You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Since AI-powered search was initially introduced Meilisearch v1.3 as an experimental feature an subsequently refined in later releases, some features may already be partially implemented. The goal of this issue is to update the SDK to align with the stabilized API in v1.13.0.
embedders setting. Methods getEmbedders, updateEmbedders, resetEmbedders. Also, the method updateSettings should be able to accept the new embedders field. Here is the list of the acceptable sub fields:
source sub field is available and accepts: ollama, rest, openAI, huggingFace and userProvided
apiKey sub field is available (string) - optional because not compatible with all sources. Only for openAi, ollama, rest.
model sub field is available (string) - optional because not compatible with all sources. Only for ollama, openAI, huggingFace
documentTemplate sub field is available (string) - optional
dimensions - optional because not compatible with all sources. Only for openAi, huggingFace, ollama, and rest
distribution - optional
request - mandatory only if using rest embedder
response - mandatory only if using rest embedder
documentTemplateMaxBytes - optional
revision - optional, only for huggingFace
headers - optional, only for rest
binaryQuantized - optional
Update search to handle vector search and hybrid search
Following the changes related to Meilisearch v1.13.0 mega issue:
Description
Integrate AI-powered search features as stabilized in Meilisearch v1.13.0.
Since AI-powered search was initially introduced Meilisearch v1.3 as an experimental feature an subsequently refined in later releases, some features may already be partially implemented. The goal of this issue is to update the SDK to align with the stabilized API in v1.13.0.
Specifications
Update settings to handle embedders
Docs: https://www.meilisearch.com/docs/reference/api/settings#embedders
embedders
setting. MethodsgetEmbedders
,updateEmbedders
,resetEmbedders
. Also, the methodupdateSettings
should be able to accept the newembedders
field. Here is the list of the acceptable sub fields:source
sub field is available and accepts:ollama
,rest
,openAI
,huggingFace
anduserProvided
apiKey
sub field is available (string) - optional because not compatible with all sources. Only foropenAi
,ollama
,rest
.model
sub field is available (string) - optional because not compatible with all sources. Only forollama
,openAI
,huggingFace
documentTemplate
sub field is available (string) - optionaldimensions
- optional because not compatible with all sources. Only foropenAi
,huggingFace
,ollama
, andrest
distribution
- optionalrequest
- mandatory only if usingrest
embedderresponse
- mandatory only if usingrest
embedderdocumentTemplateMaxBytes
- optionalrevision
- optional, only forhuggingFace
headers
- optional, only forrest
binaryQuantized
- optionalUpdate search to handle vector search and hybrid search
Docs: https://www.meilisearch.com/docs/reference/api/search
hybrid
search parameter, with sub fieldssemanticRatio
andembedder
.embedder
is mandatory ifhybrid
is set.vector
parameter is availableretrieveVectors
parameter availablesemanticHitCount
in search response_semanticScore
in the search response (optional)vector
should be returned in the search response, but optional (because depends on search parameters)_vectors
should NOT be present in the search responseAdd similar documents endpoint
Docs: https://www.meilisearch.com/docs/reference/api/similar
searchSimilarDocuments
associated with thePOST /indexes/:uid/similar
. Do NOT implement withGET
.The text was updated successfully, but these errors were encountered: