"""A team leader that has 10 years of experiance coding.

Stages:
1. analyze - Analyze
2. process - Process
3. report - Report

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 NewSampleWorkflow1Workflow(BaseWorkflow):
    """A team leader that has 10 years of experiance coding.


    Usage:
        workflow = NewSampleWorkflow1Workflow()
        result = await workflow.execute(
            # Add parameters here
        )
    """

    name = "new-sample-workflow1"
    description = "A team leader that has 10 years of experiance coding."
    stages = ["analyze", "process", "report"]
    tier_map = {
        "analyze": ModelTier.CHEAP,
        "process": ModelTier.CAPABLE,
        "report": ModelTier.PREMIUM,
    }

    def __init__(
        self,
        **kwargs: Any,
    ):
        """Initialize new-sample-workflow1 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]:
        """Route to specific stage implementation."""
        if stage_name == "analyze":
            return await self._analyze(input_data, tier)
        if stage_name == "process":
            return await self._process(input_data, tier)
        if stage_name == "report":
            return await self._report(input_data, tier)
        raise ValueError(f"Unknown stage: {stage_name}")

    async def _analyze(
        self,
        input_data: Any,
        tier: ModelTier,
    ) -> tuple[Any, int, int]:
        """Analyze stage.

        Args:
            input_data: Input from previous stage
            tier: Model tier to use

        Returns:
            Tuple of (result, input_tokens, output_tokens)

        """
        # TODO: Implement analyze logic
        prompt = f"analyze stage: {input_data}"

        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

        return {"stage": "analyze", "input": input_data}, 0, 0

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

        Args:
            input_data: Input from previous stage
            tier: Model tier to use

        Returns:
            Tuple of (result, input_tokens, output_tokens)

        """
        # TODO: Implement process logic
        prompt = f"process stage: {input_data}"

        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

        return {"stage": "process", "input": input_data}, 0, 0

    async def _report(
        self,
        input_data: Any,
        tier: ModelTier,
    ) -> tuple[Any, int, int]:
        """Report stage.

        Args:
            input_data: Input from previous stage
            tier: Model tier to use

        Returns:
            Tuple of (result, input_tokens, output_tokens)

        """
        # TODO: Implement report logic
        prompt = f"report stage: {input_data}"

        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

        return {"stage": "report", "input": input_data}, 0, 0
