The GitHub repository for "llamaindex" houses an innovative indexing system that leverages the Llama.cpp technology. This cutting-edge repository incorporates advanced indexing methodologies to streamline and optimize data retrieval processes. It serves as a hub for developers seeking efficient and robust indexing solutions, offering a framework that integrates the power of Llama.cpp for seamless and high-performance data management.

Which embedding model is best:

• https://huggingface.co/spaces/mteb/leaderboard
• hkunlp/instructor-large

FAQs:

1. How do you update only new and modified documents in the index?

A. refreshed_docs = index.refresh_ref_docs(documents)

2. Which embeddings are best for multilingual content?

A. multilingual-e5-large

3. Which embeddings are best when you need to provide additional context (legal, medical, or scientific data)?

A. Instructor embeddings

Resources:

• https://github.com/aakinlalu/GenerativeAI
• MongoDB-LlamaIndex
• RAG/LLM Evaluators - DeepEval
• LlamaIndex-RAG