from __future__ import annotations

from pathlib import Path

import pytest

from beaver.memory.runs import RunMemoryStore
from beaver.memory.skills import SkillLearningCandidate, SkillLearningStore
from beaver.skills.drafts import DraftService
from beaver.skills.learning import EvidenceSelector, SkillDraftSynthesizer, SkillLearningPipelineService, SkillLearningService
from beaver.skills.publisher import SkillPublisher
from beaver.skills.reviews import ReviewService
from beaver.skills.specs import SkillReviewState, SkillSpecStore


def _pipeline(tmp_path: Path) -> SkillLearningPipelineService:
    spec_store = SkillSpecStore(tmp_path)
    run_store = RunMemoryStore(tmp_path / "memory" / "runs")
    learning_store = SkillLearningStore(tmp_path / "memory" / "skills")
    draft_service = DraftService(spec_store)
    learning_service = SkillLearningService(
        run_store=run_store,
        learning_store=learning_store,
        draft_service=draft_service,
        evidence_selector=EvidenceSelector(run_store),
        synthesizer=SkillDraftSynthesizer(),
    )
    learning_store.record_learning_candidate(
        SkillLearningCandidate(
            candidate_id="candidate-1",
            kind="retire_skill",
            source_run_ids=["run-1"],
            source_session_ids=["session-1"],
            related_skill_names=["old-skill"],
            reason="not useful",
            evidence={"skill_version": "v0001"},
        )
    )
    return SkillLearningPipelineService(
        learning_store=learning_store,
        learning_service=learning_service,
        draft_service=draft_service,
        review_service=ReviewService(spec_store),
        publisher=SkillPublisher(spec_store),
    )


def test_pipeline_lists_candidates_and_moves_draft_through_review(tmp_path: Path) -> None:
    pipeline = _pipeline(tmp_path)
    draft = pipeline.draft_service.create_new_skill_draft(
        skill_name="new-skill",
        proposed_content="# New Skill\n\nDo the thing.",
        proposed_frontmatter={"description": "test skill"},
        created_by="test",
        reason="test",
    )

    review = pipeline.submit_review(draft.skill_name, draft.draft_id, requested_by="tester")
    approved = pipeline.approve(draft.skill_name, draft.draft_id, reviewer="tester")
    safety = pipeline.check_safety(draft.skill_name, draft.draft_id)
    version = pipeline.publish(draft.skill_name, draft.draft_id, publisher="tester")

    assert pipeline.list_candidates()[0].candidate_id == "candidate-1"
    assert review.status == SkillReviewState.IN_REVIEW.value
    assert approved.status == SkillReviewState.APPROVED.value
    assert safety.passed is True
    assert version.skill_name == "new-skill"
    assert pipeline.get_draft(draft.skill_name, draft.draft_id).status == SkillReviewState.PUBLISHED.value


def test_pipeline_reject_blocks_publish(tmp_path: Path) -> None:
    pipeline = _pipeline(tmp_path)
    draft = pipeline.draft_service.create_new_skill_draft(
        skill_name="blocked-skill",
        proposed_content="# Blocked\n\nNo publish.",
        proposed_frontmatter={"description": "blocked"},
        created_by="test",
        reason="test",
    )

    pipeline.reject(draft.skill_name, draft.draft_id, reviewer="tester")

    with pytest.raises(ValueError, match="approved"):
        pipeline.publish(draft.skill_name, draft.draft_id, publisher="tester")