"""Performance Audit Workflow — Agent SDK Native.

Delegates performance auditing to three specialized Claude Agent SDK
subagents (complexity-analyzer, bottleneck-finder, optimization-advisor)
and synthesizes their findings into a unified WorkflowResult.

Prior to v4.2.0 this was a mixin-based multi-stage pipeline. The
SDK-native implementation replaces that with `claude_agent_sdk.query()`
and `AgentDefinition` subagents while preserving the same public
interface (`PerformanceAuditWorkflow`, `perf-audit` slug) and
re-exports used by downstream code.

Copyright 2025-2026 Smart-AI-Memory
Licensed under the Apache License, Version 2.0
"""

import logging
from datetime import datetime
from pathlib import Path
from typing import Any

import claude_agent_sdk

from .agent_sdk_adapter import (
    AgentRunResult,
    AgentSDKResultAdapter,
    build_result_text,
    collect_agent_output,
    get_max_budget_usd,
    get_subagent_model,
)
from .base import BaseWorkflow, ModelTier
from .data_classes import CostReport, WorkflowResult, WorkflowStage
from .perf_audit_patterns import (
    OPTIMIZATION_ACTIONS,  # noqa: F401 — re-exported
    PERF_AUDIT_STEPS,  # noqa: F401 — re-exported
    PERF_PATTERNS,  # noqa: F401 — re-exported
)
from .perf_audit_report import (
    create_perf_audit_workflow_report,  # noqa: F401 — re-exported
    format_perf_audit_report,  # noqa: F401 — re-exported
)

logger = logging.getLogger(__name__)

# Re-export public API for backward compatibility
__all__ = [
    "PERF_AUDIT_STEPS",
    "PERF_PATTERNS",
    "PerformanceAuditWorkflow",
    "create_perf_audit_workflow_report",
    "format_perf_audit_report",
    "main",
]

# Depth → max agent turns mapping
_DEPTH_MAX_TURNS: dict[str, int] = {
    "quick": 10,
    "standard": 20,
    "deep": 40,
}

_SUBAGENT_NAMES = [
    "complexity-analyzer",
    "bottleneck-finder",
    "optimization-advisor",
]

_SYSTEM_PROMPT = """\
You are a senior performance audit orchestrator. You coordinate three \
specialized subagents to produce a unified performance audit report. \
Be thorough but concise. Cite file paths and line numbers when possible.\
"""

_TASK_PROMPT_TEMPLATE = """\
Audit the codebase at {path} using the three specialized subagents \
below. Each subagent should focus on its domain and report findings \
as structured markdown.

After all subagents finish, synthesize their findings into a single \
report with these sections:

## Summary
Overall performance health score (0-100) and a 2-3 sentence executive \
summary.

## Performance
Key performance findings across the codebase.

## Complexity
Findings from the complexity analyzer — cyclomatic complexity, nesting \
depth, and oversized functions.

## Optimization
Findings from the bottleneck finder and optimization advisor — N+1 \
patterns, unnecessary list copies, blocking I/O, missing caching, and \
prioritized suggestions with estimated impact.

## Suggestions
Actionable next steps ordered by estimated performance impact.\
"""


class PerformanceAuditWorkflow(BaseWorkflow):
    """SDK-native performance audit with three specialized subagents.

    Delegates all analysis to Claude Agent SDK subagents:
    - **complexity-analyzer** — cyclomatic complexity, nesting depth,
      oversized functions
    - **bottleneck-finder** — N+1 patterns, list copies, blocking I/O,
      missing caching
    - **optimization-advisor** — prioritized fixes with effort estimates

    The orchestrator synthesizes findings into a unified report.

    Usage::

        workflow = PerformanceAuditWorkflow()
        result = await workflow.execute(path="src/", depth="standard")
    """

    name = "perf-audit"
    description = "Agent SDK-powered performance audit with 3 specialized " "subagents"
    stages = ["agent-audit"]
    tier_map = {"agent-audit": ModelTier.CAPABLE}

    def __init__(self, **kwargs: Any) -> None:
        """Initialize workflow.

        Args:
            **kwargs: Passed to BaseWorkflow.__init__().
        """
        super().__init__(**kwargs)

    async def execute(self, **kwargs: Any) -> WorkflowResult:
        """Execute the Agent SDK performance audit.

        Args:
            **kwargs: Keyword arguments.
                path (str): Required. Directory or file to audit.
                depth (str): Audit depth — "quick", "standard",
                    or "deep". Defaults to "standard".

