Prompt, RAG, and LLM engineering examples.
What is RAG?
RAG is a technique for augmenting LLM knowledge with additional, often private or real-time, data.
Large Language Models (LLMs) have knowledge up to a certain training date and can reason on various topics. To handle private or newer data, they need Retrieval Augmented Generation (RAG) to integrate specific, updated information into their prompts.
So far, RAG applications are the most helpful outcome of the AI revolution.
- LangChain is a framework designed to simplify the creation of applications using large language models.
- OpenAI LLM
- Chroma vector database
Update the .env file with your OPENAI_KEY
python3 -m venv env
source env/bin/activate
pip3 install -r requirements.txt
python3 cs_bot.py