AI RAG Configuration

Plugin Parameters

See plugin common configurations for configuration options available to all plugins.

embeddings_provider — object · required

Embedding model provider configurations.
- azure_openai — object · required
  
  Azure OpenAI embedding model configurations.
  - endpoint — string · required
    
    Azure OpenAI embedding model endpoint.
  - api_key — string · required
    
    Azure OpenAI API key. The value is encrypted with AES before being stored in etcd.
vector_search_provider — object · required

Vector search provider configurations.
- azure_ai_search — object · required
  
  Configurations of Azure AI Search.
  - endpoint — string · required
    
    Azure AI Search endpoint.
  - api_key — string · required
    
    Azure AI Search API key. The value is encrypted with AES before being stored in etcd.
ssl_verify — boolean · optional · default: true

If true, verify TLS certificates when calling the embedding and vector search endpoints. Available in API7 Enterprise from version 3.9.10 and APISIX from version 3.17.0.

The request body should follow the below configurations.

ai_rag — object · required

Request body RAG specifications.
- embeddings — object · required
  
  Embedding specifications.
  
  The following parameters are available if you are working with Azure OpenAI.
  - input — string · required
    
    Input prompt to the LLM, which will be used to compute embeddings and generate a RAG-enhanced response.
  - user — string · optional
    
    A unique identifier representing your end user, which helps in monitoring and detecting abuse.
  - encoding_format — string · optional · default: float
    
    Valid values: float or base64
    
    Data type of the returned embeddings.
  - dimensions — integer · optional
    
    Dimensions limit of the embedding model used to output the vectors. It should match the dimension of your embedding model. For instance, the dimensions for text-embedding-ada-002 are fixed at 1536. For text-embedding-3-small or text-embedding-3-large, dimensions range from 1 to 1536 and 3072, respectively.
- vector_search — object · required
  
  Vector search specifications.
  
  The following parameter is available if you are working with Azure AI Search.
  - fields — string · required
    
    Fields for the vector search.