Browsing Tag
rag
24 posts
Function-based RAG: Extending LLMs Beyond Static Knowledge Bases
RAG Defined Retrieval-Augmented Generation (RAG) effectively overcomes a significant limitation in the field of Large Language Models (LLMs).…
The 10 Top-Rated Talks at NODES 2024
We did it! A huge thank you to everyone who turned NODES 2024 into such a great conference,…
Swiftide 0.12 – Hybrid Search, search filters, parquet loader, and a giant speed bump
Excited to announce Swiftide 0.12 🚀 A Rust library for building AI applications using retrieval augmented generation. Retrieving…
How a history-aware retriever works?
The history-aware retriever discussed in this post is the one returned by the create_history_aware_retriever function from the LangChain…
Hill climbing generative AI problems: When ground truth values are expensive to obtain & launching fast is important
For many generative AI applications it is expensive to create ground truth answers for a set of inputs…
Building a RAG Chatbot with LlamaIndex and eBay API Integration
RAG (Retrieval-Augmented Generation) is all the rage. And there’s a good reason why. Like so many others, I…
Advanced Indexing Techniques with LlamaIndex and Ollama: Part 2
Advanced Indexing Techniques with LlamaIndex and Ollama: Part 2 Code can be found here: GitHub – jamesbmour/blog_tutorials: Welcome…
Exploring Retrieval Augmented Generation (RAG): Chunking, LLMs, and Evaluations
Retrieval Augmented Generation (RAG) is a useful technique for using your own data in an AI-powered Chatbot. In…
Snapshots for AI: A “RAG-Like” solution for programming with LLMs
Picture this: You’re a developer, deep in the trenches of a complex project. Your trusty AI assistant, powered…
Guardrails AI, AAAL Pt.5
As I explored the landscape of adversarial robustness in LLMs, Guardrails AI stood out for its open-source approach…
