5 Commits (ba7a5ac9d7bbc1ad531916c8a0002d1791aa1335)

Author	SHA1	Message	Date
Ankush Gola	c1521ddbdb	Add workaround for not having async vector store methods (#2733) ... This allows us to use the async API for the Retrieval chains, though it is not guaranteed to be thread safe.	1 year ago
Eli	12f868b292	Propagate "filter" arg in Chroma similarity_search (#1869) ... Technically a duplicate fix to #1619 but with unit tests and a small documentation update - Propagate `filter` arg in Chroma `similarity_search` to delegated call to `similarity_search_with_score` - Add `filter` arg to `similarity_search_by_vector` - Clarify doc strings on FakeEmbeddings	1 year ago
Harrison Chase	a1b9dfc099	Harrison/similarity search chroma (#1434) ... Co-authored-by: shibuiwilliam <shibuiyusuke@gmail.com>	2 years ago
Anton Troynikov	d43d430d86	Chroma persistence (#1028) ... This PR adds persistence to the Chroma vector store. Users can supply a `persist_directory` with any of the `Chroma` creation methods. If supplied, the store will be automatically persisted at that directory. If a user creates a new `Chroma` instance with the same persistence directory, it will get loaded up automatically. If they use `from_texts` or `from_documents` in this way, the documents will be loaded into the existing store. There is the chance of some funky behavior if the user passes a different embedding function from the one used to create the collection - we will make this easier in future updates. For now, we log a warning.	2 years ago
Anton Troynikov	78abd277ff	Chroma in LangChain (#1010) ... Chroma is a simple to use, open-source, zero-config, zero setup vectorstore. Simply `pip install chromadb`, and you're good to go. Out-of-the-box Chroma is suitable for most LangChain workloads, but is highly flexible. I tested to 1M embs on my M1 mac, with out issues and reasonably fast query times. Look out for future releases as we integrate more Chroma features with LangChain!	2 years ago