mirror of
https://github.com/infiniflow/ragflow.git
synced 2026-03-21 06:28:10 +08:00
c3f79dbcb0
### What problem does this PR solve? Fixes [#13505](https://github.com/infiniflow/ragflow/issues/13505): Jira incremental sync could miss updated issues after initial sync, especially near time boundaries. Root cause: - Jira JQL uses minute-level precision for `updated` filters. - Incremental windows had no overlap buffer, so boundary updates could be skipped. - Sync log cursor tracking used a backward-facing update for `poll_range_start`. - Existing-doc updates in `upload_document` lacked a KB ownership guard for doc-id collisions. What changed: - Added Jira incremental overlap buffer (`time_buffer_seconds`, defaulting to `JIRA_SYNC_TIME_BUFFER_SECONDS`) when building JQL lower-bound time. - Preserved second-level post-filtering to avoid duplicate reprocessing while still catching boundary updates. - Improved Jira sync logging to include start/end window and overlap configuration. - Updated sync cursor tracking in `increase_docs` to keep `poll_range_start` moving forward with max update time. - Added KB ID safety check before updating existing document records in `upload_document`. Verification performed: - Python syntax compile checks passed for modified files. - Manual verification flow: 1. Run full Jira sync. 2. Edit an already-indexed Jira issue. 3. Run next incremental sync. 4. Confirm updated content is re-ingested into KB. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) --------- Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
(1). Deploy RAGFlow services and images
https://ragflow.io/docs/build_docker_image
(2). Configure the required environment for testing
Install Python dependencies (including test dependencies):
uv sync --python 3.12 --only-group test --no-default-groups --frozen
Activate the environment:
source .venv/bin/activate
Install SDK:
uv pip install sdk/python
Modify the .env file: Add the following code:
COMPOSE_PROFILES=${COMPOSE_PROFILES},tei-cpu
TEI_MODEL=BAAI/bge-small-en-v1.5
RAGFLOW_IMAGE=infiniflow/ragflow:v0.24.0 #Replace with the image you are using
Start the container（wait two minutes）:
docker compose -f docker/docker-compose.yml up -d
(3). Test Elasticsearch
a) Run sdk tests against Elasticsearch:
export HTTP_API_TEST_LEVEL=p2
export HOST_ADDRESS=http://127.0.0.1:9380 # Ensure that this port is the API port mapped to your localhost
pytest -s --tb=short --level=${HTTP_API_TEST_LEVEL} test/testcases/test_sdk_api
b) Run http api tests against Elasticsearch:
pytest -s --tb=short --level=${HTTP_API_TEST_LEVEL} test/testcases/test_http_api
(4). Test Infinity
Modify the .env file:
DOC_ENGINE=${DOC_ENGINE:-infinity}
Start the container:
docker compose -f docker/docker-compose.yml down -v
docker compose -f docker/docker-compose.yml up -d
a) Run sdk tests against Infinity:
DOC_ENGINE=infinity pytest -s --tb=short --level=${HTTP_API_TEST_LEVEL} test/testcases/test_sdk_api
b) Run http api tests against Infinity:
DOC_ENGINE=infinity pytest -s --tb=short --level=${HTTP_API_TEST_LEVEL} test/testcases/test_http_api