Improve vector store onboarding exp (#6698)

This PR
- fixes the `similarity_search_by_vector` example, makes the code run
and adds the example to mirror `similarity_search`
- reverts back to chroma from faiss to remove sharp edges / create a
happy path for new developers. (1) real metadata filtering, (2) expected
functionality like `update`, `delete`, etc to serve beyond the most
trivial use cases

@hwchase17

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
This commit is contained in:
Jeff Huber
2023-07-18 13:48:42 -07:00
committed by GitHub
parent 25a2bdfb70
commit dc8b790214
3 changed files with 114 additions and 6 deletions

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@@ -8,6 +8,8 @@ vectors, and then at query time to embed the unstructured query and retrieve the
'most similar' to the embedded query. A vector store takes care of storing embedded data and performing vector search
for you.
![vector store diagram](/img/vector_stores.jpg)
## Get started
This walkthrough showcases basic functionality related to VectorStores. A key part of working with vector stores is creating the vector to put in them, which is usually created via embeddings. Therefore, it is recommended that you familiarize yourself with the [text embedding model](/docs/modules/data_connection/text_embedding/) interfaces before diving into this.

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