destinations.impl.lancedb.configuration
LanceDBCredentials Objects
@configspec
class LanceDBCredentials(CredentialsConfiguration)
uri
LanceDB database URI. Defaults to local, on-disk instance.
The available schemas are:
/path/to/database
- local database.db://host:port
- remote database (LanceDB cloud).
api_key
API key for the remote connections (LanceDB cloud).
embedding_model_provider_api_key
API key for the embedding model provider.
LanceDBClientOptions Objects
@configspec
class LanceDBClientOptions(BaseConfiguration)
max_retries
EmbeddingFunction
class wraps the calls for source and query embedding
generation inside a rate limit handler that retries the requests with exponential
backoff after successive failures.
You can tune it by setting it to a different number, or disable it by setting it to 0.
LanceDBClientConfiguration Objects
@configspec
class LanceDBClientConfiguration(DestinationClientDwhConfiguration)
dataset_separator
Character for the dataset separator.
options
LanceDB client options.
embedding_model_provider
Embedding provider used for generating embeddings. Default is "cohere". You can find the full list of providers at https://github.com/lancedb/lancedb/tree/main/python/python/lancedb/embeddings as well as https://lancedb.github.io/lancedb/embeddings/default_embedding_functions/.
embedding_model
The model used by the embedding provider for generating embeddings. Check with the embedding provider which options are available. Reference https://lancedb.github.io/lancedb/embeddings/default_embedding_functions/.
embedding_model_dimensions
The dimensions of the embeddings generated. In most cases it will be automatically inferred, by LanceDB, but it is configurable in rare cases.
Make sure it corresponds with the associated embedding model's dimensionality.
vector_field_name
Name of the special field to store the vector embeddings.
id_field_name
Name of the special field to manage deduplication.
sentinel_table_name
Name of the sentinel table that encapsulates datasets. Since LanceDB has no concept of schemas, this table serves as a proxy to group related dlt tables together.
fingerprint
def fingerprint() -> str
Returns a fingerprint of a connection string.