wehub-resource-sync
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284 lines
12 KiB
Python
284 lines
12 KiB
Python
"""Knowledge HTTP e2e — all 9 endpoints via real LLM + full HTTP stack.
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Drives every knowledge API endpoint end-to-end with a **real LLM**:
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GET /categories → taxonomy auto-generation
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POST /documents → real LLM extraction → md → cascade
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GET /documents/{doc_id} → document detail with topics
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GET /topics/{topic_id} → topic content
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POST /search (keyword) → BM25 retrieval
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POST /search (vector) → ANN retrieval
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POST /search (hybrid) → RRF fusion
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POST /search (include_content) → content enrichment
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PATCH /documents/{doc_id} → metadata update
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GET /documents → paginated listing
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PUT /documents/{doc_id} → replace (delete + recreate)
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DELETE /documents/{doc_id} → cleanup
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Uses ``httpx.AsyncClient`` against ``create_app()`` with full lifespan
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(SQLite + LanceDB + Cascade + OME).
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Marked ``live_llm`` + ``slow`` — requires ``EVEROS_LLM__*`` +
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``EVEROS_EMBEDDING__*`` credentials in ``.env``.
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"""
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from __future__ import annotations
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import asyncio
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import httpx
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import pytest
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# ---------------------------------------------------------------------------
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# Test document — 3 clear sections for predictable topic extraction.
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# ---------------------------------------------------------------------------
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_TEST_DOCUMENT = """\
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# 2028 Los Angeles Olympics Budget Plan
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## Venue Construction
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The venue construction program covers 12 new facilities and 8 renovated \
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sites across greater Los Angeles. Total venue construction budget is \
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estimated at $5.3 billion, with the Intuit Dome as the centerpiece for \
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basketball events. Temporary overlay structures account for $800 million.
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## Transportation Infrastructure
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A comprehensive transportation plan connects all venue clusters via \
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dedicated Olympic lanes. The LAX-to-Downtown express shuttle operates \
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24 hours during Games time. Budget allocation for transportation is \
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$1.2 billion including temporary bus fleet leases.
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## Security Operations
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Multi-agency security coordination involves LAPD, FBI, and DHS. \
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Cybersecurity operations center monitors digital threats 24/7. \
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Drone detection perimeter extends 30 miles around the Olympic Village. \
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Security budget is $2.1 billion.
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"""
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_TEST_TITLE = "2028 LA Olympics Budget Plan"
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_PREFIX = "/api/v1/knowledge"
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# ---------------------------------------------------------------------------
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# Fixtures — reuse the shared e2e conftest (async_client + lifespan)
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# ---------------------------------------------------------------------------
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# ---------------------------------------------------------------------------
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# Tests
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# ---------------------------------------------------------------------------
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@pytest.mark.live_llm
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@pytest.mark.slow
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async def test_knowledge_full_http_lifecycle(
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async_client: httpx.AsyncClient,
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cascade_done_poll,
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) -> None:
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"""Full HTTP lifecycle: create → get → search → list → delete.
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Validates every HTTP endpoint with real LLM extraction output,
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checking response shapes, status codes, and semantic correctness
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against the known input document.
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"""
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client = async_client
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# ── 1. GET /categories — taxonomy auto-generated ──────────────
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resp = await client.get(f"{_PREFIX}/categories")
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assert resp.status_code == 200
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cats = resp.json()["data"]["categories"]
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assert len(cats) >= 10, f"Expected >=10 default categories, got {len(cats)}"
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cat_ids = {c["id"] for c in cats}
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assert "Sports" in cat_ids
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assert "Others" in cat_ids
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# ── 2. POST /documents — create with real LLM extraction ─────
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resp = await client.post(
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f"{_PREFIX}/documents",
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data={"title": _TEST_TITLE, "source_type": "file"},
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files={"file": ("budget.md", _TEST_DOCUMENT.encode(), "text/plain")},
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)
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assert resp.status_code == 201, f"Create failed: {resp.text}"
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create_data = resp.json()["data"]
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doc_id = create_data["doc_id"]
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assert doc_id.startswith("d_")
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assert create_data["topic_count"] >= 2, (
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f"3-section doc should produce >= 2 topics, got {create_data['topic_count']}"
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)
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assert create_data["category_id"], "LLM should assign a category"
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assert create_data["source_name"] == "budget.md"
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# ── 3. Wait for cascade to index all topics ─────────────────
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# The watcher needs time to detect new files, then the worker
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# processes them. Poll the GET endpoint until topics appear.
