update app

app.py

@@ -122,38 +122,36 @@ if torch.cuda.is_available():
 
 print("Using device:", device)
 
-CACHE_PATH = "./model_cache"
-if not os.path.exists(CACHE_PATH):
-    os.makedirs(CACHE_PATH)
-
-
-model_path_d_local = snapshot_download(
-    repo_id='rednote-hilab/dots.ocr',
-    local_dir=os.path.join(CACHE_PATH, 'dots.ocr'),
-    max_workers=20,
-    local_dir_use_symlinks=False
-)
-
-config_file_path = os.path.join(model_path_d_local, "configuration_dots.py")
-
-if os.path.exists(config_file_path):
-    with open(config_file_path, 'r') as f:
-        input_code = f.read()
-
-    lines = input_code.splitlines()
-    if "class DotsVLProcessor" in input_code and not any("attributes = " in line for line in lines):
-        output_lines = []
-        for line in lines:
-            output_lines.append(line)
-            if line.strip().startswith("class DotsVLProcessor"):
-                output_lines.append("    attributes = [\"image_processor\", \"tokenizer\"]")
-
-        with open(config_file_path, 'w') as f:
-            f.write('\n'.join(output_lines))
-        print("Patched configuration_dots.py successfully.")
-
-
-sys.path.append(model_path_d_local)
+# CACHE_PATH = "./model_cache"
+# if not os.path.exists(CACHE_PATH):
+#     os.makedirs(CACHE_PATH)
+#
+# model_path_d_local = snapshot_download(
+#     repo_id='rednote-hilab/dots.ocr',
+#     local_dir=os.path.join(CACHE_PATH, 'dots.ocr'),
+#     max_workers=20,
+#     local_dir_use_symlinks=False
+# )
+#
+# config_file_path = os.path.join(model_path_d_local, "configuration_dots.py")
+#
+# if os.path.exists(config_file_path):
+#     with open(config_file_path, 'r') as f:
+#         input_code = f.read()
+#
+#     lines = input_code.splitlines()
+#     if "class DotsVLProcessor" in input_code and not any("attributes = " in line for line in lines):
+#         output_lines = []
+#         for line in lines:
+#             output_lines.append(line)
+#             if line.strip().startswith("class DotsVLProcessor"):
+#                 output_lines.append("    attributes = [\"image_processor\", \"tokenizer\"]")
+#
+#         with open(config_file_path, 'w') as f:
+#             f.write('\n'.join(output_lines))
+#         print("Patched configuration_dots.py successfully.")
+#
+#sys.path.append(model_path_d_local)
 
 MAX_MAX_NEW_TOKENS = 4096
 DEFAULT_MAX_NEW_TOKENS = 2048
@@ -180,7 +178,7 @@ model_x = Qwen2_5_VLForConditionalGeneration.from_pretrained(
 ).to(device).eval()
 
 # Load Dots.OCR from the local, patched directory
-MODEL_PATH_D = model_path_d_local
+MODEL_PATH_D = "strangervisionhf/dots.ocr-base-fix"
 processor_d = AutoProcessor.from_pretrained(MODEL_PATH_D, trust_remote_code=True)
 model_d = AutoModelForCausalLM.from_pretrained(
     MODEL_PATH_D,