Config File

warning

The config file format is subject to change as it's still in development.

note

This global configuration file is independent from the flow configuration files.

Usage

Using the config file is as simple as passing -c <path> or --config-file <path> to the knowledge CLI on supported commands. You may as well use the KNOW_CONFIG_FILE environment variable to set the path to the config file.

Configuration Overview

Here we try to capture all supported configuration items in one example.

note

You can write the config in YAML or JSON format. You can find some example config files in the GitHub repository.

embeddings:
  providers:
  - name: my-cohere
    type: cohere
    config:
      apiKey: "${COHERE_API_KEY}" # environment variables are expanded when reading the config file
      model: "embed-english-v2.0"
  - name: myopenai
    type: openai
    config:
      apiKey: "${OPENAI_API_KEY}"
      embeddingEndpoint: "/some-custom-endpoint" # anything that's not the default /embeddings
  - name: foobar
    type: vertex
    config:
      apiKey: "${GOOGLE_API_KEY}"
      project: "acorn-io"
      # apiEndpoint: https://us-central1-aiplatform.googleapis.com
      model: "text-embedding-004"

Sections

• embeddings: See Embedding Models for more details.
  • Select a provider using the command line flag --embedding-model-provider or the environment variable KNOW_EMBEDDING_MODEL_PROVIDER (default: openai).
  • Note: If a provider is selected but not specified in the config file, we'll assume that it's a standard provider configured via standard environment variables.
    • E.g. you select vertex, but that name is not configured, so we default to type=vertex and use the VERTEX_* environment variables to configure a standard Google Vertex AI provider.