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### What problem does this PR solve? Closes #15187. RAGFlow shipped a Slack connector (`common/data_source/slack_connector.py`) but it was never usable: `Slack._generate()` in the sync worker was a `pass` stub, the connector's document-generating code was incompatible with the current data model, and Slack was commented out of the data-source settings UI. As a result, teams had no way to index Slack channels/threads into a knowledge base. This PR completes the connector end to end. **Backend** - `common/data_source/slack_connector.py` - Rewrote `thread_to_doc` to produce a blob-based `Document` (`extension`/`blob`/`size_bytes`). The previous implementation built the doc with a `sections=[...]` argument and omitted the now-required `blob`/`extension`/ `size_bytes` fields, so it raised a validation error against the current `Document` model. Thread messages are now cleaned and flattened into a single UTF-8 text blob. - Added `load_from_state()` / `poll_source(start, end)` generators. The connector's checkpoint interface is a no-op stub, so both full and incremental syncs run through a single channel-iterating generator built on the existing module helpers (`get_channels`, `filter_channels`, `get_channel_messages`, `_process_message`), with per-channel thread de-duplication. - `rag/svr/sync_data_source.py` - Implemented `Slack._generate()`. Credentials are loaded via `StaticCredentialsProvider` (the connector requires `slack_bot_token` and does not support `load_credentials`). Supports full reindex and incremental polling from `poll_range_start`, plus the optional channel filter. Modeled on the Confluence/Dropbox wrappers. - `SlackConnector` was already exported from `common/data_source/__init__.py`. **Frontend (`web/`)** - Enabled the `SLACK` data-source enum and added its form fields (Slack bot token + optional channel filter), default values, display metadata, and a Slack icon. - Added `slackDescription` / `slackBotTokenTip` / `slackChannelsTip` strings to `en.ts` and `zh.ts`. **Tests** - `test/unit_test/data_source/test_slack_connector_unit.py`: unit tests covering credential loading (`load_credentials` raises, `set_credentials_provider` initializes clients, missing credentials raises) and document generation (standalone message + flattened thread, blob/extension/size_bytes/metadata, and the incremental poll time window). All 5 pass; `ruff check` is clean. Required Slack scopes: `channels:read`, `channels:history`, `users:read`. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
(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 3.13 --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=${COMPOSE_PROFILES},tei-cpu
TEI_MODEL=BAAI/bge-small-en-v1.5
RAGFLOW_IMAGE=infiniflow/ragflow:v0.25.6 #Replace with the image you are using
Start the container（wait two minutes）:
docker compose -f docker/docker-compose.yml up -d
(3). Test Elasticsearch
a) Run sdk tests against Elasticsearch:
export HTTP_API_TEST_LEVEL=p2
export HOST_ADDRESS=http://127.0.0.1:9380 # Ensure that this port is the API port mapped to your localhost
pytest -s --tb=short --level=${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