth_scheme)):
-    if not credentials:
-        raise HTTPException(status_code=401, detail="Not authenticated", headers={"WWW-Authenticate": "Bearer"})
+    if not credentials: raise HTTPException(status_code=401, detail="Not authenticated")
     return credentials.token
 
 # --- 2. OpenAI 格式的数据模型 ---
-class ChatMessage(BaseModel):
-    role: str
-    content: str
+class ChatMessage(BaseModel): role: str; content: str
+class ChatCompletionRequest(BaseModel): model: str; messages: List[ChatMessage]; stream: Optional[bool] = False
 
-class ChatCompletionRequest(BaseModel):
-    model: str
-    messages: List[ChatMessage]
-    stream: Optional[bool] = False
-
-# --- 3. Selenium 自动化核心函数 ---
+# --- 3. Selenium 自动化核心函数 (带黑匣子) ---
 def get_sai_response(prompt_text: str):
+    print("--- [DEBUG] 进入 get_sai_response 函数 ---")
     options = webdriver.ChromeOptions()
     options.add_argument("--headless")
     options.add_argument("--no-sandbox")
     options.add_argument("--disable-dev-shm-usage")
     options.add_argument("--disable-gpu")
     options.binary_location = "/usr/bin/chromium"
-
+    
     service = ChromeService(executable_path='/usr/bin/chromedriver')
     driver = None
     try:
+        print("--- [DEBUG] 正在初始化 Chrome Driver... ---")
         driver = webdriver.Chrome(service=service, options=options)
+        print("--- [DEBUG] Chrome Driver 初始化成功。---")
+        
+        print(f"--- [DEBUG] 正在访问: https://sai.coludai.cn/ ---")
         driver.get("https://sai.coludai.cn/")
+        print("--- [DEBUG] 页面 get() 方法执行完毕。---")
         
+        # 保存截图和源码，看看我们到底加载了什么页面
+        driver.save_screenshot("debug_page_loaded.png")
+        with open("debug_page_source.html", "w", encoding="utf-8") as f:
+            f.write(driver.page_source)
+        print("--- [DEBUG] 已保存加载后的页面截图和源码。---")
+
         wait = WebDriverWait(driver, 20)
         textarea_selector = 'textarea[placeholder="随时与未来对话，探索无限可能...."]'
+        print(f"--- [DEBUG] 正在等待输入框 (selector: {textarea_selector})... ---")
         textarea = wait.until(EC.presence_of_element_located((By.CSS_SELECTOR, textarea_selector)))
+        print("--- [DEBUG] 输入框定位成功。---")
         
+        print("--- [DEBUG] 正在输入并发送 prompt... ---")
         textarea.send_keys(prompt_text)
         textarea.send_keys(Keys.RETURN)
+        print("--- [DEBUG] Prompt 已发送。---")
         
         last_assistant_selector = "(.//div[@class='message-item' and @type='assistant'])[last()]"
+        print(f"--- [DEBUG] 正在等待新的 AI 回复框 (selector: {last_assistant_selector})... ---")
         wait.until(EC.presence_of_element_located((By.XPATH, last_assistant_selector)))
         last_response_element = driver.find_element(By.XPATH, last_assistant_selector)
+        print("--- [DEBUG] 新的 AI 回复框已出现。---")
 
         previous_text = ""
         max_wait_time = 120
         start_time = time.time()
         
+        print("--- [DEBUG] 进入循环，开始捕获流式文本... ---")
         while time.time() - start_time < max_wait_time:
+            # (内部循环代码保持不变)
             try:
                 markdown_body = last_response_element.find_element(By.CSS_SELECTOR, '.markdown-body')
                 current_text = markdown_body.text
@@ -78,25 +92,43 @@ def get_sai_response(prompt_text: str):
                     yield new_text_chunk
                     previous_text = current_text
                 
