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### What problem does this PR solve?
## Summary
Refactor the dataset API layer into a clean service/REST separation
pattern, add a unified `/index` API for graph/raptor/mindmap operations,
and introduce several new dataset management endpoints with full test
coverage.
## Changes
### Service Layer (`dataset_api_service.py`)
- Added `trace_index(dataset_id, tenant_id, index_type)` — unified trace
function for all index types
- Added `run_index`, `delete_index` service functions
- Added `get_dataset`, `get_ingestion_summary`, `list_ingestion_logs`,
`get_ingestion_log`
- Added `run_embedding`, `list_tags`, `aggregate_tags`, `delete_tags`,
`rename_tag`
- Added `get_flattened_metadata`, `get_auto_metadata`,
`update_auto_metadata`
### REST API Layer (`dataset_api.py`)
**New unified routes:**
| Method | Route | Description |
|--------|-------|-------------|
| POST | `/datasets/<id>/index?type=graph\|raptor\|mindmap` | Run index
task |
| GET | `/datasets/<id>/index?type=graph\|raptor\|mindmap` | Trace index
task |
| DELETE | `/datasets/<id>/<index_type>` | Delete index |
| GET | `/datasets/<id>` | Get dataset details |
| GET | `/datasets/<id>/ingestions/summary` | Ingestion summary |
| GET | `/datasets/<id>/ingestions` | List ingestion logs |
| GET | `/datasets/<id>/ingestions/<log_id>` | Get single ingestion log
|
| POST | `/datasets/<id>/embedding` | Run embedding |
| GET | `/datasets/<id>/tags` | List tags |
| GET | `/datasets/tags/aggregation` | Aggregate tags across datasets |
| DELETE | `/datasets/<id>/tags` | Delete tags |
| PUT | `/datasets/<id>/tags` | Rename tag |
| GET | `/datasets/metadata/flattened` | Get flattened metadata |
| GET/PUT | `/datasets/<id>/metadata/config` | New metadata config path
|
**Removed routes (replaced by unified `/index`):**
- `POST /datasets/<id>/mindmap`
- `GET /datasets/<id>/mindmap`
**Preserved legacy routes (backward compatibility):**
- `/run_graphrag`, `/trace_graphrag`, `/run_raptor`, `/trace_raptor`
- `/auto_metadata` GET/PUT
### Test Suite
- Updated `common.py` helpers: added `trace_index`, removed
`run_mindmap`/`trace_mindmap`
- Added 7 new test files with 39 test cases total:
| Test File | Cases |
|-----------|-------|
| `test_get_dataset.py` | 4 |
| `test_ingestion_summary.py` | 2 |
| `test_ingestion_logs.py` | 5 |
| `test_index_api.py` | 14 |
| `test_embedding.py` | 2 |
| `test_tags.py` | 8 |
| `test_flattened_metadata.py` | 4 |
- Deleted `test_mindmap_tasks.py` (covered by unified index tests)
## Design Decisions
1. **Unified `/index?type=...`** — single endpoint replaces 3 separate
route pairs for graph/raptor/mindmap
2. **Backward compatibility** — old routes (`/run_graphrag`,
`/run_raptor`, `/auto_metadata`) preserved alongside new paths
3. **`_VALID_INDEX_TYPES = {"graph", "raptor", "mindmap"}`** — input
validation via constant set
4. **`_INDEX_TYPE_TO_TASK_ID_FIELD`** — maps index type to KB model task
ID field for clean dispatch
## Files Changed
- `api/apps/restful_apis/dataset_api.py`
- `api/apps/services/dataset_api_service.py`
- `sdk/python/ragflow_sdk/modules/dataset.py`
- `test/testcases/test_http_api/common.py`
- `test/testcases/test_http_api/test_dataset_management/` (7 new files)
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
---------
Signed-off-by: noob <yixiao121314@outlook.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=${COMPOSE_PROFILES},tei-cpu
TEI_MODEL=BAAI/bge-small-en-v1.5
RAGFLOW_IMAGE=infiniflow/ragflow:v0.25.0 #Replace with the image you are using
Start the container（wait two minutes）:
docker compose -f docker/docker-compose.yml up -d
(3). Test Elasticsearch
a) Run sdk tests against Elasticsearch:
export HTTP_API_TEST_LEVEL=p2
export HOST_ADDRESS=http://127.0.0.1:9380 # Ensure that this port is the API port mapped to your localhost
pytest -s --tb=short --level=${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