Mistral: Embeddings search

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

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

Parameters

Application—REQUIRED

Select configured Mistral AI application.

Input

Search query—REQUIRED

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 Embeddings—REQUIRED

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
}