RAG Memory Lab

A mini Retrieval-Augmented Generation (RAG) project using local Ollama models.

What it does

• Loads memories from a text file
• Converts memories into embeddings
• Converts user question into an embedding
• Finds relevant memories using cosine similarity
• Sends retrieved context to a local LLM
• Generates an answer based on retrieved context

Technologies

• Python
• Ollama
• nomic-embed-text
• qwen2.5-coder
• NumPy

Run

python3 main.py