Configuring
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
Create a GCS bucket to store the learned examples
gsutil mb gs://my-foyle-examples
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
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