How do we add Memory to LLMs?

Basic Premise

Adding memory in LLMs currently is through the use of Vector Databases.

This leads to what has been dubbed as: Retrieval Augmented Generation

Key Steps:

To build a vector storage, you will need to:

Ingest Documents
Split Documents
Create an Embedding Model
Load it to a Vector Database

Example of building with Langchain is given here: Langchain RAG

(Not necessary but useful) Orchestrator:

Using orchestrator frameworks like LangChain and LlamaIndex can make things easier.

See Also

Link Text

References

This project uses code from the following source:

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