# 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)