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docs(python): add missing public APIs to the Python reference
The Python API reference page had drifted from the public API. Branch management (`Branches` / `AsyncBranches`, which own `diff` and `merge`), structured full-text query classes, take queries, blob helpers, namespace connections, most rerankers and embedding functions, the PyTorch dataloader, and several other public symbols were never listed, so they did not appear in the rendered docs. Also fixes docstring cross-references that pointed at guide pages which have since moved off this site, and at unresolvable relative targets (`[Table](Table)`, `[PyArrow Table](pyarrow.Table)`). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
This commit is contained in:
Will Jones
@@ -359,7 +359,7 @@ class DBConnection(EnforceOverrides):
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Data is converted to Arrow before being written to disk. For maximum
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control over how data is saved, either provide the PyArrow schema to
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convert to or else provide a [PyArrow Table](pyarrow.Table) directly.
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convert to or else provide a [PyArrow Table][pyarrow.Table] directly.
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>>> import pyarrow as pa
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>>> custom_schema = pa.schema([
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@@ -1529,7 +1529,7 @@ class AsyncConnection(object):
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Data is converted to Arrow before being written to disk. For maximum
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control over how data is saved, either provide the PyArrow schema to
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convert to or else provide a [PyArrow Table](pyarrow.Table) directly.
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convert to or else provide a [PyArrow Table][pyarrow.Table] directly.
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>>> import pyarrow as pa
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>>> custom_schema = pa.schema([
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@@ -664,8 +664,9 @@ class Query(pydantic.BaseModel):
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- A higher number makes search more accurate but also slower.
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- See discussion in [Querying an ANN Index][querying-an-ann-index] for
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tuning advice.
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- See discussion in
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[Querying an ANN Index](https://lancedb.com/docs/indexing/)
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for tuning advice.
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Will be None if this is not a vector search.
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refine_factor : Optional[int]
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@@ -673,8 +674,9 @@ class Query(pydantic.BaseModel):
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- A higher number makes search more accurate but also slower.
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- See discussion in [Querying an ANN Index][querying-an-ann-index] for
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tuning advice.
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- See discussion in
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[Querying an ANN Index](https://lancedb.com/docs/indexing/)
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for tuning advice.
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Will be None if this is not a vector search.
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lower_bound : Optional[float]
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@@ -1651,8 +1653,8 @@ class LanceVectorQueryBuilder(LanceQueryBuilder):
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Higher values will yield better recall (more likely to find vectors if
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they exist) at the expense of latency.
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See discussion in [Querying an ANN Index][querying-an-ann-index] for
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tuning advice.
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See discussion in [Querying an ANN Index](https://lancedb.com/docs/indexing/)
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for tuning advice.
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This method sets both the minimum and maximum number of probes to the same
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value. See `minimum_nprobes` and `maximum_nprobes` for more fine-grained
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@@ -1752,8 +1754,8 @@ class LanceVectorQueryBuilder(LanceQueryBuilder):
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As an example, a refine factor of 2 will sample 2x as many vectors as
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requested, re-ranks them, and returns the top half most relevant results.
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See discussion in [Querying an ANN Index][querying-an-ann-index] for
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tuning advice.
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See discussion in [Querying an ANN Index](https://lancedb.com/docs/indexing/)
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for tuning advice.
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Parameters
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----------
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@@ -580,8 +580,9 @@ class RemoteTable(Table):
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progress: Optional[Union[bool, Callable, Any]] = None,
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write_parallelism: Optional[int] = None,
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) -> AddResult:
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"""Add more data to the [Table](Table). It has the same API signature as
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the OSS version.
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"""Add more data to the [Table][lancedb.table.Table].
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It has the same API signature as the OSS version.
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Parameters
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----------
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@@ -1211,7 +1211,7 @@ class Table(ABC):
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progress: Optional[Union[bool, Callable, Any]] = None,
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write_parallelism: Optional[int] = None,
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) -> AddResult:
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"""Add more data to the [Table](Table).
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"""Add more data to the [Table][lancedb.table.Table].
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Parameters
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----------
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@@ -1343,8 +1343,8 @@ class Table(ABC):
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fts_columns: Optional[Union[str, List[str]]] = None,
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) -> LanceQueryBuilder:
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"""Create a search query to find the nearest neighbors
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of the given query vector. We currently support [vector search][search]
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and [full-text search][experimental-full-text-search].
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of the given query vector. We currently support [vector search](https://lancedb.com/docs/search/vector-search/)
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and [full-text search](https://lancedb.com/docs/search/full-text-search/).
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All query options are defined in
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[LanceQueryBuilder][lancedb.query.LanceQueryBuilder].
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@@ -1778,7 +1778,7 @@ class Table(ABC):
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for faster reads.
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Arguments are passed onto Lance's
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[compact_files][lance.dataset.DatasetOptimizer.compact_files].
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`lance.dataset.DatasetOptimizer.compact_files`.
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For most cases, the default should be fine.
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See Also
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@@ -3387,7 +3387,7 @@ class LanceTable(Table):
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fts_columns: Optional[Union[str, List[str]]] = None,
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) -> LanceQueryBuilder:
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"""Create a search query to find the nearest neighbors
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of the given query vector. We currently support [vector search][search]
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of the given query vector. We currently support [vector search](https://lancedb.com/docs/search/vector-search/)
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and [full-text search][search].
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Examples
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@@ -4691,7 +4691,7 @@ class AsyncTable:
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Parameters
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----------
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**kwargs
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Forwarded to [`lance.dataset`][lance.dataset].
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Forwarded to `lance.dataset`.
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Returns
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-------
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@@ -5010,7 +5010,7 @@ class AsyncTable:
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progress: Optional[Union[bool, Callable, Any]] = None,
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write_parallelism: Optional[int] = None,
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) -> AddResult:
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"""Add more data to the [Table](Table).
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"""Add more data to the [AsyncTable][lancedb.table.AsyncTable].
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Parameters
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----------
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@@ -5212,8 +5212,8 @@ class AsyncTable:
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fts_columns: Optional[Union[str, List[str]]] = None,
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) -> Union[AsyncHybridQuery, AsyncFTSQuery, AsyncVectorQuery]:
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"""Create a search query to find the nearest neighbors
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of the given query vector. We currently support [vector search][search]
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and [full-text search][experimental-full-text-search].
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of the given query vector. We currently support [vector search](https://lancedb.com/docs/search/vector-search/)
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and [full-text search](https://lancedb.com/docs/search/full-text-search/).
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All query options are defined in [AsyncQuery][lancedb.query.AsyncQuery].
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