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expected_topics = create_data["topic_count"]
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async with asyncio.timeout(60.0):
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while True:
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resp = await client.get(f"{_PREFIX}/documents/{doc_id}")
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if resp.status_code == 200:
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detail = resp.json()["data"]
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if len(detail.get("topics", [])) >= expected_topics:
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break
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await asyncio.sleep(1.0)
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# Extra settle for LanceDB FTS index.
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await asyncio.sleep(1.0)
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# ── 4. GET /documents/{doc_id} — document detail ─────────────
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assert detail["doc_id"] == doc_id
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assert detail["title"] == _TEST_TITLE
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assert len(detail["summary"]) > 30, "Document summary should be meaningful"
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assert len(detail["topics"]) >= 2
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# Verify topic names relate to the input document sections.
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topic_names = [t["topic_name"].lower() for t in detail["topics"]]
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found_sections = {
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"venue": any("venue" in n for n in topic_names),
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"transport": any("transport" in n for n in topic_names),
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"security": any("security" in n for n in topic_names),
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}
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assert sum(found_sections.values()) >= 2, (
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f"Expected >= 2 of 3 sections in topic names, got: {topic_names}"
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)
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# All topics have topic_path and summary.
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for t in detail["topics"]:
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assert t["topic_path"], f"topic_path empty for {t['topic_id']}"
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assert len(t["summary"]) > 10, f"summary too short for {t['topic_id']}"
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# ── 5. GET /topics/{topic_id} — topic detail with content ────
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first_topic = detail["topics"][0]
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topic_id = first_topic["topic_id"]
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resp = await client.get(f"{_PREFIX}/topics/{topic_id}")
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assert resp.status_code == 200
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topic_detail = resp.json()["data"]
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assert topic_detail["topic_id"] == topic_id
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assert topic_detail["doc_id"] == doc_id
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assert len(topic_detail["content"]) > 20, "Topic should have content body"
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assert topic_detail["category_id"] == create_data["category_id"]
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# ── 6. POST /search — keyword search ─────────────────────────
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resp = await client.post(
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f"{_PREFIX}/search",
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json={"query": "budget", "method": "keyword", "top_k": 10},
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)
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assert resp.status_code == 200
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search_data = resp.json()["data"]
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assert search_data["total"] >= 1, "Keyword search 'budget' should find hits, got 0"
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assert search_data["took_ms"] > 0
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hit = search_data["hits"][0]
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assert hit["score"] > 0
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assert hit["topic_id"]
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assert hit["document"]["doc_id"] == doc_id
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assert hit["document"]["title"] == _TEST_TITLE
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# ── 7. POST /search — include_content=true ───────────────────
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resp = await client.post(
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f"{_PREFIX}/search",
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json={
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"query": "venue construction",
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"method": "keyword",
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"top_k": 5,
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"include_content": True,
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},
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)
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assert resp.status_code == 200
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hits_with_content = resp.json()["data"]["hits"]
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if hits_with_content:
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assert hits_with_content[0]["content"], (
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"include_content=true should populate content field"
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)
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# ── 8. POST /search — vector search ─────────────────────────
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resp = await client.post(
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f"{_PREFIX}/search",
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json={"query": "Olympic venue stadium", "method": "vector", "top_k": 5},
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)
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assert resp.status_code == 200
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vector_data = resp.json()["data"]
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assert vector_data["total"] >= 1, "Vector search should find hits"
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assert vector_data["hits"][0]["retrieval_method"] == "vector"
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# ── 9. POST /search — hybrid search ──────────────────────────
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resp = await client.post(
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f"{_PREFIX}/search",
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json={"query": "security operations", "method": "hybrid", "top_k": 5},
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)
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assert resp.status_code == 200
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hybrid_data = resp.json()["data"]
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assert hybrid_data["total"] >= 1, "Hybrid search should find hits"
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# ── 10. PATCH /documents/{doc_id} — update metadata ──────────
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new_title = "Updated Olympics Budget 2028"
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resp = await client.patch(
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f"{_PREFIX}/documents/{doc_id}",
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json={"title": new_title},
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)
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assert resp.status_code == 200
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patch_data = resp.json()["data"]
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assert patch_data["doc_id"] == doc_id
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assert "title" in patch_data["updated_fields"]
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# Verify title change persisted via GET.
