I stumbled upon a bug that led to different similarity scores between
the async and sync similarity searches with relevance scores in Qdrant.
The reason being is that _asimilarity_search_with_relevance_scores is
missing, this makes langchain_qdrant use the method of the vectorstore
baseclass leading to drastically different results.
To illustrate the magnitude here are the results running an identical
search in a test vectorstore.
Output of asimilarity_search_with_relevance_scores:
[0.9902903374601824, 0.9472135924938804, 0.8535534011299859]
Output of similarity_search_with_relevance_scores:
[0.9805806749203648, 0.8944271849877607, 0.7071068022599718]
Co-authored-by: Erick Friis <erick@langchain.dev>
## Description
This PR introduces a new sparse embedding provider interface to work
with the new Qdrant implementation that will follow this PR.
Additionally, an implementation of this interface is provided with
https://github.com/qdrant/fastembed.
This PR will be followed by
https://github.com/Anush008/langchain/pull/3.
## Description
The `path` param is used to specify the local persistence directory,
which isn't required if using Qdrant server.
This is a breaking but necessary change.
- [ ] **Packages affected**:
- community: fix `cosine_similarity` to support simsimd beyond 3.7.7
- partners/milvus: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/mongodb: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/pinecone: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/qdrant: fix `cosine_similarity` to support simsimd beyond
3.7.7
- [ ] **Broadcast operation failure while using simsimd beyond v3.7.7**:
- **Description:** I was using simsimd 4.3.1 and the unsupported operand
type issue popped up. When I checked out the repo and ran the tests,
they failed as well (have attached a screenshot for that). Looks like it
is a variant of https://github.com/langchain-ai/langchain/issues/18022 .
Prior to 3.7.7, simd.cdist returned an ndarray but now it returns
simsimd.DistancesTensor which is ineligible for a broadcast operation
with numpy. With this change, it also remove the need to explicitly cast
`Z` to numpy array
- **Issue:** #19905
- **Dependencies:** No
- **Twitter handle:** https://x.com/GetzJoydeep
<img width="1622" alt="Screenshot 2024-05-29 at 2 50 00 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/fb27b383-a9ae-4a6f-b355-6d503b72db56">
- [ ] **Considerations**:
1. I started with community but since similar changes were there in
Milvus, MongoDB, Pinecone, and QDrant so I modified their files as well.
If touching multiple packages in one PR is not the norm, then I can
remove them from this PR and raise separate ones
2. I have run and verified that the tests work. Since, only MongoDB had
tests, I ran theirs and verified it works as well. Screenshots attached
:
<img width="1573" alt="Screenshot 2024-05-29 at 2 52 13 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/ce87d1ea-19b6-4900-9384-61fbc1a30de9">
<img width="1614" alt="Screenshot 2024-05-29 at 3 33 51 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/6ce1d679-db4c-4291-8453-01028ab2dca5">
I have added a test for simsimd. I feel it may not go well with the
CI/CD setup as installing simsimd is not a dependency requirement. I
have just imported simsimd to ensure simsimd cosine similarity is
invoked. However, its not a good approach. Suggestions are welcome and I
can make the required changes on the PR. Please provide guidance on the
same as I am new to the community.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
## Description
This PR introduces the new `langchain-qdrant` partner package, intending
to deprecate the community package.
## Changes
- Moved the Qdrant vector store implementation `/libs/partners/qdrant`
with integration tests.
- The conditional imports of the client library are now regular with
minor implementation improvements.
- Added a deprecation warning to
`langchain_community.vectorstores.qdrant.Qdrant`.
- Replaced references/imports from `langchain_community` with either
`langchain_core` or by moving the definitions to the `langchain_qdrant`
package itself.
- Updated the Qdrant vector store documentation to reflect the changes.
## Testing
- `QDRANT_URL` and
[`QDRANT_API_KEY`](583e36bf6b)
env values need to be set to [run integration
tests](d608c93d1f)
in the [cloud](https://cloud.qdrant.tech).
- If a Qdrant instance is running at `http://localhost:6333`, the
integration tests will use it too.
- By default, tests use an
[`in-memory`](https://github.com/qdrant/qdrant-client?tab=readme-ov-file#local-mode)
instance(Not comprehensive).
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Erick Friis <erickfriis@gmail.com>
