XataVectorStore(
self,
api_key: str,
db_url: str,
embedding: Embeddings,
table_name: | Name | Type |
|---|---|
| api_key | str |
| db_url | str |
| embedding | Embeddings |
| table_name | str |
Xata vector store.
It assumes you have a Xata database created with the right schema. See the guide at: https://integrations.langchain.com/vectorstores?integration_name=XataVectorStore
Return VectorStore initialized from texts and embeddings.
Return docs most similar to query.
Run similarity search with Chroma with distance.
Delete by vector IDs.
Wait for the search index to contain a certain number of documents. Useful in tests.