diff --git a/HANDOFF.md b/HANDOFF.md index c3e4654..01c3260 100644 --- a/HANDOFF.md +++ b/HANDOFF.md @@ -52,6 +52,7 @@ uv run pytest -q ## 已验证与尚未验证 - 部署镜像内完整后端测试：**19 通过、0 跳过**，包括 DOCX/PPTX 转换与页面图像测试。宿主机运行结果为 18 通过、1 跳过，因为宿主机未安装 LibreOffice；部署容器内为 25.2.3.2。另已用课程 DOCX 和验收 PPTX 实际验证页数、文字及页面图片。 +- 2026-09-25：后端测试已改用独立 PostgreSQL + pgvector，并通过真实 DeepSeek 和本地 BGE-M3 模型测试。19 个其他测试通过；使用课程示例材料的完整流程单独重跑通过，22 个评分项全部完成，教师复核和导出检查通过。测试命令见 `docs/DEPLOYMENT.md`。 - 前端生产构建通过；Compose 的 PostgreSQL、Redis、API、worker、Web 当前均已启动，首页、深链接、`/api/health`、课程及仪表盘 API 返回正常。数据库版本为 `0002`；全新 SQLite 数据库迁移至 `0002` 也已验证。 - RQ worker 曾在空闲期间因 Redis 连接超时退出，日志显示正常退出码 0；已在 `compose.yaml` 设置 `restart: unless-stopped` 并重新启动。接手后应观察是否反复超时。 - 使用 `docs/` 的四份示例报告及生成的汇报 PPTX，经目录扫描、确认、课程资料入库、真实 BGE-M3/pgvector 检索和真实 DeepSeek API 完成批次 `3`：**22/22 项成功**。首轮有 1 项引文不匹配，重试后成功；保留了成功项。项目索引重建后有 316 段、平均 506 字，向量均为 1024 维；77 条评分证据均能匹配对应文档页的原文和页面图片。 diff --git a/backend/Dockerfile b/backend/Dockerfile index 99bb175..80350b6 100644 --- a/backend/Dockerfile +++ b/backend/Dockerfile @@ -5,5 +5,7 @@ WORKDIR /app COPY --from=ghcr.io/astral-sh/uv:0.11.0 /uv /uvx /bin/ COPY pyproject.toml uv.lock ./ RUN uv sync --frozen --no-dev --extra ocr +ARG INCLUDE_DEV=false +RUN if [ "$INCLUDE_DEV" = "true" ]; then uv sync --frozen --group dev --extra ocr; fi COPY . . ENV PATH=/app/.venv/bin:$PATH PYTHONPATH=/app diff --git a/backend/tests/conftest.py b/backend/tests/conftest.py index 3523fc8..144f581 100644 --- a/backend/tests/conftest.py +++ b/backend/tests/conftest.py @@ -1,13 +1,28 @@ import os from pathlib import Path +from uuid import uuid4 import pytest +from alembic import command +from alembic.config import Config +from sqlalchemy import create_engine +from sqlalchemy.engine import make_url from sqlalchemy.orm import sessionmaker from wisegrade.config import get_settings -from wisegrade.db import Base, engine_for +from wisegrade.db import engine_for from wisegrade.seed import seed_initial -from wisegrade import models # noqa: F401 + + +@pytest.fixture(scope="session") +def test_database_url(): + value = os.environ.get("TEST_DATABASE_URL") + if not value: + pytest.fail("Set TEST_DATABASE_URL to a dedicated PostgreSQL database named wisegrade_tests") + url = make_url(value) + if url.drivername != "postgresql+psycopg" or url.database != "wisegrade_tests": + pytest.fail("TEST_DATABASE_URL must use postgresql+psycopg and the wisegrade_tests database") + return url @pytest.fixture @@ -24,14 +39,35 @@ def environment(tmp_path, monkeypatch): @pytest.fixture -def session_factory(environment): - engine = engine_for(f"sqlite:///{environment / 'test.db'}") - Base.metadata.create_all(engine) - factory = sessionmaker(bind=engine, expire_on_commit=False) - with factory() as db: - seed_initial(db) - yield factory - engine.dispose() +def session_factory(environment, monkeypatch, test_database_url): + admin_engine = create_engine(test_database_url, isolation_level="AUTOCOMMIT") + name = f"wisegrade_test_{uuid4().hex}" + engine = None + created = False + try: + with admin_engine.connect() as connection: + connection.exec_driver_sql(f'CREATE DATABASE "{name}"') + created = True + url = test_database_url.set(database=name).render_as_string(hide_password=False) + monkeypatch.setenv("DATABASE_URL", url) + get_settings.cache_clear() + backend_root = Path(__file__).resolve().parents[1] + migration_config = Config(str(backend_root / "alembic.ini")) + migration_config.set_main_option("script_location", str(backend_root / "migrations")) + command.upgrade(migration_config, "head") + engine = engine_for(url) + factory = sessionmaker(bind=engine, expire_on_commit=False) + with factory() as db: + seed_initial(db) + yield factory + finally: + if engine is not None: + engine.dispose() + get_settings.cache_clear() + if created: + with admin_engine.connect() as connection: + connection.exec_driver_sql(f'DROP DATABASE "{name}" WITH (FORCE)') + admin_engine.dispose() @pytest.fixture diff --git a/backend/tests/test_api.py b/backend/tests/test_api.py index 333a879..ac86618 100644 --- a/backend/tests/test_api.py +++ b/backend/tests/test_api.py @@ -55,7 +55,7 @@ def test_missing_material_is_explicit_and_reviewable(session_factory): client = client_for(session_factory) try: batch_id = client.post("/api/scoring-batches", json={"course_version_id": 1, "rubric_version_id": 1}).json()["id"] - run_batch(batch_id, session_factory=session_factory, client_factory=lambda db, batch: object()) + run_batch(batch_id, session_factory=session_factory) status = client.get(f"/api/scoring-batches/{batch_id}/progress").json() assert status["status"] == "partial" and status["progress_done"] == status["progress_total"] == 22 result = client.get(f"/api/scoring-batches/{batch_id}/scores").json()[0] diff --git a/backend/tests/test_foundation.py b/backend/tests/test_foundation.py index c4b4807..60be701 100644 --- a/backend/tests/test_foundation.py +++ b/backend/tests/test_foundation.py @@ -1,13 +1,19 @@ from pathlib import Path import pytest -from sqlalchemy import select +from sqlalchemy import select, text from wisegrade.models import CourseObjective, CourseVersion, GraduationIndicator, RubricCriterion, RubricScoreLevel, RubricVersion, TopicDirection from wisegrade.rules import RubricData, totals from wisegrade.storage import classify, extract_identity, parse_student_folder, secure_path, sha256 +def test_postgresql_migrations_and_vector_extension(db): + assert db.bind.dialect.name == "postgresql" + assert db.scalar(text("SELECT version_num FROM alembic_version")) == "0002" + assert db.scalar(text("SELECT extname FROM pg_extension WHERE extname = 'vector'")) == "vector" + + def test_seeded_course_and_weights(db): version = db.scalar(select(CourseVersion)) rubric = db.scalar(select(RubricVersion)) diff --git a/backend/tests/test_llm_and_rag.py b/backend/tests/test_llm_and_rag.py index 3655ef0..ba77c95 100644 --- a/backend/tests/test_llm_and_rag.py +++ b/backend/tests/test_llm_and_rag.py @@ -1,17 +1,22 @@ -import json - -import httpx import pytest +from PIL import Image, ImageDraw from sqlalchemy import select -from wisegrade.llm import DeepSeekClient, ModelError, ScoreResult, validate_score -from wisegrade.models import AppSetting, KnowledgeChunk +from wisegrade.llm import DeepSeekClient, FactResult, ModelError, ScoreResult, validate_score +from wisegrade.models import AppSetting, KnowledgeChunk, Project, Student from wisegrade.rag import ingest, local_encoder, retrieve, split_pages from wisegrade.settings_store import model_config, save_model_config -def fake_embed(texts): - return [[1.0] + [0.0] * 1023 for _ in texts] +def make_project(db, number): + student = Student(student_no=f"90000000{number}", name=f"测试学生{number}") + db.add(student) + db.flush() + project = Project(course_version_id=1, student_id=student.id, topic=f"测试项目{number}", + source_dir=f"tests/student-{number}") + db.add(project) + db.flush() + return project.id def test_json_validation_and_evidence(): @@ -37,33 +42,28 @@ def test_evidence_quote_resolves_pdf_line_breaks_and_page(): assert checked.evidence[0].quote in chunks[0]["text"] -def test_deepseek_adapter_mock_and_key_not_in_error(tmp_path): +@pytest.mark.integration +def test_deepseek_adapter_live_with_image(tmp_path): image = tmp_path / "page.png" - image.write_bytes(b"png fixture") - def handler(request): - assert request.url.path == "/chat/completions" - assert request.headers["Authorization"] == "Bearer fake-secret" - content = json.loads(request.content)["messages"][1]["content"] - assert content[1]["type"] == "image_url" and content[1]["image_url"]["url"].startswith("data:image/png;base64,") - return httpx.Response(200, json={"choices": [{"message": {"content": json.dumps({"criterion_id": "x", "score": 0, - "max_score": 10, "reason": "缺失", "evidence": [], "confidence": .2})}}]}) - client = DeepSeekClient(base_url="https://example.test", api_key="fake-secret", retries=0, transport=httpx.MockTransport(handler)) - assert client.json_call("prompt", {}, ScoreResult, images=[str(image)]).score == 0 - bad = DeepSeekClient(base_url="https://example.test", api_key="fake-secret", retries=0, - transport=httpx.MockTransport(lambda _: httpx.Response(500, text="fake-secret"))) - with pytest.raises(ModelError) as error: - bad.json_call("prompt", {}, ScoreResult) - assert "fake-secret" not in str(error.value) + picture = Image.new("RGB", (320, 100), "white") + ImageDraw.Draw(picture).text((20, 30), "TEST 123", fill="black") + picture.save(image) + result = DeepSeekClient().json_call( + "从用户提供的JSON中复制topic字段，原样返回到JSON对象的topic字段。", + {"topic": "真实模型连通测试"}, FactResult, images=[str(image)]) + assert result.topic == "真实模型连通测试" def test_project_isolation_and_chunk_metadata(db): + project_a = make_project(db, 1) + project_b = make_project(db, 2) pages = [{"page_number": 3, "section": "实验", "text": "机器人实验数据和分析"}] - ingest(db, course_version_id=1, project_id=101, submission_file_id=None, title="学生A", category="stage3", - source_hash="a", pages=pages, embedder=fake_embed) - ingest(db, course_version_id=1, project_id=102, submission_file_id=None, title="学生B", category="stage3", - source_hash="b", pages=[{**pages[0], "text": "另一个学生的秘密"}], embedder=fake_embed) - hits = retrieve(db, course_version_id=1, project_id=101, category="stage3", query="实验数据", embedder=fake_embed) - assert hits and all(hit["project_id"] == 101 and hit["page"] == 3 for hit in hits) + ingest(db, course_version_id=1, project_id=project_a, submission_file_id=None, title="学生A", category="stage3", + source_hash="a", pages=pages) + ingest(db, course_version_id=1, project_id=project_b, submission_file_id=None, title="学生B", category="stage3", + source_hash="b", pages=[{**pages[0], "text": "另一个学生的秘密"}]) + hits = retrieve(db, course_version_id=1, project_id=project_a, category="stage3", query="实验数据") + assert hits and all(hit["project_id"] == project_a and hit["page"] == 3 for hit in hits) assert "秘密" not in str(hits) @@ -76,15 +76,16 @@ def test_short_paragraphs_share_a_page_chunk(): def test_stale_knowledge_index_reuses_document_id(db): + project_id = make_project(db, 1) pages = [{"page_number": 1, "text": "实验方案与测量结果"}] - document = ingest(db, course_version_id=1, project_id=101, submission_file_id=None, - title="报告", category="stage3", source_hash="same-source", pages=pages, embedder=fake_embed) + document = ingest(db, course_version_id=1, project_id=project_id, submission_file_id=None, + title="报告", category="stage3", source_hash="same-source", pages=pages) old_chunk = db.scalar(select(KnowledgeChunk).where(KnowledgeChunk.document_id == document.id)) old_chunk.text = "过时片段" document.index_version = 1 db.commit() - reindexed = ingest(db, course_version_id=1, project_id=101, submission_file_id=None, - title="报告", category="stage3", source_hash="same-source", pages=pages, embedder=fake_embed) + reindexed = ingest(db, course_version_id=1, project_id=project_id, submission_file_id=None, + title="报告", category="stage3", source_hash="same-source", pages=pages) assert reindexed.id == document.id and reindexed.index_version == 2 assert db.scalar(select(KnowledgeChunk.text).where(KnowledgeChunk.document_id == document.id)) == pages[0]["text"] diff --git a/backend/tests/test_workflow.py b/backend/tests/test_workflow.py index 7eb8467..7e6fa34 100644 --- a/backend/tests/test_workflow.py +++ b/backend/tests/test_workflow.py @@ -4,37 +4,13 @@ from pathlib import Path import pymupdf as fitz import pytest from fastapi.testclient import TestClient -from sqlalchemy import select -from wisegrade.config import get_settings from wisegrade.db import get_db -from wisegrade.llm import ConsistencyResult, FactResult, ScoreResult from wisegrade.main import app -from wisegrade.models import CourseVersion, CriterionScore, RubricVersion, ScoringBatch, TeacherRevision -from wisegrade.rag import retrieve from wisegrade.scoring import run_batch from wisegrade.storage import scan -def fake_embed(texts): - return [[1.0] + [0.0] * 1023 for _ in texts] - - -class FakeModel: - def json_call(self, _prompt, payload, schema, images=None): - if schema is FactResult: - return FactResult(topic="自动化实践示例") - if schema is ConsistencyResult: - return ConsistencyResult() - criterion = payload["criterion"] - evidence = payload["evidence"][0] - return ScoreResult(criterion_id=criterion["criterion_id"], score=criterion["max_score"] / 2, - max_score=criterion["max_score"], reason="示例证据支持部分要求", - evidence=[{"chunk_id": evidence["chunk_id"], "page": evidence["page"], - "quote": evidence["text"][:min(12, len(evidence["text"]))]}], - missing_evidence=[], suggestion="补充量化论证", confidence=.7) - - def make_pdf(path, title): pdf = fitz.open() page = pdf.new_page() @@ -70,14 +46,20 @@ def test_docs_examples_end_to_end(environment, session_factory): response = client.post("/api/scoring-batches", json={"course_version_id": 1, "rubric_version_id": 1}) assert response.status_code == 200, response.text batch_id = response.json()["id"] - run_batch(batch_id, session_factory=session_factory, client_factory=lambda db, batch: FakeModel(), embedder=fake_embed, - retriever=lambda db, **kwargs: retrieve(db, embedder=fake_embed, **kwargs)) + run_batch(batch_id, session_factory=session_factory) + progress = client.get(f"/api/scoring-batches/{batch_id}/progress").json() + assert progress["status"] == "completed", progress + assert progress["progress_done"] == progress["progress_total"] == 22 result = client.get(f"/api/projects/{project_id}/scores?batch_id={batch_id}").json() - assert result["totals"]["overall"] == 50 - assert