Captain
a6011dcd95
`OllamaEmbeddings.compute_source_embeddings(np.array(["hello", "world"]))` raises a validation error before sending a request. The embedding interface accepts NumPy arrays, but the adapter passes the array directly to Ollama's string-or-sequence request field. Convert NumPy text arrays to lists before the batched request. This preserves input order, the single request, model options and `keep_alive`. The tests cover Unicode/object/sliced arrays, empty input, existing list/Arrow/query inputs and API error propagation. The added input-contract tests also cover two-dimensional arrays and byte strings, with equivalent list inputs as controls. The real Ollama SDK rejects 2-D inputs and invalid UTF-8 locally, before transport. Valid UTF-8 bytes are decoded normally. No extra adapter validation is needed for these cases. Validation on Python 3.12.14 / macOS arm64: - Built the Rust/PyO3 bindings using the repository's uv/maturin environment. - The initial regression run had 5 failures and 4 passing controls on the base; all 9 passed with the fix. With the 6 additional input-contract cases, the related embedding and trust suites now total 55 passed / 11 skipped. - All Python Ruff lint and formatting checks pass. Root checks still report the same 49 lint errors and 11 documentation formatting files reproduced on the untouched base. - Separate review exercised 13 public API cases. Another 7 groups passed through a real loopback HTTP transport, including local validation, UTF-8 serialization and empty-batch model-error propagation. The regression tests use the real Ollama 0.6.2 SDK with HTTPX MockTransport. The loopback check uses an HTTP surrogate, not an Ollama daemon. No live model inference was run. A live Ollama server was unavailable locally. [The current server handler](https://github.com/ollama/ollama/blob/2cd63f7a15039ccd790e97b31edc091fa1707c56/server/routes.go#L1212) explicitly returns HTTP 200 with empty embeddings for empty input after model lookup and runner setup. The adapter preserves the existing empty-list request and its model/setup errors. This is a source check, not a live-server test. Developed with OpenAI Codex, with separate agent review and executed local checks.
LanceDB Documentation
LanceDB docs are available at docs.lancedb.com.
The SDK docs are built and deployed automatically by Github Actions
whenever a commit is pushed to the main branch. So it is possible for the docs to show
unreleased features.
Building the docs
Setup
- Install LanceDB Python. See setup in Python contributing guide.
Run
make developto install the Python package. - Install documentation dependencies. From LanceDB repo root:
pip install -r docs/requirements.txt
Preview the docs
Run these commands from the LanceDB repository root. The subshell changes into
docs to load mkdocs.yml, while leaving your shell in the repository root.
(cd docs && PYTHONPATH=. mkdocs serve)
If you want to just generate the HTML files:
(cd docs && PYTHONPATH=. mkdocs build)
If successful, you should see a docs/site directory in the repository root that
you can verify locally.
Adding examples
To make sure examples are correct, we put examples in test files so they can be run as part of our test suites.
You can see the tests are at:
- Python:
python/python/tests/docs - Typescript:
nodejs/examples/
Checking python examples
cd python
pytest -vv python/tests/docs
Checking typescript examples
The examples depend on @lancedb/lancedb at file:../dist, so the package must be
built before running the tests. This uses pnpm; see the
Typescript contributing guide for the toolchain setup.
pushd nodejs
pnpm install
pnpm build
popd
Then you can run the examples by going to the nodejs/examples directory, which is a
separate pnpm package with its own lockfile:
pushd nodejs/examples
pnpm install
pnpm test
popd
API documentation
Python
The Python API documentation is organized based on the file docs/src/python/python.md.
We manually add entries there so we can control the organization of the reference page.
However, this means any new types must be manually added to the file. No additional
steps are needed to generate the API documentation.
Typescript
The typescript API documentation is generated from the typescript source code using typedoc.
When new APIs are added, you must manually re-run the typedoc command to update the API documentation. The new files should be checked into the repository.
pushd nodejs
# `pnpm docs` would invoke pnpm's built-in `docs` command, not the script.
pnpm run docs
popd