Mohammad Hijjawi
5f9a8af27c
`EmbeddingFunctionRegistry.register()` documents that the class name is
used when no alias is given, and it does register the class under that
name. But it stored the alias itself (`None`) as
`__embedding_function_registry_alias__`, which is what
`function_to_metadata()` writes into the table schema. A table using
such a function gets `"name": null` in its `embedding_functions`
metadata, and any later read of the functions fails:
```python
@get_registry().register()
class MyEmbed(TextEmbeddingFunction): ...
f = MyEmbed.create()
class Schema(LanceModel):
text: str = f.SourceField()
vector: Vector(4) = f.VectorField()
tbl = db.create_table("t", schema=Schema)
tbl.add([{"text": "hi"}]) # KeyError: None
tbl.search("hi") # KeyError: None
```
This stores the key the class is registered under instead, so the class
name round-trips. For aliased classes the key is the alias, so their
metadata is unchanged. The TypeScript registry already falls back to
`ctor.name` in the same way.
Added `test_embedding_function_registered_without_alias`, which creates
a table with such a function, reopens it, and adds a row. It fails with
`KeyError` before the change. `test_embeddings.py`, `test_pydantic.py`,
`test_table.py` and `test_db.py` pass, and `ruff format --check` / `ruff
check` are clean.
The Multimodal Lakehouse for AI
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The ultimate multimodal data platform for AI/ML applications.
LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. LanceDB is a central location where developers can build, train and analyze their AI workloads.
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|---|---|
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| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
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