[v1.3] [EXPERIMENTAL] Vector Store
brunoocasali opened this issue · comments
Also, if you are a maintainer, feel free to add any clarification and instruction about this issue.
Sorry if this is already partially/completely implemented, feel free to let me know about the state of this issue in the repo.
Related to meilisearch/integration-guides#280
New implementation
To ensure we still deliver stability to our users and have ways to innovate. Meilisearch has a way to opt-in for experimental features. The user must query a particular route and enable/disable those features.
The SDKs receiving the experimental features will likely change soon (a.k.a: breaking changes), which will not trigger a major version update.
So, before adopting a experimental feature, be sure what you're doing.
Related to:
It allows the user to store dense vectors to be retrieved later during search time.
What needs to be changed:
- Ensure sending the
vector
key during the search works:client.index('myindex').search('query', { vector: [0.1, ...] })
- Ensure it is possible to send during the data ingestion the
_vectors
special field in the documents:client.index('myindex').add_documents({ _vectors: [0.1, ...] })
- The response can contain a
vector
key similar to theq
key.
PATCH /experimental-features
with { "vectorStore": true }
Extra: Add inline documentation for the method, explaining the availability of this feature only for Meilisearch v1.3 and newer. And that is also an experimental feature that needs to be opt-in manually using the /experimental-features
meilisearch/meilisearch#3857 endpoint.
TODO:
- Add the ability receive a new param in the search request called
vector
. - Add the ability handle a
vector
key in the response. - Add integration tests (don't forget to enable the experimental feature)
I close this issue since it's an experimental which is already outdated
If someone wants to implement AI search in this repo, please refer to the v1.6.0 changelogs