Use a DAO to govern LLM training data, Part 4: MetaMask authentication

This article discusses using a decentralized autonomous organization (DAO) and MetaMask authentication to govern the ingestion of training data for large language models (LLMs) into an Amazon Bedrock knowledge base.

Specifically, the article covers:

• Setting up a Lambda authorizer function using MetaMask authentication to validate Ethereum addresses allowed to upload training data
• Creating a frontend Lambda function to generate a web interface for users to sign messages with MetaMask and initiate uploading data
• Configuring the existing API Gateway and Lambda setup from previous parts to use the new authorizer
• Testing the end-to-end workflow of authenticating via MetaMask to upload training data
• Cleaning up the resources created in this multi-part series