No-code RAG with ChatGPT and LlamaIndex

Retrieval augmented generation (RAG) is one of the big use cases of LLMs. RAG uses external documents to provide context to LLMs and improve their accuracy. RAG reduces hallucinations and enables developers to use LLMs for applications that involve information not included in their training data, including breaking news stories, user-specific data, or company documents.

There are several tools that enable you to use RAG with your LLMs. A new open-source project by LlamaIndex provides you with a web application and a no-code interface to create RAG agents with ChatGPT. This can be a good foundation to create your own RAG apps.

Read the full article on TechTalks.

For more tips and tricks:

• How to fine-tune GPT-3.5 or Llama 2 with a single instruction

• How to run multiple fine-tuned LLMs for the price of one

• How to launch an LLM API server with minimal coding

• How to write better code with ChatGPT

Recommendations:

• My go-to platform for working with ChatGPT, GPT-4, and Claude is ForeFront.ai, which has a super-flexible pricing plan and plenty of good features for writing and coding.

• If you want a reliable VPN, try PrivadoVPN, which has servers in 50+ server locations. There is currently a Black Friday sale that gives you a 90% discount.