docs(python): fix cross-references that resolved to the wrong page

`mkdocs build --strict` only catches references it cannot resolve. A bare
anchor such as `[limit][]` or `[vector search][search]` is matched by
autorefs against any heading on the site, so six of them silently linked
into the JavaScript reference instead. The relative links in
`permutation.py` and `remote/errors.py` pointed at in-page anchors and
paths that do not exist.

Targets that still exist here or in an imported inventory now use
mkdocstrings references; the guide pages deleted in #2770 use their
lancedb.com URLs.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

python/python/lancedb/permutation.py

@@ -438,7 +438,8 @@ class Permutation:
         _reader: Optional[PermutationReader] = None,
     ):
         """
-        Internal constructor.  Use [from_tables](#from_tables) instead.
+        Internal constructor.  Use
+        [from_tables][lancedb.permutation.Permutation.from_tables] instead.
         """
         assert base_table is not None, "base_table is required"
         assert selection is not None, "selection is required"
@@ -985,8 +986,9 @@ class Permutation:
         types.  Conversion of strings, lists, and structs will require creating python
         objects and this is not zero-copy.
 
-        For custom formatting, use [with_transform](#with_transform) which overrides
-        this method.
+        For custom formatting, use
+        [with_transform][lancedb.permutation.Permutation.with_transform] which
+        overrides this method.
         """
         assert format is not None, "format is required"
         if format == "python":
@@ -1061,7 +1063,8 @@ class Permutation:
         Note: this method returns a new permutation and does not modify `self`
         It is provided for compatibility with the huggingface Dataset API.
 
-        Use [with_skip](#with_skip) instead to avoid confusion.
+        Use [with_skip][lancedb.permutation.Permutation.with_skip] instead to
+        avoid confusion.
         """
         return self.with_skip(skip)
 
@@ -1084,7 +1087,8 @@ class Permutation:
         Note: this method returns a new permutation and does not modify `self`
         It is provided for compatibility with the huggingface Dataset API.
 
-        Use [with_take](#with_take) instead to avoid confusion.
+        Use [with_take][lancedb.permutation.Permutation.with_take] instead to
+        avoid confusion.
         """
         return self.with_take(limit)
 
@@ -1107,7 +1111,8 @@ class Permutation:
         Note: this method returns a new permutation and does not modify `self`
         It is provided for compatibility with the huggingface Dataset API.
 
-        Use [with_repeat](#with_repeat) instead to avoid confusion.
+        Use [with_repeat][lancedb.permutation.Permutation.with_repeat] instead
+        to avoid confusion.
         """
         return self.with_repeat(times)
 

python/python/lancedb/query.py

@@ -651,7 +651,8 @@ class Query(pydantic.BaseModel):
     distance_type : Optional[str]
         the distance type to use for vector search
 
-        This can be l2 (default), cosine and dot.  See [metric definitions][search] for
+        This can be l2 (default), cosine and dot.  See
+        [metric definitions](https://lancedb.com/docs/search/vector-search/) for
         more details.
 
         If this is not a vector search this will be None.
@@ -3381,8 +3382,9 @@ class AsyncQuery(AsyncStandardQuery):
         are various ANN search parameters that will let you fine tune your recall
         accuracy vs search latency.
 
-        Vector searches always have a [limit][].  If `limit` has not been called then
-        a default `limit` of 10 will be used.
+        Vector searches always have a
+        [limit][lancedb.query.AsyncVectorQuery.limit].  If `limit` has not been
+        called then a default `limit` of 10 will be used.
 
         Typically, a single vector is passed in as the query. However, you can also
         pass in multiple vectors. When multiple vectors are passed in, if the vector
@@ -3513,8 +3515,9 @@ class AsyncFTSQuery(AsyncStandardQuery):
         are various ANN search parameters that will let you fine tune your recall
         accuracy vs search latency.
 
-        Hybrid searches always have a [limit][].  If `limit` has not been called then
-        a default `limit` of 10 will be used.
+        Hybrid searches always have a
+        [limit][lancedb.query.AsyncHybridQuery.limit].  If `limit` has not been
+        called then a default `limit` of 10 will be used.
 
         Typically, a single vector is passed in as the query. However, you can also
         pass in multiple vectors.  This can be useful if you want to find the nearest

python/python/lancedb/remote/errors.py

@@ -53,9 +53,9 @@ class RetryError(LanceDBClientError):
     """An error that occurs when the client has exceeded the maximum number of retries.
 
     The retry strategy can be adjusted by setting the
-    [retry_config](lancedb.remote.ClientConfig.retry_config) in the client
+    [retry_config][lancedb.remote.ClientConfig.retry_config] in the client
     configuration. This is passed in the `client_config` argument of
-    [connect](lancedb.connect) and [connect_async](lancedb.connect_async).
+    [connect][lancedb.connect] and [connect_async][lancedb.connect_async].
 
     The __cause__ attribute of this exception will be the last exception that
     caused the retry to fail. It will be an

python/python/lancedb/remote/table.py

@@ -642,7 +642,8 @@ class RemoteTable(Table):
         fast_search: bool = False,
     ) -> LanceVectorQueryBuilder:
         """Create a search query to find the nearest neighbors
-        of the given query vector. We currently support [vector search][search]
+        of the given query vector. We currently support
+        [vector search](https://lancedb.com/docs/search/vector-search/)
 
         All query options are defined in
         [LanceVectorQueryBuilder][lancedb.query.LanceVectorQueryBuilder].

python/python/lancedb/table.py

@@ -3389,7 +3389,7 @@ class LanceTable(Table):
     ) -> LanceQueryBuilder:
         """Create a search query to find the nearest neighbors
         of the given query vector. We currently support [vector search](https://lancedb.com/docs/search/vector-search/)
-        and [full-text search][search].
+        and [full-text search](https://lancedb.com/docs/search/full-text-search/).
 
         Examples
         --------
@@ -3419,8 +3419,9 @@ class LanceTable(Table):
             - *default None*.
             Acceptable types are: list, np.ndarray, PIL.Image.Image
 
-            - If None then the select/[where][sql]/limit clauses are applied
-            to filter the table
+            - If None then the
+            select/[where][lancedb.query.LanceQueryBuilder.where]/limit clauses
+            are applied to filter the table
         vector_column_name: str, optional
             The name of the vector column to search.