Files
ragflow/test
bitloi 2bc8c6d35e feat(dropbox): support deleted-file sync (#14476)
### What problem does this PR solve?

Partially addresses #14362 by adding deleted-file sync support for the
Dropbox data source.

Dropbox previously did not provide the slim current-file snapshot
required by stale document reconciliation, and its sync runner returned
only document batches. As a result, enabling deleted-file sync could not
remove local documents that had been deleted from Dropbox.

This PR:
- Adds `retrieve_all_slim_docs_perm_sync()` to `DropboxConnector`.
- Reuses Dropbox metadata traversal to collect current remote file IDs
without downloading file contents.
- Wires incremental Dropbox sync to return `(document_generator,
file_list)` when `sync_deleted_files` is enabled.
- Enables the deleted-file sync toggle for Dropbox in the data source
settings UI.
- Adds regression coverage for slim snapshots, nested folders, paginated
listings, duplicate filenames, and full reindex behavior.

Tests:
- `uv run pytest test/unit_test/common/test_dropbox_connector.py -q`
- `uv run pytest test/unit_test/rag/test_sync_data_source.py -q`
- `uv run pytest test/unit_test/common/test_dropbox_connector.py
test/unit_test/rag/test_sync_data_source.py -q`
- `uv run ruff check common/data_source/dropbox_connector.py
rag/svr/sync_data_source.py
test/unit_test/common/test_dropbox_connector.py
test/unit_test/rag/test_sync_data_source.py`
- `./node_modules/.bin/eslint
src/pages/user-setting/data-source/constant/index.tsx`

### Type of change

- [x] New Feature (non-breaking change which adds functionality)
2026-04-29 19:05:11 +08:00
..


(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:v0.25.0 #Replace with the image you are using

Start the containerwait 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