steven_li
8a12c30141
新增内部Task系统，包括验证、反馈门控机制，实现自动质量验证 (通过率>=0.75)和用户反馈闭环(satisfied/revise/abandon)。 实现Agent Team v1协调器，支持sequence/parallel/dag执行策略， sub-agent复用主AgentLoop，每个run使用独立memory snapshot。 建立Skill学习pipeline，包含draft/审核/发布/回滚完整生命周期， 通过Task验证通过且用户满意才生成学习候选。 重构目录结构，移除third_party依赖，建立统一engine内核， 所有agent共享运行时基础组件。 更新ContextBuilder清理provider消息字段，增强SkillContext版本管理， 集成TaskExecutionPlanner和TaskSkillResolver实现技能解析机制。
85 lines
3.3 KiB
Python
85 lines
3.3 KiB
Python
from __future__ import annotations
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from pathlib import Path
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import pytest
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from beaver.memory.runs import RunMemoryStore
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from beaver.memory.skills import SkillLearningCandidate, SkillLearningStore
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from beaver.skills.drafts import DraftService
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from beaver.skills.learning import EvidenceSelector, SkillDraftSynthesizer, SkillLearningPipelineService, SkillLearningService
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from beaver.skills.publisher import SkillPublisher
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from beaver.skills.reviews import ReviewService
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from beaver.skills.specs import SkillReviewState, SkillSpecStore
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def _pipeline(tmp_path: Path) -> SkillLearningPipelineService:
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spec_store = SkillSpecStore(tmp_path)
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run_store = RunMemoryStore(tmp_path / "memory" / "runs")
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learning_store = SkillLearningStore(tmp_path / "memory" / "skills")
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draft_service = DraftService(spec_store)
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learning_service = SkillLearningService(
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run_store=run_store,
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learning_store=learning_store,
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draft_service=draft_service,
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evidence_selector=EvidenceSelector(run_store),
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synthesizer=SkillDraftSynthesizer(),
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)
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learning_store.record_learning_candidate(
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SkillLearningCandidate(
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candidate_id="candidate-1",
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kind="retire_skill",
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source_run_ids=["run-1"],
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source_session_ids=["session-1"],
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related_skill_names=["old-skill"],
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reason="not useful",
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evidence={"skill_version": "v0001"},
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)
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)
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return SkillLearningPipelineService(
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learning_store=learning_store,
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learning_service=learning_service,
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draft_service=draft_service,
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review_service=ReviewService(spec_store),
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publisher=SkillPublisher(spec_store),
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)
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def test_pipeline_lists_candidates_and_moves_draft_through_review(tmp_path: Path) -> None:
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pipeline = _pipeline(tmp_path)
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draft = pipeline.draft_service.create_new_skill_draft(
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skill_name="new-skill",
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proposed_content="# New Skill\n\nDo the thing.",
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proposed_frontmatter={"description": "test skill"},
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created_by="test",
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reason="test",
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)
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review = pipeline.submit_review(draft.skill_name, draft.draft_id, requested_by="tester")
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approved = pipeline.approve(draft.skill_name, draft.draft_id, reviewer="tester")
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safety = pipeline.check_safety(draft.skill_name, draft.draft_id)
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version = pipeline.publish(draft.skill_name, draft.draft_id, publisher="tester")
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assert pipeline.list_candidates()[0].candidate_id == "candidate-1"
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assert review.status == SkillReviewState.IN_REVIEW.value
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assert approved.status == SkillReviewState.APPROVED.value
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assert safety.passed is True
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assert version.skill_name == "new-skill"
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assert pipeline.get_draft(draft.skill_name, draft.draft_id).status == SkillReviewState.PUBLISHED.value
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def test_pipeline_reject_blocks_publish(tmp_path: Path) -> None:
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pipeline = _pipeline(tmp_path)
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draft = pipeline.draft_service.create_new_skill_draft(
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skill_name="blocked-skill",
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proposed_content="# Blocked\n\nNo publish.",
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proposed_frontmatter={"description": "blocked"},
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created_by="test",
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reason="test",
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)
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pipeline.reject(draft.skill_name, draft.draft_id, reviewer="tester")
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with pytest.raises(ValueError, match="approved"):
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pipeline.publish(draft.skill_name, draft.draft_id, publisher="tester")
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