Fede Kamelhar
8be1f8e00f
Adds `OCIGenAIEmbeddings`, registered as `"oci-genai"`, embedding text with the Cohere models hosted on Oracle Cloud Infrastructure Generative AI (default `cohere.embed-v4.0`) via the `oci` SDK, alongside the existing Bedrock, Gemini and watsonx functions. - Auth delegated to the OCI SDK: `API_KEY` / `SECURITY_TOKEN` profiles from the OCI config file, or `INSTANCE_PRINCIPAL` / `RESOURCE_PRINCIPAL`. No credentials are stored on the function or in table metadata; `compartment_id` can come from `OCI_COMPARTMENT_ID` so the OCID need not be baked into metadata either. - Endpoint derived from `region` (default `us-chicago-1`) or overridden with `service_endpoint`; dedicated AI cluster endpoint OCIDs use `DedicatedServingMode`. - Asymmetric Cohere input types (`SEARCH_DOCUMENT` for the source column, `SEARCH_QUERY` for queries); `truncate` and `output_dimensions` (embed-v4.0: 256/512/1024/1536) forwarded. - Batched at the service limit of 96 inputs; empty inputs are not sent and come back as `None`. - `ndims()` uses `output_dimensions` when set, otherwise a single cached probe request, so there is no model→dims table to keep in sync with the catalog. - SDK retries disabled in favour of LanceDB's `max_retries` backoff; 401/403 service errors carry `status_code` so they surface without retrying, with an actionable message (expired session token, IAM policy, region, model). - `oci>=2.165.1` added to the `embeddings` extra (the floor where `EmbedTextDetails.output_dimensions` exists). Tests: 22 mocked unit tests (auth paths, batching, input types, config validation, retry behaviour, pickling, table-metadata round trip) and a live test skipped unless `OCI_COMPARTMENT_ID` is set, which passes against us-chicago-1 for embed-v4.0 at 1536 and 512 dims and embed-multilingual-v3.0 at 1024. Verified end to end with a real LanceDB table (`LanceModel` with `SourceField`/`VectorField`, 6 rows, two semantic queries ranked correctly). `ruff format --check`, `ruff check`, pyright and typos are clean. Docs: a page under `docs/src/embeddings/available_embedding_models/text_embedding_functions/` in the shape of the remaining `voyageai_embedding.md`; the function is exported from `lancedb.embeddings` so the API reference picks it up. The hosted docs' available-models table lives outside this repo and would need a separate update.
LanceDB Documentation
For website guides in docs/web, start with
Documentation in CONTRIBUTING.md. That
covers editing pages, generated examples, previews, availability and drafts.
This page covers the SDK reference in docs/src, built with MkDocs. Its
GitHub Actions workflow builds and deploys on
pushes to main, so it can include unreleased APIs. That is separate from the
release editions of the Mintlify website.
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