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resp = await client.get(f"{_PREFIX}/documents/{doc_id}")
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assert resp.json()["data"]["title"] == new_title
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# ── 11. GET /documents — paginated listing ───────────────────
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resp = await client.get(f"{_PREFIX}/documents")
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assert resp.status_code == 200
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list_data = resp.json()["data"]
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assert list_data["total"] >= 1
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assert any(d["doc_id"] == doc_id for d in list_data["documents"])
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our_doc = next(d for d in list_data["documents"] if d["doc_id"] == doc_id)
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assert our_doc["title"] == new_title
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assert our_doc["topic_count"] >= 2
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# ── 12. PUT /documents/{doc_id} — replace with new content ───
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replacement_doc = (
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"# Revised 2028 LA Olympics Plan\n\n"
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"## Athlete Village\n"
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"The athlete village will house 15,000 athletes in UCLA campus "
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"facilities. Total village budget is $1.8 billion.\n"
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)
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resp = await client.put(
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f"{_PREFIX}/documents/{doc_id}",
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data={"title": "Revised Olympics Plan"},
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files={"file": ("revised.md", replacement_doc.encode(), "text/plain")},
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)
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assert resp.status_code == 200, f"Replace failed: {resp.text}"
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replace_data = resp.json()["data"]
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assert replace_data["doc_id"] == doc_id, "PUT should preserve doc_id"
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assert replace_data["topic_count"] >= 1
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# Wait for cascade to fully cycle: old topics deleted + new topics indexed.
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# Poll until GET returns new title AND topic names from the replacement doc.
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async with asyncio.timeout(60.0):
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while True:
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resp = await client.get(f"{_PREFIX}/documents/{doc_id}")
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if resp.status_code == 200:
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d = resp.json()["data"]
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names = [t["topic_name"].lower() for t in d.get("topics", [])]
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has_new = any("village" in n or "athlete" in n for n in names)
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has_old = any("venue" in n or "security" in n for n in names)
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if d["title"] == "Revised Olympics Plan" and has_new and not has_old:
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break
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await asyncio.sleep(1.0)
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# Verify replaced content.
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resp = await client.get(f"{_PREFIX}/documents/{doc_id}")
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replaced = resp.json()["data"]
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assert replaced["title"] == "Revised Olympics Plan"
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# ── 13. DELETE /documents/{doc_id} ────────────────────────────
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resp = await client.delete(f"{_PREFIX}/documents/{doc_id}")
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assert resp.status_code == 200
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del_data = resp.json()["data"]
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assert del_data["doc_id"] == doc_id
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assert del_data["deleted_topics"] >= 1
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# Note: cascade cleanup of SQLite/LanceDB rows is eventually
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# consistent (scanner interval + FK constraint retry). The service
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# DELETE removes md files immediately; the cascade handler catches
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# up on subsequent scan passes. Integration tests verify cascade
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# cleanup; this e2e test verifies the HTTP contract only.
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