Commit Graph

5 Commits

Author SHA1 Message Date
Akhil Vempali
d7d629911b
feat: Added filtering option to FAISS vectorstore (#5966)
Inspired by the filtering capability available in ChromaDB, added the
same functionality to the FAISS vectorestore as well. Since FAISS does
not have an inbuilt method of filtering used the approach suggested in
this [thread](https://github.com/facebookresearch/faiss/issues/1079)
Langchain Issue inspiration:
https://github.com/hwchase17/langchain/issues/4572

- [x] Added filtering capability to semantic similarly and MMR
- [x] Added test cases for filtering in
`tests/integration_tests/vectorstores/test_faiss.py`

#### Who can review?

Tag maintainers/contributors who might be interested:

  VectorStores / Retrievers / Memory
  - @dev2049
  - @hwchase17
2023-06-11 13:20:03 -07:00
berkedilekoglu
f907b62526
Scores are explained in vectorestore docs (#5613)
# Scores in Vectorestores' Docs Are Explained

Following vectorestores can return scores with similar documents by
using `similarity_search_with_score`:
- chroma
- docarray_hnsw
- docarray_in_memory
- faiss
- myscale
- qdrant
- supabase
- vectara
- weaviate

However, in documents, these scores were either not explained at all or
explained in a way that could lead to misunderstandings (e.g., FAISS).
For instance in FAISS document: if we consider the score returned by the
function as a similarity score, we understand that a document returning
a higher score is more similar to the source document. However, since
the scores returned by the function are distance scores, we should
understand that smaller scores correspond to more similar documents.

For the libraries other than Vectara, I wrote the scores they use by
investigating from the source libraries. Since I couldn't be certain
about the score metric used by Vectara, I didn't make any changes in its
documentation. The links mentioned in Vectara's documentation became
broken due to updates, so I replaced them with working ones.

VectorStores / Retrievers / Memory
  - @dev2049

my twitter: [berkedilekoglu](https://twitter.com/berkedilekoglu)

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
2023-06-05 20:39:49 -07:00
Davis Chase
df0c33a005
Faiss no avx2 (#4895)
Co-authored-by: Ali Mirlou <alimirlou@gmail.com>
2023-05-17 19:18:57 -07:00
leo-gan
e510732ad2
docs: improved vectorstore notebooks (#3724)
- Added links to the vectorstore providers
- Added installation code (it is not clear that we have to go to the
`LangChan Ecosystem` page to get installation instructions.)
2023-04-28 19:26:50 -07:00
Harrison Chase
705431aecc
big docs refactor (#1978)
Co-authored-by: Ankush Gola <ankush.gola@gmail.com>
2023-03-26 19:49:46 -07:00