Store Vector Embeddings¤
Python Plugin
This operator is part of a Python Plugin Package. In order to use it, you need to install it, e.g. with cmemc.
This plugin workflow store embeddings into Postgres Vector Store.
The vector embeddings and its respective metadata are going to be stored into a collection inside the Postgres Vector Store. It is possible to specify either the name of the attributes containing the vectors as well as the metadata.
Parameter¤
Database Host¤
The hostname of the postgres database service.
- Datatype:
string - Default Value:
pgvector
Database Port¤
The port number of the postgres database service.
- Datatype:
Long - Default Value:
5432
Database User¤
The account name used to login to the postgres database service.
- Datatype:
string - Default Value:
pgvector
Database Password¤
The password of the database account.
- Datatype:
password - Default Value:
None
Database Name¤
The database name.
- Datatype:
string - Default Value:
pgvector
Collection Name¤
The name of the collection that will be used for search.
- Datatype:
string - Default Value:
None
Pre Delete Collection¤
If set to true, then the collection will removed at the beginning.
- Datatype:
boolean - Default Value:
true
Source Path¤
The name of the path to use for reading the embedding source.
- Datatype:
string - Default Value:
_embedding_source
Embedding Path¤
The name of the path to use for reading the embeddings.
- Datatype:
string - Default Value:
_embedding
Metadata Paths¤
The comma separated list path names to be used as metadata. Empty name means all paths (except embedding source and embedding) will be used
- Datatype:
string - Default Value:
None
Batch Processing Size¤
The number of entries to be processed in batch.
- Datatype:
Long - Default Value:
100