Update app.py

app.py

@@ -25,11 +25,22 @@ def upload_file(image_path):
     headers = {'Authorization': f'Bearer {HF_TOKEN}'}
     resp = requests.post(UPLOAD_URL, files=files, headers=headers)
     resp.raise_for_status()
-    res = resp.json()
-    # 返回格式可能是list或dict
+    # 修复: 解析结果时先检查返回类型, 如果非dict或list则报错
+    try:
+        res = resp.json()
+    except Exception as e:
+        raise RuntimeError("解析API响应的JSON失败: %s" % e)
     if isinstance(res, list) and len(res) > 0:
-        return res[0]
-    return res
+        # 取第一个有效项目, 如果不是dict也报错
+        if isinstance(res[0], dict):
+            return res[0]
+        else:
+            raise RuntimeError("返回结果不是字典类型: %s" % str(res[0]))
+    elif isinstance(res, dict):
+        return res
+    else:
+        # 返回格式不明, 直接异常
+        raise RuntimeError("API响应格式异常，期望是dict或list: %s" % str(res))
 
 def call_infer(payload):
     headers = {'Authorization': f'Bearer {HF_TOKEN}'}
@@ -79,7 +90,10 @@ def infer(
     # 1. 上传文件
     try:
         uploaded_info = upload_file(image)
-        # 提交给API需要包装成和官方一样的dict
+        # 检查uploaded_info类型
+        if not isinstance(uploaded_info, dict) or "path" not in uploaded_info:
+            print(f"[图片上传] 失败: 返回结果无'path'字段: {uploaded_info}")
+            return None, seed
         img_obj = {
             "path": uploaded_info["path"],
             "meta": {"_type": "gradio.FileData"},
@@ -96,7 +110,7 @@ def infer(
         "lora_adapter": lora_adapter,
         "seed": int(seed),
         "randomize_seed": bool(randomize_seed),
-        "guidance_scale": float(guidance_scale),
+        "guidance_scale": int(guidance_scale),
         "steps": int(steps),
     }