Update app.py

app.py

@@ -2,22 +2,15 @@ import gradio as gr
 import requests
 from gradio_client import Client, handle_file
 
-# 定义多个备用免费 Whisper Space 节点，防止单个节点维护或排队
-WHISPER_SPACES = [
-    "hf-audio/whisper-large-v3",
-    "openai/whisper-large-v3",
-    "sanchit-gandhi/whisper-large-v3",
-]
-
+# 使用 API 结构极简且稳定的公共 Whisper 空间
+FREE_WHISPER_SPACE = "sanchit-gandhi/whisper-large-v3"
 _whisper_client = None
-_current_space_idx = 0
 
 
 def get_whisper_client():
-    global _whisper_client, _current_space_idx
+    global _whisper_client
     if _whisper_client is None:
-        space_name = WHISPER_SPACES[_current_space_idx]
-        _whisper_client = Client(space_name)
+        _whisper_client = Client(FREE_WHISPER_SPACE)
     return _whisper_client
 
 
@@ -34,24 +27,22 @@ LANG_MAP = {
 def transcribe(audio_path):
     client = get_whisper_client()
     
-    # 不强制指定 api_name，让 client 自动匹配默认入口
-    # 同时兼容不同 Space 的入参命名 (inputs 或 input_audio)
+    # 该 Space 只含一个简洁的 predict 入口，并使用 fn_index=0 确保精准匹配
     try:
         result = client.predict(
             inputs=handle_file(audio_path),
             task="transcribe",
+            fn_index=0,
         )
-    except TypeError:
-        # 如果对应的 Space 只有 1 个音频输入参数：
+    except Exception:
+        # 兼容无 extra 选项的识别调用
         result = client.predict(
             handle_file(audio_path),
+            fn_index=0,
         )
 
-    # 提取返回值中的文本部分
     if isinstance(result, (list, tuple)):
         result = result[0]
-    
-    # 某些 space 返回 dict
     if isinstance(result, dict) and "text" in result:
         result = result["text"]
 
@@ -88,7 +79,7 @@ def process(audio_path, mode_label, history):
             return history, None
         trans = translate(text, cfg["pair"])
     except Exception as e:
-        history.append({"role": "assistant", "content": f"⚠️ 识别接口响应异常 ({e})，请重试或检查网络。"})
+        history.append({"role": "assistant", "content": f"⚠️ 出错了：{e}"})
         return history, None
 
     history.append({"role": "user", "content": f"[{cfg['src_tag']}] {text}"})