#!/usr/bin/env python

# Copyright 2025 HuggingFace Inc. team. 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 lerobot.configs import PipelineFeatureType, PolicyFeature

from .pipeline import ComplementaryDataProcessorStep, ProcessorStepRegistry


# NOTE: The registry name "smolvla_new_line_processor" is kept for backward compatibility
# with serialized processor configs that reference this name.
@ProcessorStepRegistry.register(name="smolvla_new_line_processor")
class NewLineTaskProcessorStep(ComplementaryDataProcessorStep):
    """
    A processor step that ensures the 'task' description ends with a newline character.

    This step is necessary for certain tokenizers (e.g., PaliGemma) that expect a
    newline at the end of the prompt. It handles both single string tasks and lists
    of string tasks.
    """

    def complementary_data(self, complementary_data):
        if "task" not in complementary_data:
            return complementary_data

        task = complementary_data["task"]
        if task is None:
            return complementary_data

        new_complementary_data = dict(complementary_data)

        # Handle both string and list of strings
        if isinstance(task, str):
            # Single string: add newline if not present
            if not task.endswith("\n"):
                new_complementary_data["task"] = f"{task}\n"
        elif isinstance(task, list) and all(isinstance(t, str) for t in task):
            # List of strings: add newline to each if not present
            new_complementary_data["task"] = [t if t.endswith("\n") else f"{t}\n" for t in task]
        # If task is neither string nor list of strings, leave unchanged

        return new_complementary_data

    def transform_features(
        self, features: dict[PipelineFeatureType, dict[str, PolicyFeature]]
    ) -> dict[PipelineFeatureType, dict[str, PolicyFeature]]:
        return features