Handle NaN input data (#241)

Sometimes LangChain would insert a single `[np.nan]` as a placeholder if
the embedding function failed. This causes a problem for Lance format
because then the array can't be stored as a FixedSizedListArray.

Instead:
1. By default we remove rows with embedding lengths less than the
maximum length in the batch
2. If `strict=True` kwargs is set to True, then a `ValueError` is raised
if the embeddings aren't all the same length

---------

Co-authored-by: Chang She <chang@lancedb.com>

python/tests/test_remote_client.py

@@ -30,7 +30,7 @@ class MockLanceDBServer:
         table_name = request.match_info["table_name"]
         assert table_name == "test_table"
 
-        request_json = await request.json()
+        await request.json()
         # TODO: do some matching
 
         vecs = pd.Series([np.random.rand(128) for x in range(10)], name="vector")