Configuring RAG

What You’ll Learn

How to configure Learning in Foyle to continually learn from human feedback

How It Works

• As you use Foyle, the AI builds a dataset of examples (input, output)
• The input is a notebook at some point in time , t
• The output is one more or cells that were then added to the notebook at time t+1
• Foyle uses these examples to get better at suggesting cells to insert into the notebook

Configuring RAG

Foyle uses RAG to improve its predictions using its existing dataset of examples. You can control the number of RAG results used by Foyle by setting agent.rag.maxResults.

foyle config set agent.rag.maxResults=3

Disabling RAG

RAG is enabled by default. To disable it run

foyle config set agent.rag.enabled=false

To check the status of RAG get the current configuration

foyle config get

Sharing Learned Examples

In a team setting, you should build a shared AI that learns from the feedback of all team members and assists all members. To do this you can configure Foyle to write and read examples from a shared location like GCS. If you’d like S3 support please vote up issue #153.

To configure Foyle to use a shared location for learned examples

1. Create a GCS bucket to store the learned examples

    gsutil mb gs://my-foyle-examples
   

2. Configure Foyle to use the GCS bucket

   foyle config set learner.exampleDirs=gs://${YOUR_BUCKET}
   

Optionally you can configure Foyle to use a local location as well if you want to be able to use the AI without an internet connection.

foyle config set learner.exampleDirs=gs://${YOUR_BUCKET},/local/training/examples