-                time.sleep(1) # 稍作等待，让内容有机会刷新
+                time.sleep(1)
                 final_text_check = markdown_body.text
                 if final_text_check == previous_text and final_text_check != "":
                     break
-            except Exception:
+            except Exception as loop_e:
+                 # 捕获循环内的错误但继续
+                print(f"--- [DEBUG] 循环中出现小错误: {loop_e} ---")
                 time.sleep(0.5)
+
+        print("--- [DEBUG] 文本捕获循环结束。---")
+
     except Exception as e:
-        error_message = f"自动化过程中发生错误: {e}"
+        print("\n" + "="*20 + " !!! 发生严重错误 !!! " + "="*20)
+        # 打印非常详细的错误堆栈信息
+        print(traceback.format_exc())
+        print("="*60 + "\n")
+        
+        # 在崩溃时，再保存一次截图和源码，这是最有价值的线索
+        if driver:
+            error_screenshot_path = "debug_error_screenshot.png"
+            driver.save_screenshot(error_screenshot_path)
+            print(f"--- [CRASH] 错误截图已保存到: {error_screenshot_path} ---")
+        
+        # 产生一个包含详细错误信息的流式响应
+        error_message = f"自动化过程中发生严重错误: {e}\n\n详细信息请查看 Hugging Face Space 的日志。"
         yield error_message
     finally:
         if driver:
+            print("--- [DEBUG] 正在关闭 Chrome Driver... ---")
             driver.quit()
+            print("--- [DEBUG] Chrome Driver 已关闭。---")
 
-# --- 4. API 端点定义 ---
+# --- 4. API 端点定义 (保持不变) ---
 @app.post("/v1/chat/completions")
 async def chat_completions(request: ChatCompletionRequest, token: str = Depends(api_key_auth)):
     last_user_message = next((msg.content for msg in reversed(request.messages) if msg.role == 'user'), None)
-    if not last_user_message:
-        raise HTTPException(status_code=400, detail="No user message found")
+    if not last_user_message: raise HTTPException(status_code=400, detail="No user message found")
 
     response_id, created_timestamp = f"chatcmpl-{uuid.uuid4()}", int(time.time())
 
@@ -104,22 +136,14 @@ async def chat_completions(request: ChatCompletionRequest, token: str = Depends(
         async def stream_generator():
             for chunk in get_sai_response(last_user_message):
                 if not chunk: continue
-                response_chunk = {
-                    "id": response_id, "object": "chat.completion.chunk", "created": created_timestamp,
-                    "model": "sai-chatbot-l6", "choices": [{"index": 0, "delta": {"content": chunk}, "finish_reason": None}]
-                }
+                response_chunk = {"id": response_id, "object": "chat.completion.chunk", "created": created_timestamp, "model": "sai-chatbot-l6", "choices": [{"index": 0, "delta": {"content": chunk}, "finish_reason": None}]}
                 yield f"data: {json.dumps(response_chunk)}\n\n"
             yield f"data: [DONE]\n\n"
         return StreamingResponse(stream_generator(), media_type="text/event-stream")
     else:
         full_content = "".join([chunk for chunk in get_sai_response(last_user_message)])
-        return {
-            "id": response_id, "object": "chat.completion", "created": created_timestamp,
-            "model": "sai-chatbot-l6", "choices": [{"index": 0, "message": {"role": "assistant", "content": full_content}, "finish_reason": "stop"}],
-            "usage": {"prompt_tokens": len(last_user_message), "completion_tokens": len(full_content), "total_tokens": len(last_user_message) + len(full_content)}
-        }
+        return {"id": response_id, "object": "chat.completion", "created": created_timestamp, "model": "sai-chatbot-l6", "choices": [{"index": 0, "message": {"role": "assistant", "content": full_content}, "finish_reason": "stop"}], "usage": {"prompt_tokens": len(last_user_message), "completion_tokens": len(full_content), "total_tokens": len(last_user_message) + len(full_content)}}
 
-# --- 5. 【关键】启动服务器 ---
+# --- 5. 启动服务器 (保持不变) ---
 if __name__ == "__main__":
-    # 在 Hugging Face Spaces 中，应用需要监听 0.0.0.0:7860
     uvicorn.run(app, host="0.0.0.0", port=7860)