VectorStores — langchain Architecture
Abstraction layer for semantic search and high-dimensional data persistence.
Entity Profile
Dependency Diagram
graph TD subdomain_DataProcessing_VectorStores["VectorStores"] b00583bb_9045_d00b_62c9_7e70b6aaf04e["in_memory.py"] subdomain_DataProcessing_VectorStores --> b00583bb_9045_d00b_62c9_7e70b6aaf04e e919d308_8778_6617_0854_6d78babc4ba7["base.py"] subdomain_DataProcessing_VectorStores --> e919d308_8778_6617_0854_6d78babc4ba7 style subdomain_DataProcessing_VectorStores fill:#6366f1,stroke:#818cf8,color:#fff
Relationship Graph
Domain
Functions
- _HAS_NUMPY()
- _HAS_SIMSIMD()
- __getattr__()
- __init__()
- __init__()
- _asimilarity_search_with_relevance_scores()
- _batch()
- _calculate_hash()
- _cosine_relevance_score_fn()
- _cosine_similarity()
- _delete()
- _get_ls_params()
- _get_retriever_tags()
- _get_source_id_assigner()
- _hash_string()
- _select_relevance_score_fn()
- _similarity_search_with_relevance_scores()
- _similarity_search_with_score_by_vector()
- _to_async_iterator()
- acreate_schema()
- adelete()
- adelete_keys()
- aexists()
- afrom_texts()
- aget_time()
- aindex()
- alist_keys()
- amax_marginal_relevance_search()
- amax_marginal_relevance_search()
- amax_marginal_relevance_search_by_vector()
- asearch()
- asimilarity_search()
- asimilarity_search()
- asimilarity_search_by_vector()
- asimilarity_search_by_vector()
- asimilarity_search_with_relevance_scores()
- asimilarity_search_with_score()
- asimilarity_search_with_score()
- aupdate()
- collections()
- create_schema()
- delete()
- delete()
- delete_keys()
- dump()
- embeddings()
- exists()
- get()
- get()
- get_by_ids()
- get_by_ids()
- get_time()
- list_keys()
- max_marginal_relevance_search()
- max_marginal_relevance_search()
- max_marginal_relevance_search_by_vector()
- max_marginal_relevance_search_by_vector()
- numpy()
- search()
- similarity_search()
- similarity_search()
- similarity_search_by_vector()
- similarity_search_by_vector()
- similarity_search_with_relevance_scores()
- similarity_search_with_score()
- similarity_search_with_score()
- similarity_search_with_score_by_vector()
- update()
- upsert()
- upsert()
- validate_search_type()
Source Files
Frequently Asked Questions
What is the VectorStores subdomain?
VectorStores is a subdomain in the langchain codebase, part of the DataProcessing domain. Abstraction layer for semantic search and high-dimensional data persistence. It contains 2 source files.
Which domain does VectorStores belong to?
VectorStores belongs to the DataProcessing domain.
What functions are in VectorStores?
The VectorStores subdomain contains 71 function(s): _HAS_NUMPY, _HAS_SIMSIMD, __getattr__, __init__, __init__, _asimilarity_search_with_relevance_scores, _batch, _calculate_hash, and 63 more.
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