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fix: update backend references from huggingface to transformers in client and predictor modules

myhloli 5 mēneši atpakaļ
vecāks
revīzija
76259a80ff

+ 5 - 5
mineru/backend/vlm/predictor.py

@@ -22,7 +22,7 @@ try:
 
     hf_loaded = True
 except ImportError as e:
-    logger.warning("hf is not installed. If you are not using huggingface, you can ignore this warning.")
+    logger.warning("hf is not installed. If you are not using transformers, you can ignore this warning.")
 
 engine_loaded = False
 try:
@@ -51,9 +51,9 @@ def get_predictor(
 ) -> BasePredictor:
     start_time = time.time()
 
-    if backend == "huggingface":
+    if backend == "transformers":
         if not model_path:
-            raise ValueError("model_path must be provided for huggingface backend.")
+            raise ValueError("model_path must be provided for transformers backend.")
         if not hf_loaded:
             raise ImportError(
                 "transformers is not installed, so huggingface backend cannot be used. "
@@ -77,7 +77,7 @@ def get_predictor(
             raise ImportError(
                 "sglang is not installed, so sglang-engine backend cannot be used. "
                 "If you need to use sglang-engine backend for inference, "
-                "please install sglang[all]==0.4.6.post4 or a newer version."
+                "please install sglang[all]==0.4.7 or a newer version."
             )
         predictor = SglangEnginePredictor(
             server_args=ServerArgs(model_path, **kwargs),
@@ -104,7 +104,7 @@ def get_predictor(
             http_timeout=http_timeout,
         )
     else:
-        raise ValueError(f"Unsupported backend: {backend}. Supports: huggingface, sglang-engine, sglang-client.")
+        raise ValueError(f"Unsupported backend: {backend}. Supports: transformers, sglang-engine, sglang-client.")
 
     elapsed = round(time.time() - start_time, 2)
     logger.info(f"get_predictor cost: {elapsed}s")

+ 2 - 2
mineru/backend/vlm/vlm_analyze.py

@@ -40,7 +40,7 @@ def doc_analyze(
     pdf_bytes,
     image_writer: DataWriter | None,
     predictor: BasePredictor | None = None,
-    backend="huggingface",
+    backend="transformers",
     model_path=ModelPath.vlm_root_hf,
     server_url: str | None = None,
 ):
@@ -66,7 +66,7 @@ async def aio_doc_analyze(
     pdf_bytes,
     image_writer: DataWriter | None,
     predictor: BasePredictor | None = None,
-    backend="huggingface",
+    backend="transformers",
     model_path=ModelPath.vlm_root_hf,
     server_url: str | None = None,
 ):

+ 2 - 2
mineru/cli/client.py

@@ -48,10 +48,10 @@ from .common import do_parse, read_fn, pdf_suffixes, image_suffixes
     '-b',
     '--backend',
     'backend',
-    type=click.Choice(['pipeline', 'vlm-huggingface', 'vlm-sglang-engine', 'vlm-sglang-client']),
+    type=click.Choice(['pipeline', 'vlm-transformers', 'vlm-sglang-engine', 'vlm-sglang-client']),
     help="""the backend for parsing pdf:
     pipeline: More general.
-    vlm-huggingface: More general.
+    vlm-transformers: More general.
     vlm-sglang-engine: Faster(engine).
     vlm-sglang-client: Faster(client).
     without method specified, pipeline will be used by default.""",