Mistral: Embeddings search

Deprecated

This function is deprecated and can no longer be added to new workflows. Existing workflows using it keep running. Use the generic Embeddings Search function instead.

Generate embeddings using Mistral embeddings API on mistral-embed model.

Pre-requisite: Install Mistral AI application Profile > {Organization} > Applications to grant Zparse access.

Parameters

Applicationrequired

Select configured Mistral AI application.

Input

Search queryrequired

Embeddings search request with model like:

{
   "query": <String>, # Actual text to generate embeddings from.
   "query_vector": [], # Empty before generation
   "filters": [ # Filter for metadata
     {
         "attribute": <String>, # which attribute to filter from
         "value": <String>, # which value matching given attribute to filter from
     }
   ],
   "limit": <Number>, # Own many vector to return from rag database
   "exact": <Bool>, # Whether to exact match on filters of not
}

Output

JSON Embeddingsrequired

Embeddings search request with model like:

{
   "query": <String>, # Actual text to generate embeddings from.
   "query_vector": [f32, f32, f32,...], # Generated vector
   "filters": [ # Filter for metadata
     {
         "attribute": <String>, # which attribute to filter from
         "value": <String>, # which value matching given attribute to filter from
     }
   ],
   "limit": <Number>, # Own many vector to return from rag database
   "exact": <Bool>, # Whether to exact match on filters of not
}