        Returns:
            WorkflowResult with findings, suggestions, and metadata.
        """
        path_arg: str = kwargs.get("path", "")
        depth: str = kwargs.get("depth", "standard")

        if not path_arg:
            return self._error_result("path argument is required")

        resolved_path = str(Path(path_arg).resolve())
        max_turns = _DEPTH_MAX_TURNS.get(depth, 20)

        started_at = datetime.now()

        try:
            run_result = await self._run_agent_audit(resolved_path, max_turns, depth)
            completed_at = datetime.now()

            return AgentSDKResultAdapter.from_agent_output(
                result_text=run_result.result_text,
                subagent_names=_SUBAGENT_NAMES,
                started_at=started_at,
                completed_at=completed_at,
                metadata={
                    "path": resolved_path,
                    "depth": depth,
                    "max_turns": max_turns,
                },
                agent_run_result=run_result,
            )

        except ImportError as exc:
            logger.error("Agent SDK import failed: %s", exc)
            return self._error_result(f"Agent SDK unavailable: {exc}")
        except (ConnectionError, TimeoutError) as exc:
            logger.error("Agent SDK network error: %s", exc)
            return self._error_result(f"Agent SDK connection failed: {exc}")
        except Exception as exc:  # noqa: BLE001
            # INTENTIONAL: Catch-all for unknown SDK errors to
            # return a structured WorkflowResult rather than
            # crashing the CLI.
            logger.exception(
                "Agent SDK perf audit failed: %s",
                type(exc).__name__,
            )
            return self._error_result(f"Agent SDK error: {type(exc).__name__}: {exc}")

    async def _run_agent_audit(
        self, resolved_path: str, max_turns: int, depth: str = "standard"
    ) -> AgentRunResult:
        """Run the Agent SDK audit and return result text.

        Args:
            resolved_path: Absolute path to audit.
            max_turns: Maximum agent turns.

        Returns:
            AgentRunResult with findings and SDK metadata.
        """
        assistant_parts: list[str] = []
        result_parts: list[str] = []
        run_result = AgentRunResult(result_text="No results returned.")
        async for message in claude_agent_sdk.query(
            prompt=_TASK_PROMPT_TEMPLATE.format(path=resolved_path),
            options=claude_agent_sdk.ClaudeAgentOptions(
                system_prompt=_SYSTEM_PROMPT,
                cwd=resolved_path,
                max_budget_usd=get_max_budget_usd(depth),
                allowed_tools=["Read", "Glob", "Grep", "Agent"],
                permission_mode="default",
                max_turns=max_turns,
                agents={
                    "complexity-analyzer": claude_agent_sdk.AgentDefinition(
                        description=(
                            "Complexity analyzer that measures " "code complexity metrics."
                        ),
                        prompt=(
                            "You are a complexity analyzer. Focus "
                            "on: cyclomatic complexity, nesting "
                            "depth, large functions (>50 lines), "
                            "overly complex conditionals, and deep "
                            "class hierarchies. Report each finding "
                            "with file path, line number, metric "
                            "value, and simplification advice."
                        ),
                        tools=["Read", "Glob", "Grep"],
                        model=get_subagent_model("complexity-analyzer"),
                    ),
                    "bottleneck-finder": claude_agent_sdk.AgentDefinition(
                        description=("Bottleneck finder that identifies " "performance issues."),
                        prompt=(
                            "You are a bottleneck finder. Focus "
                            "on: N+1 query patterns, unnecessary "
                            "list copies, blocking I/O in async "
                            "code, missing caching opportunities, "
                            "and inefficient data structures. "
                            "Report each finding with file path, "
                            "estimated performance impact, and a "
                            "concrete fix."
                        ),
                        tools=["Read", "Glob", "Grep"],
                        model=get_subagent_model("bottleneck-finder"),
                    ),
                    "optimization-advisor": claude_agent_sdk.AgentDefinition(
                        description=(
                            "Optimization advisor that prioritizes " "and recommends fixes."
                        ),
                        prompt=(
                            "You are an optimization advisor. "
                            "Review the findings from the "
                            "complexity analyzer and bottleneck "
                            "finder. Prioritize them by estimated "
                            "impact (high/medium/low), suggest "
                            "concrete optimizations with code "
                            "examples, and estimate the effort "
                            "required for each fix."
                        ),
                        tools=["Read", "Glob", "Grep"],
                        model=get_subagent_model("optimization-advisor"),
                    ),
                },
            ),
        ):
            sdk_result = collect_agent_output(message, assistant_parts, result_parts)
            if sdk_result is not None:
                run_result = sdk_result
        run_result.result_text = build_result_text(assistant_parts, result_parts)
        return run_result

    def _error_result(self, message: str) -> WorkflowResult:
        """Build a failed WorkflowResult with the given error message.

        Args:
            message: Human-readable error description.

        Returns:
            WorkflowResult with success=False.
        """
        now = datetime.now()
        return WorkflowResult(
            success=False,
            stages=[
                WorkflowStage(
                    name="agent-audit",
                    tier=ModelTier.CAPABLE,
                    description="Agent SDK performance audit",
                ),
            ],
            final_output=None,
            cost_report=CostReport(
                total_cost=0.0,
                baseline_cost=0.0,
                savings=0.0,
                savings_percent=0.0,
            ),
            started_at=now,
            completed_at=now,
            total_duration_ms=0,
            provider="anthropic",
            error=message,
        )


def main() -> None:
    """CLI entry point for performance audit workflow."""
    import asyncio

    async def run() -> None:
        """Run the performance audit."""
        workflow = PerformanceAuditWorkflow()
        result = await workflow.execute(path=".", depth="standard")
        output = result.final_output or {}

        print("\nPerformance Audit Results")
        print("=" * 50)
        print(f"Success: {result.success}")
        if result.error:
            print(f"Error: {result.error}")
        elif output:
            print(output)

    asyncio.run(run())


if __name__ == "__main__":
    main()
