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@cevian cevian commented Aug 19, 2024

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@jgpruitt jgpruitt self-requested a review August 19, 2024 21:23
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nit: the doc comments need updating. Missing the schema parameter.

| table_name | Name of the table to use for storing the embeddings. Think of this as the collection name |
| num_dimensions | Number of dimensions in the vector |

You can also specify the schema name, distance type, primary key type,

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Why not adding it to the table above with a column marking it as optional?

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I want to keep this part as simple as possible

"""
self.builder = QueryBuilder(
table_name, num_dimensions, distance_type, id_type, time_partition_interval, infer_filters)
table_name, num_dimensions, distance_type, id_type, time_partition_interval, infer_filters, schema_name)

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Need to add schema_name to the docs. Would it make it easier if instead of None we default to "public"? That way we don't have to do the if self.schema_name is not None checks.

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None and public are not the same since public is not always the default schema. None means use the default schema defined by the db

time_partition_interval: Optional[timedelta] = None,
max_db_connections: Optional[int] = None,
infer_filters: bool = True,
schema_name: Optional[str] = None,

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Need to add this to the constructor docs

@cevian cevian merged commit c6c74c4 into main Aug 22, 2024
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4 participants