List of software that allows searching the web with the assistance of AI: https://hf.co/spaces/felladrin/awesome-ai-web-search

Multimodal RAG to search and interact locally with technical documents of any kind

CodeRAG-Bench: Can Retrieval Augment Code Generation?

'Talk to your slide deck' (Multimodal RAG) using foundation models (FMs) hosted on Amazon Bedrock and Amazon SageMaker

Open source implementation of Sova - RAG-based Web search engine using power of LLMs. Using Langchain, Ollama, HuggingFace Embeddings and scraping google search results.

This is a RAG implementation using Open Source stack. BioMistral 7B has been used to build this app along with PubMedBert as an embedding model, Qdrant as a self hosted Vector DB, and Langchain & Llama CPP as an orchestration frameworks.

This is a RAG based chatbot in which semantic cache and guardrails have been incorporated.

This example repository illustrates the usage of LLMs with Quarkus by using the quarkus-langchain4j extension to build integrations with ChatGPT or Hugging Face. The code dives into simple conversations, retrieval augmented generation (RAG) and building agents.

Techniques for Using LLMs Effectively: An Introduction to Prompt Engineering, Retrieval Augmented Generation, and Toolformer

Source code for the Gilded Age Gourmet, a cooking chat app based on the Boston Cooking-School Cook Book.

Web application to help develop scraping techniques to create context in LLM prompts.

🧠 A self-contained, frontend-only RAG chat interface. Plug in any RAG API URL and Bearer token—no server, no setup, full local history, and zero dependencies.

Retrieval-Augmented Generation using Azure OpenAI

RAG Chatbot for Technical Documentation 🤖📄 - Using LanChain 🦜🔗

VectorSearch.Tech - Blog articles , tutorials, and guides on latest search technologies.

Advancing the next generation of Retrieval Augmented Generation (RAG): A dynamic exploration of RAG technology's evolving landscape. This repository is the go-to resource for state-of-the-art developments, conceptual advancements, and the future trajectory of AI-driven information retrieval and generation.

Use the OpenAI API to connect to the Elasticsearch search engine, and then recommend relevant content or products to users.

Perplexify is a demo search engine showcasing a Retrieval-Augmented Generation (RAG) workflow, fetching and ranking web content to generate context-aware answers using language models.

🚀 Revolutionize your data interaction with a cutting-edge chatbot built on Retrieval-Augmented Generation (RAG) and OpenAI’s GPT-4. Upload documents, create custom knowledge bases, and get precise, contextual answers. Ideal for research, business operations, customer support, and more!

A curated list of LLM aided with Retrieval Augmented Generation (RAG)