from __future__ import annotations from typing import Any import pytest from fastapi.testclient import TestClient from app.api import app from app.routes import query_generation from query_planning.sources.pattern_topic_build import ( PatternTopicBuildConfig, PatternTopicBuildSource, ) from query_planning.topic_table import ( ROUTES, TopicTableGenerationError, generate_topic_table_preview, preview_to_dict, ) def _topic_payload() -> dict[str, Any]: return { "success": True, "source_url": "https://pattern.aiddit.com/api/pattern/topic_builds/1229", "build": { "id": 1229, "demand": "为小羊糊涂啊创作新选题", "demand_constraints": None, "strategies_config": {"always_on": []}, "status": "success", }, "topics": [ { "id": 1392, "status": "mature", "result": "樱花树下低角度拍少女与小羊,传递治愈感并分享穿搭。", "topic_direction": { "account_name": "小羊糊涂啊", "persona_dimensions": { "实质偏好": "樱花与穿搭", "形式偏好": "低角度和动态摆拍", "意图偏好": "治愈和种草", }, }, "points": [ { "id": 8371, "point_type": "灵感点", "point_result": "低角度仰拍小羊和彩虹光晕", "is_active": True, "item_ids": [25684, 25688], } ], "composition_items": [ { "id": 25684, "item_level": "element", "dimension": "形式", "point_type": "灵感点", "element_name": "低角度仰拍", "category_path": "/呈现/视觉/低角度", "reason": "增强视觉张力", "is_active": True, "sources": [ { "derivation_type": "external_search", "source_type": "search_case", "source_reference_id": "case-1", "reason": "草坪案例证明低角度有动感", "dataset_from": "", "source_reference_data": {"large": "must not enter prompt"}, } ], }, { "id": 25688, "item_level": "element", "dimension": "实质", "point_type": "灵感点", "element_name": "羊", "reason": "与账号名形成双关", "is_active": True, "sources": [], }, { "id": 25700, "item_level": "element", "dimension": "意图", "point_type": "目的点", "element_name": "治愈感", "reason": "满足粉丝对美好生活的向往", "is_active": True, "sources": [], }, ], "item_relations": [ { "source_item_id": 25684, "target_item_id": 25688, "reason": "低角度用于突出人与小羊互动", } ], } ], } def _llm_output() -> dict[str, Any]: needs = [] for index, (route, config) in enumerate(ROUTES.items()): needs.append( { "need_key": f"need_{route}", "route": route, "decision_context": f"决定{config['label']}怎么做", "unknown_information": f"缺少{config['label']}的可执行方法", "priority": config["priority"], "source_ref": {"point_id": 8371, "item_ids": [25684, 25688]}, "queries": [ f"{config['label']}有哪些可执行方法", "逆光人像怎么拍出彩虹光晕" if index == 0 else f"{config['label']}常见失败原因", ], } ) return {"knowledge_needs": needs} def test_topic_source_calls_read_only_detail_endpoint(): calls = [] class Response: def raise_for_status(self): return None def json(self): return _topic_payload() source = PatternTopicBuildSource( PatternTopicBuildConfig(base_url="https://pattern.example", timeout_seconds=8), http_get=lambda url, **kwargs: calls.append((url, kwargs)) or Response(), ) payload = source.fetch(1229) assert calls == [ ("https://pattern.example/api/pattern/topic_builds/1229", {"timeout": 8}) ] assert payload["build"]["id"] == 1229 assert payload["source_url"].endswith("/1229") def test_topic_table_generation_uses_six_routes_and_unified_budget(): seen = {} def chat(system, user): seen["system"] = system seen["user"] = user return _llm_output() preview = generate_topic_table_preview( _topic_payload(), topic_id=1392, max_queries=8, chat_fn=chat, ) data = preview_to_dict(preview) assert data["generator_kind"] == "topic_table" assert len(data["knowledge_needs"]) == 6 assert set(data["summary"]["route_counts"]) == set(ROUTES) assert data["summary"]["selected_count"] == 8 assert data["summary"]["persisted"] is False assert data["summary"]["search_started"] is False assert data["topic"]["dimensions"] == { "实质": ["羊"], "形式": ["低角度仰拍"], "意图": ["治愈感"], } assert "source_reference_data" not in seen["user"] assert "正好有 6 项" in seen["user"] assert "废弃" not in seen["user"] assert "What、How、Why" in seen["system"] assert data["queries"][0]["route"] == "unique_hook" def test_topic_table_generation_rejects_missing_or_duplicate_routes(): malformed = _llm_output() malformed["knowledge_needs"][-1]["route"] = "unique_hook" with pytest.raises(TopicTableGenerationError, match="不完整或有重复"): generate_topic_table_preview( _topic_payload(), topic_id=1392, max_queries=18, chat_fn=lambda _system, _user: malformed, ) def test_topic_table_prompt_and_preview_api_do_not_persist_or_search(monkeypatch): class Source: def fetch(self, topic_build_id): assert topic_build_id == 1229 return _topic_payload() monkeypatch.setattr(query_generation, "_topic_source", lambda _env: Source()) monkeypatch.setattr( query_generation, "_topic_query_chat", lambda system, user, settings: _llm_output(), ) monkeypatch.setattr( query_generation.Settings, "from_env", classmethod(lambda cls, _env: object()), ) client = TestClient(app) prompt = client.get("/api/query-generation/topic-table/prompt") assert prompt.status_code == 200 assert prompt.json()["example_request"]["topic_build_id"] == 1229 assert len(prompt.json()["routes"]) == 6 response = client.post( "/api/query-generation/topic-table/preview", json={"topic_build_id": 1229, "topic_id": 1392, "max_queries": 10}, ) assert response.status_code == 200 body = response.json() assert body["source"]["topic_id"] == 1392 assert body["summary"]["selected_count"] == 10 assert body["summary"]["persisted"] is False assert body["summary"]["search_started"] is False