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paddleocr/_models/doc_vlm.py

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+# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from paddlex.utils.pipeline_arguments import custom_type
+
+from .._utils.cli import (
+    add_simple_inference_args,
+    get_subcommand_args,
+    perform_simple_inference,
+)
+from .base import PaddleXPredictorWrapper, PredictorCLISubcommandExecutor
+from paddlex.utils.pipeline_arguments import custom_type
+
+
+class DocVLM(PaddleXPredictorWrapper):
+    def __init__(
+        self,
+        *args,
+        **kwargs,
+    ):
+        self._extra_init_args = {}
+        super().__init__(*args, **kwargs)
+
+    @property
+    def default_model_name(self):
+        return "PP-DocBee2-3B"
+
+    @classmethod
+    def get_cli_subcommand_executor(cls):
+        return DocVLMSubcommandExecutor()
+
+    def _get_extra_paddlex_predictor_init_args(self):
+        return self._extra_init_args
+
+
+class DocVLMSubcommandExecutor(PredictorCLISubcommandExecutor):
+    input_validator = staticmethod(custom_type(dict))
+
+    @property
+    def subparser_name(self):
+        return "doc_vlm"
+
+    def _update_subparser(self, subparser):
+        add_simple_inference_args(
+            subparser,
+            input_help='Input dict, e.g. `{"image": "https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/medal_table.png", "query": "Recognize this table"}`.',
+        )
+
+    def execute_with_args(self, args):
+        params = get_subcommand_args(args)
+        params["input"] = self.input_validator(params["input"])
+        perform_simple_inference(DocVLM, params)