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Achieve3318 16354f4e14 fix(dify): guard retrieval argument error behavior (#14169) 
## What problem does this PR solve?

The Dify-compatible `/dify/retrieval` endpoint recently gained stricter
parsing and validation for its request payload, including:
- Normalized `retrieval_setting.top_k` and
`retrieval_setting.score_threshold` types.
- Clear separation between malformed arguments vs missing required
fields.
Previously, there was no unit test explicitly guarding the exact error
code and message contract for these cases.

## What does this PR change?

- **Add guard-style unit test** in `test_dify_retrieval_routes_unit.py`:
  - `test_retrieval_argument_error_messages`:
    - Sends a request with malformed numeric options:
- `retrieval_setting = {"top_k": "not-int", "score_threshold":
"not-float"}`
      - Asserts `code == RetCode.ARGUMENT_ERROR` and message contains  
        `"invalid or malformed arguments:"`.
    - Sends a request with required fields missing:
      - Empty payload (`{}`)
      - Asserts `code == RetCode.ARGUMENT_ERROR` and message contains  
        `"required arguments are missing:"`.

This test encodes the intended behavior of the Dify retrieval API so
future refactors cannot silently regress error handling.

## Type of change

- [x] Tests (add coverage and guardrails for existing behavior)

Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
2026-05-11 13:17:42 +08:00
..
benchmark
Refa: restore openai-compatible chat completions api (#14380)
2026-04-27 14:02:19 +08:00
playwright
feat(api): add unified index API and dataset management endpoints (#14222)
2026-04-27 09:38:01 +08:00
testcases
fix(dify): guard retrieval argument error behavior (#14169)
2026-05-11 13:17:42 +08:00
unit_test
fix(prompt): reserve system budget in message_fit_in (#14164)
2026-05-11 12:44:27 +08:00
__init__.py
Feat: UI testing automation with playwright (#12749)
2026-03-02 13:04:08 +08:00
README.md
Docs: Update version references to v0.25.2 in READMEs and docs (#14731)
2026-05-09 19:06:05 +08:00

README.md

(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:v0.25.2 #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