Plan to Capture Mike's Brain

Hi Co-Pilot, What is the best way to store a knowledge base so that it can be queried with prompts, much like talking to Co-Pilot, except the knowledge base is built by audio file transcripts?

That's a great question! To store a knowledge base built from audio file transcripts and make it queryable with prompts, you can follow these steps:

Transcription: Use a service like Amazon Transcribe to convert your audio files into text. This will generate transcripts that you can store and manage.
Storage: Store the transcriptions in a cloud storage service like Amazon S3. This will keep your data organized and easily accessible.
Indexing: Use a tool like Amazon Elasticsearch Service to index the transcriptions. This will allow you to perform fast and efficient searches on the text data.
Embeddings: To enable semantic search, you can use a service like Amazon Bedrock to create embeddings from the transcriptions. Embeddings are numerical representations of the text that capture its meaning, making it easier to find relevant content based on the context of the query.
Querying: Use a vector database to store the embeddings and perform queries against them. This will allow you to retrieve relevant information based on the semantic meaning of the prompts.
Integration: Integrate these services into your application using APIs. This will allow you to build a seamless interface for querying the knowledge base with prompts.

Here's a high-level overview of the process:

Audio Files -> Amazon Transcribe -> Transcripts -> Amazon S3 -> Amazon Elasticsearch Service -> Amazon Bedrock -> Vector Database -> Query Interface

This setup will enable you to build a robust and efficient knowledge base that can be queried with prompts, similar to how you interact with Copilot.