Jack Ye
6b6778e684
Infer Blob V2 input access from the Python Function signature. `video:
BlobReader` requests a lazy, seekable reader; `video: bytes` requests
the complete payload. Users do not need a separate `blob_inputs`
registration option.
## Python experience
For a video table joined to a table of frame timestamps, the Function
can pass its reader directly to a media decoder:
```python
import io
import av
from lancedb import BlobReader, udf
@udf(pip=["av", "Pillow"])
def extract_frame(video: BlobReader, timestamp_s: float) -> bytes:
with av.open(video) as container:
stream = container.streams.video[0]
container.seek(int(timestamp_s / stream.time_base), stream=stream)
for frame in container.decode(stream):
if frame.time is not None and frame.time >= timestamp_s:
output = io.BytesIO()
frame.to_image().save(output, format="JPEG")
return output.getvalue()
raise ValueError("No frame at or after the requested timestamp")
```
After registering `extract_frame`, the query keeps the usual Function
call:
```sql
SELECT f.video_id, f.timestamp_s,
extract_frame(v.video, f.timestamp_s) AS image
FROM videos AS v
JOIN frames AS f ON v.id = f.video_id
```
The returned JPEG can feed a subsequent image-model step. The reader
provides `read`, `readinto`, `seek`, `tell`, `size()`, and
`read_range(offset, length)`; range reads leave the sequential cursor
unchanged. Each row invocation owns its reader, which closes after the
call. Decoder seeks can request the parts of the MP4 needed to locate
and decode the requested frame; the amount read depends on the file
layout and codec.
Functions that need the whole value can keep a bytes signature:
```python
@udf
def video_length(video: bytes) -> int:
return len(video)
```
## Execution contract
- Signature inference maps `BlobReader` to a Blob V2 field and records
`blob_access="reader"`. `bytes` keeps its binary Arrow type and records
`blob_access="bytes"`; it can also bind to a Blob V2 source. Explicit
schemas support the same choice, including a Blob V2 field annotated as
`bytes`.
- Reader execution carries a compact blob reference into the Function
worker. Payload reads happen when Python calls the reader, with requests
split into at most 1 MiB ranges. The full video does not need to enter
the Arrow input batch just to invoke the Function.
- Bytes execution materializes the full source before the Function runs
and remains subject to eager-input memory admission. Calling
`reader.read()` without a size also materializes the remaining contents
in Python; lazy access depends on how the Function consumes it.
- Input access metadata survives Python/Rust Function serialization and
registration. Packaged Functions import the worker-provided reader
implementation. This PR defines the SDK contract; execution requires
corresponding server support.
- This changes blob inputs. The example still returns ordinary image
bytes; it does not add streamed outputs or run an image model.
Adds coverage for signature inference, explicit schemas, nullable
readers, signature round trips, seeking, bounded range reads, buffering,
and invalid responses.
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