Files
ragflow/test
Muhammad Furqan 83540185e1 fix(agent/tools): port AkShare to ToolBase so it works as an Agent tool (#16417)
### What problem does this PR solve?

Closes #16416.

The **AkShare** agent tool (`agent/tools/akshare.py`) was never ported
to the modern `ToolBase`/`_invoke` interface during the agent module
redesign and was still written against the removed legacy
`_run`/`be_output` API, so it was non-functional:

1. **Adding it to an Agent raised `AttributeError`.** `AkShare` extended
`ComponentBase` (not `ToolBase`) and `AkShareParam` defined no `meta`,
so it had no `get_meta()`. `agent/component/agent_with_tools.py` builds
each tool's function descriptor via `cpn.get_meta()`, so constructing an
Agent that includes the AkShare tool raised `AttributeError: 'AkShare'
object has no attribute 'get_meta'`.
2. **It could never run.** `invoke()` dispatches to `self._invoke`, but
`AkShare` only implemented the legacy `_run`, so `_invoke` fell through
to `ComponentBase._invoke` → `NotImplementedError`. `_run` also called
`be_output(...)`, which no longer exists on the base classes.

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

### Changes

- Port `AkShareParam` to `ToolParamBase` with a `ToolMeta` (defined
before `super().__init__()`, matching `ArXivParam`/`TavilyExtractParam`)
exposing a required `query` parameter — the stock symbol to look up,
default `{sys.query}`. `query` matches the `{sys.query}` convention
shared by the other tools.
- Rewrite the component with `_invoke`/`set_output("formalized_content",
...)` (errors surfaced via `_ERROR`), keeping `top_n` and importing
`akshare` lazily.
- Add regression tests
(`test/unit_test/agent/component/test_akshare.py`) covering param
construction, validation, and the tool descriptor.

Same class of defect as #16329 (DeepL) and #16414 (Crawler).
Backend-only; no frontend changes.

---------

Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
2026-07-03 11:39:26 +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 3.13 --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:v0.26.3 #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