Closed curquiza closed 8 months ago
(?) Python for vector search v2
I verified that at a minimum the python tests will need updating for vector search.
test_vector_search
result:
meilisearch.errors.MeilisearchApiError: MeilisearchApiError. Error code: missing_search_hybrid. Error message: Invalid request: missing `hybrid` parameter when both `q` and `vector` are present.. Hint: It might not be working because you're not up to date with the Meilisearch version that search call requires. Error documentation: https://docs.meilisearch.com/errors#missing_search_hybrid Error type: invalid_request
Issues opened for proximityPrecision
✅
Are k8s and cloud providers released @brunoocasali?
Also missing this PR to be merged on the dart side. Having an issue with linter 😢
Discussed with @brunoocasali, k8s and cloud providers are done
Closing this issue then
is this error fixed now? I'm still getting this erro?
is this error fixed now? I'm still getting this erro?
Which SDK are you using? Which version of Meiliesarch? What is the error message?
is this error fixed now? I'm still getting this erro?
Which SDK are you using? Which version of Meiliesarch? What is the error message?
I've got the same error when I do vector search using python sdk 0.30.0 and the version of Meilisearch is 1.6.2:
meilisearch.errors.MeilisearchApiError: MeilisearchApiError. Error code: missing_search_hybrid. Error message: Invalid request: missing
hybridparameter when both
qand
vectorare present.. Hint: It might not be working because you're not up to date with the Meilisearch version that search call requires. Error documentation: https://docs.meilisearch.com/errors#missing_search_hybrid Error type: invalid_request
I've got the same error when I do vector search using python sdk 0.30.0 and the version of Meilisearch is 1.6.2
Did you include the hybrid
parameter with your search?
@sanders41 I'm following this tutorial and I'm get the same error and there is nothing about the error code in the docs.
https://blog.meilisearch.com/langchain-semantic-search-tutorial/
@sanders41 I'm following this tutorial and I'm get the same error and there is nothing about the error code in the docs.
There were breaking changes to vector search in 1.6. I have not used LangChain and don't know much about it, but looking at the example provided it doesn't look like LangChain is compatible with Meilisearch 1.6+ vector search.
@Strift I'm not sure if LangChain needs to be updated, if the tutorial needs updating to mention it works with Meilisearch >=1.3 <1.6, or if it is possible somehow to make it work with Meilisearch 1.6+?
I tried to add an embedder to my meilisearch instance but I got the error bellow. When we add an embedded to meili, it will generate vectors for all documents or only use to embedding queries?
"message": "The `_vectors` field in the document with id: `\"0c297f065a8c46cab12857ca5999c371\"` is not an object. Was expecting an object with a key for each embedder with manually provided vectors, but instead got `[-0......."
Hello @kauly,
If you want to use LangChain, please use a previous Meilisearch version, like v1.5.
Our current LangChain integration is intended for v1.3, v1.4, and v1.5. @CaroFG is currently updating our LangChain integration. After this, we'll update the tutorial too. 🙏
Thanks @sanders41 for the heads up.
This issue gathers the changes related to the v1.6.0 of Meilisearch that will impact the integrations scope.
📅 Release date: 15/01/2024
TODO
Before pre-release
#1
integrations. Integration to update:Pre-release
rc0
, define in which SDKs we have to update the testsRelease day
Features to implement
proximityPrecision
settingsIssue: https://github.com/meilisearch/meilisearch/issues/4187 Usage: https://www.notion.so/meilisearch/Customize-proximity-precision-usage-aa69c2bab2c3402bab9340ae4def4577
Should be implemented for
Vector search v2
Usage: https://www.notion.so/meilisearch/v1-6-Hybrid-Search-Embedders-ea42c82f90cc4bc0be1eeb917c1118c8
By Meili developers
By community if available
-> ⚠️ If not implemented by community, we will have to be clear (release notes + issues) the experimental vector search feature is broken in the SDK until someone implements it.