from __future__ import annotations import json from types import SimpleNamespace import pytest from app.config.ai_prompts import build_default_role_prompt_bundle from app.services.ai_service_core import AIService from app.services.sstc import charter_prefill_utils from app.services.signal.draft_generator_service import DraftGeneratorService def test_default_role_prompt_bundle_is_pm_reviewer() -> None: bundle = build_default_role_prompt_bundle() assert bundle["active_role_key"] == "pm_dispatcher" role = next((item for item in bundle["roles"] if item.get("role_key") == "pm_dispatcher"), {}) assert "立项评审" in str(role.get("role_name") or "") assert "同名或相似项目" in str(role.get("system_prompt") or "") assert "MVP" in str(role.get("system_prompt") or "") @pytest.mark.asyncio async def test_generate_and_render_draft_includes_pm_sections(monkeypatch) -> None: service = DraftGeneratorService(db=object(), tenant_id=1) captured: dict[str, str] = {} async def fake_load_members(*, world_model): _ = world_model return [ {"id": 7, "name": "Alice", "workload_percent": 25.0}, {"id": 8, "name": "Bob", "workload_percent": 60.0}, ] async def fake_generate_draft_payload(*, prompt): captured["prompt"] = prompt return {} monkeypatch.setattr(service, "_load_members", fake_load_members) monkeypatch.setattr(service, "_generate_draft_payload", fake_generate_draft_payload) work_item = SimpleNamespace( draft_version=0, draft_content={}, draft_expires_at=None, confirm_message_id=None, execution_result={}, ) world_model = { "project": {"title": "企业知识库问答平台", "description": "面向内部知识库的问答能力"}, "active_projects": [ { "id": 51, "name": "AI劝退助手", "title": "AI劝退助手", "description": "项目进展与风险提醒", "status": "active", "owner_id": 10, }, { "id": 52, "name": "企业知识库问答平台 V2", "title": "企业知识库问答平台 V2", "description": "旧版知识库问答平台", "status": "active", "owner_id": 11, }, ], "recent_signals": [ {"id": 91, "title": "文档检索性能优化", "signal_type": "新需求", "status": "open"}, ], "capacity": [], } generated = await service.generate_and_persist( work_item=work_item, intent_name="project.create", message_text="我想做一个企业知识库问答项目，先帮我评估一下。", world_model=world_model, ) prompt = captured["prompt"] assert "现有活跃项目（JSON）" in prompt assert "候选相似项目（JSON）" in prompt assert "同名/相似项目列表" in prompt assert generated["draft"]["similar_projects"] assert "🔎 同名 / 相似项目：" in generated["draft_text"] assert "🚀 MVP 建议：" in generated["draft_text"] assert "📈 前景判断：" in generated["draft_text"] assert "🧩 需求清单：" in generated["draft_text"] assert "❓ 还缺的信息：" in generated["draft_text"] assert generated["draft"]["recommended_assignee_name"] == "Alice" assert generated["draft"]["recommended_assignee_workload"] == 25.0 @pytest.mark.asyncio async def test_generate_charter_seed_uses_project_context(monkeypatch) -> None: captured: dict[str, str] = {} async def fake_load_project_context(*, db, tenant_id, project_id): _ = db, tenant_id, project_id return { "id": 7, "name": "kb-v2", "title": "企业知识库问答平台", "description": "内部知识库问答升级", "status": "active", "owner_id": 10, } async def fake_load_active_projects_context(*, db, tenant_id, project_id, limit=10): _ = db, tenant_id, project_id, limit return [ { "id": 51, "name": "ai-warn", "title": "AI劝退助手", "description": "项目进展与风险提醒", "status": "active", "owner_id": 11, } ] async def fake_generate(prompt, **kwargs): captured["prompt"] = prompt return json.dumps( { "title": "内部知识库问答升级", "summary": "围绕内部知识库问答能力升级", "background": "背景说明", "objectives": ["提升检索质量"], "scope": "范围说明", "success_metrics": ["命中率提升"], "risks": ["重复建设风险"], "dependencies": ["知识库索引"], "primary_model": "gpt", "fallback_model": "gpt-mini", }, ensure_ascii=False, ) monkeypatch.setattr(charter_prefill_utils, "_load_charter_project_context", fake_load_project_context) monkeypatch.setattr(charter_prefill_utils, "_load_active_projects_context", fake_load_active_projects_context) monkeypatch.setattr(charter_prefill_utils.llm_service, "generate", fake_generate) result = await charter_prefill_utils._generate_charter_seed( db=object(), tenant_id=1, project_id=7, signal_context="AI 劝退诉求：请升级内部知识库问答能力。", ) prompt = captured["prompt"] assert "当前项目上下文" in prompt assert "企业知识库问答平台" in prompt assert "现有活跃项目（JSON）" in prompt assert "AI劝退助手" in prompt assert result["summary"] == "围绕内部知识库问答能力升级" @pytest.mark.asyncio async def test_generate_charter_from_signal_includes_project_context(monkeypatch) -> None: service = AIService() captured: dict[str, object] = {} async def fake_invoke(self, prompt, **kwargs): _ = self captured["prompt"] = prompt captured["kwargs"] = kwargs return json.dumps( { "title": "内部知识库问答升级", "summary": "围绕内部知识库问答能力升级", "background": "背景说明", "objectives": ["提升检索质量"], "scope": "范围说明", "success_metrics": ["命中率提升"], "risks": ["重复建设风险"], "dependencies": ["知识库索引"], "primary_model": "gpt", "fallback_model": "gpt-mini", }, ensure_ascii=False, ) monkeypatch.setattr(AIService, "_invoke_with_retry", fake_invoke) result = await service.generate_charter_from_signal( "AI 劝退诉求：请升级内部知识库问答能力。", tenant_id=1, db=object(), project_id=7, project_context="当前项目上下文：企业知识库问答平台", active_projects_json='[{"id":51,"title":"AI劝退助手"}]', ) prompt = str(captured["prompt"] or "") kwargs = captured["kwargs"] if isinstance(captured.get("kwargs"), dict) else {} assert "当前项目上下文：企业知识库问答平台" in prompt assert "现有活跃项目（JSON）" in prompt assert kwargs.get("project_id") == 7 assert result["summary"] == "围绕内部知识库问答能力升级"