all(row["evidence"] and row["evidence"][0]["page"] >= 1 for row in result["rows"]) - assert client.get(result["rows"][0]["evidence"][0]["image_url"]).content[:8] == b"\x89PNG\r\n\x1a\n" + assert result["totals"]["overall"] is not None + assert all(row["status"] == "scored" and + (row["model_score"] == 0 or row["evidence"] and row["evidence"][0]["page"] >= 1) + for row in result["rows"]), result["rows"] + evidence_row = next(row for row in result["rows"] if row["evidence"] and row["evidence"][0]["image_url"]) + assert client.get(evidence_row["evidence"][0]["image_url"]).content[:8] == b"\x89PNG\r\n\x1a\n" score_id = result["rows"][0]["score_id"] - reviewed = client.put(f"/api/criterion-scores/{score_id}/review", json={"score": 20, "comment": "教师核定", "reason": "核查原文"}) + teacher_score = 0 if result["rows"][0]["model_score"] != 0 else 1 + reviewed = client.put(f"/api/criterion-scores/{score_id}/review", json={"score": teacher_score, "comment": "教师核定", "reason": "核查原文"}) assert reviewed.status_code == 200 assert reviewed.json()["model_score"] != reviewed.json()["teacher_score"] assert len(client.get(f"/api/criterion-scores/{score_id}/revisions").json()) == 1 diff --git a/compose.yaml b/compose.yaml index 2b96674..82b38dd 100644 --- a/compose.yaml +++ b/compose.yaml @@ -13,6 +13,38 @@ services: retries: 12 redis: image: redis:7-alpine + test-db: + profiles: [test] + image: pgvector/pgvector:pg16 + environment: + POSTGRES_DB: wisegrade_tests + POSTGRES_USER: wisegrade_test + POSTGRES_PASSWORD: wisegrade_test + tmpfs: + - /var/lib/postgresql/data + healthcheck: + test: [CMD-SHELL, "pg_isready -U wisegrade_test -d wisegrade_tests"] + interval: 5s + retries: 12 + test: + profiles: [test] + build: + context: ./backend + args: + INCLUDE_DEV: "true" + env_file: .env + environment: + DATABASE_URL: postgresql+psycopg://wisegrade_test:wisegrade_test@test-db:5432/wisegrade_tests + TEST_DATABASE_URL: postgresql+psycopg://wisegrade_test:wisegrade_test@test-db:5432/wisegrade_tests + EMBEDDING_MODEL_PATH: /models/bge-m3 + OCR_MODEL_DIR: /models/ocr + volumes: + - ./backend/tests:/app/tests:ro + - ./docs:/docs:ro + - ./models:/models:ro + depends_on: + test-db: {condition: service_healthy} + command: ["pytest", "-q"] api: build: ./backend env_file: .env diff --git a/docs/DEPLOYMENT.md b/docs/DEPLOYMENT.md index 918e365..b13b065 100644 --- a/docs/DEPLOYMENT.md +++ b/docs/DEPLOYMENT.md @@ -96,10 +96,17 @@ Python 依赖由 `backend/pyproject.toml` 管理： cd backend uv sync --extra ocr --group dev uv run alembic upgrade head -uv run pytest uv run uvicorn wisegrade.main:app --reload ``` +测试从仓库根目录运行： + +```bash +docker compose --profile test run --build --rm test +``` + +测试使用独立的 PostgreSQL 16 + pgvector 容器，不连接业务数据库。每个数据库测试创建临时数据库，执行 Alembic 迁移后运行，结束时删除；`test-db` 的数据目录为 tmpfs，不会写入业务数据卷。测试会从 `.env` 读取真实 DeepSeek API Key，并加载 `models/bge-m3` 和 `models/ocr` 中的离线模型；完整流程测试会发起真实模型请求。在宿主机直接运行 `uv run pytest` 时，需先设置指向专用 `wisegrade_tests` 数据库的 `TEST_DATABASE_URL`（使用 `postgresql+psycopg` 驱动，账号需有创建数据库的权限），并提供可用的模型配置。 + 本地开发需提供 PostgreSQL、Redis 和与容器路径一致的挂载目录；可用 Compose 启动 `db` 和 `redis`。Vite 前端： ```bash @@ -108,7 +115,7 @@ npm install npm run dev ``` -开发服务器将 `/api` 代理到 `localhost:8000`。测试中的 DeepSeek 请求使用 mock，不会使用真实 API Key。集成测试从仓库 `docs/` 复制阶段报告 1、2、3 与最终报告，并生成一份汇报 PDF 测试材料。 +开发服务器将 `/api` 代理到 `localhost:8000`。集成测试从仓库 `docs/` 复制阶段报告 1、2、3 与最终报告，并生成一份汇报 PDF 测试材料。 ## 故障定位