"""Manage documentation

Stages:
1. process - Process

Copyright 2025 Smart-AI-Memory
Licensed under Fair Source License 0.9
"""

import logging
from typing import Any

from attune.workflows.base import BaseWorkflow, ModelTier

logger = logging.getLogger(__name__)


class ManageDocsWorkflow(BaseWorkflow):
    """Manage documentation


    Usage:
        workflow = ManageDocsWorkflow()
        result = await workflow.execute(
            # Add parameters here
        )
    """

    name = "manage-docs"
    description = "Manage documentation"
    stages = ["process"]
    tier_map = {
        "process": ModelTier.CAPABLE,
    }

    def __init__(
        self,
        **kwargs: Any,
    ):
        """Initialize manage-docs workflow.

        Args:
            **kwargs: Additional arguments passed to BaseWorkflow

        """
        super().__init__(**kwargs)

    async def run_stage(
        self,
        stage_name: str,
        tier: ModelTier,
        input_data: Any,
    ) -> tuple[Any, int, int]:
        """Execute the single processing stage."""
        if stage_name == "process":
            return await self._process(input_data, tier)
        raise ValueError(f"Unknown stage: {stage_name}")

    async def _process(
        self,
        input_data: Any,
        tier: ModelTier,
    ) -> tuple[Any, int, int]:
        """Process the input data.

        Args:
            input_data: Input data to process
            tier: Model tier to use

        Returns:
            Tuple of (result, input_tokens, output_tokens)

        """
        # TODO: Implement processing logic
        prompt = f"Process this input: {input_data}"

        # Use LLM executor if available
        if self._executor:
            result = await self._executor.run(
                task_type="workflow_stage",
                prompt=prompt,
                tier=tier.to_unified() if hasattr(tier, "to_unified") else tier,
            )
            return result.content, result.input_tokens, result.output_tokens

        # Fallback to basic processing
        return {"result": "Processed", "input": input_data}, 0, 0
