feat(avatar): optimize embedded H5 management flow

This commit is contained in:
stefanfeng
2026-08-27 09:27:17 +08:00
parent c37294be17
commit e2b02ddf30
10 changed files with 307 additions and 63 deletions
@@ -2,9 +2,17 @@ from pathlib import Path
from types import SimpleNamespace
from unittest.mock import patch
from fastapi.testclient import TestClient
from database import SessionLocal
from main import app
from models import KnowledgeChunk, KnowledgeDoc
from routers.knowledge import _doc_payload
client = TestClient(app)
def test_doc_payload_reports_whether_the_persisted_file_exists(tmp_path: Path):
avatar_id = "avatar-1"
stored_name = "knowledge.md"
@@ -21,3 +29,66 @@ def test_doc_payload_reports_whether_the_persisted_file_exists(tmp_path: Path):
assert _doc_payload(doc)["filePresent"] is False
stored_file.write_text("knowledge", encoding="utf-8")
assert _doc_payload(doc)["filePresent"] is True
def test_upload_marks_vectorization_failure_instead_of_staying_processing(
tmp_path: Path,
authorization_context,
):
context = authorization_context
with (
patch("routers.knowledge.UPLOAD_DIR", str(tmp_path)),
patch("routers.knowledge.embeddings.embed", side_effect=RuntimeError("provider unavailable")),
):
response = client.post(
f"/api/avatar/{context['avatar'].id}/knowledge/docs",
headers=context["owner_headers"],
files={"file": ("knowledge.md", b"# Knowledge\n\nTest content", "text/markdown")},
)
payload = response.json()["data"]
assert payload["status"] == "failed"
assert payload["vectorized"] is False
assert payload["chunkCount"] == 0
db = SessionLocal()
try:
stored = db.query(KnowledgeDoc).filter(KnowledgeDoc.id == payload["id"]).one()
assert stored.status == "failed"
assert db.query(KnowledgeChunk).filter(KnowledgeChunk.doc_id == stored.id).count() == 0
db.delete(stored)
db.commit()
finally:
db.close()
def test_markdown_upload_commits_ready_document_and_chunks_together(
tmp_path: Path,
authorization_context,
):
context = authorization_context
with (
patch("routers.knowledge.UPLOAD_DIR", str(tmp_path)),
patch("routers.knowledge.embeddings.embed", return_value=[[1.0, 0.0]]),
):
response = client.post(
f"/api/avatar/{context['avatar'].id}/knowledge/docs",
headers=context["owner_headers"],
files={"file": ("knowledge.md", b"# Knowledge\n\nTest content", "text/markdown")},
)
payload = response.json()["data"]
assert payload["status"] == "ready"
assert payload["vectorized"] is True
assert payload["chunkCount"] == 1
db = SessionLocal()
try:
stored = db.query(KnowledgeDoc).filter(KnowledgeDoc.id == payload["id"]).one()
assert stored.status == "ready"
assert db.query(KnowledgeChunk).filter(KnowledgeChunk.doc_id == stored.id).count() == 1
db.query(KnowledgeChunk).filter(KnowledgeChunk.doc_id == stored.id).delete()
db.delete(stored)
db.commit()
finally:
db.close()