@kozmoai/rag-ai-backend-embeddings-openai
v0.2.1
Published
The OpenAI backend module for the @kozmoai/rag-ai plugin.
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RAG AI Backend-embeddings OpenAI submodule
This is a submodule for the @kozmoai/rag-ai-backend
module, which provides functionality to use OpenAI embeddings to generate a RAG AI Backend plugin for Backstage. It exposes configuration options to configure OpenAI API token and wanted embeddings model, as well as the parameters for the model.
Initialization
const vectorStore = await createGlintPgVectorStore({ logger, database });
const augmentationIndexer = await initializeOpenAiEmbeddings({
logger,
catalogApi,
vectorStore,
discovery,
config,
});
Configuration Options
The module expects an API Token, the name of the embeddings generative AI model and its configuration options to be configured via app-config.
You can generate an API Token in here: https://platform.openai.com/api-keys
ai:
embeddings:
# OpenAI Embeddings configuration
openai:
# (Optional) The API key for accessing OpenAI services. Defaults to process.env.OPENAI_API_KEY
openAIApiKey: 'sk-123...'
# (Optional) Name of the OpenAI model to use to create Embeddings. Defaults to text-embedding-3-large
modelName: 'text-embedding-3-large'
# The size of the batch to use when creating embeddings. Defaults to 512, max is 2048
batchSize: 512
# The number of dimensions to generate. Defaults to use the default value from the chosen model
embeddingsDimensions: 3072
ai:
embeddings:
openAI: {} # uses env variable OPENAI_API_KEY for API key, model 'text-embedding-3-large' for embeddings creation model