A proof-of-concept of retrieval-augmented generation, using Google's PaLM API.
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Updated
Jun 22, 2023 - Python
A proof-of-concept of retrieval-augmented generation, using Google's PaLM API.
Using Pinecone, LangChain + OpenAI for Generative Q&A with Retrieval Augmented Generation (RAG).
Retrieval Augmented Generation (RAG) using Azure Cognitive Search
Agents based Multi-lingual AI-seva kendra for helping you navigate through government resources
RAG chatbot built on top of trending M&A news.
Jupyeter Notebooks that demo Generative AI concepts
COSCUP 2023 的議程搜尋系統
This repository is dedicated to collecting blog posts and articles on the implementation of state-of-the-art techniques in semantic search, dense retrieval, and retrieval augmented generation (RAG).
Code and resources showcasing the Retrieval-Augmented Generation (RAG) technique, a solution for enhancing data freshness in Large Language Models (LLMs). Incorporate up-to-date external knowledge into LLM-generated responses. Additionally, this repository includes a Gradio-based user interface for seamless model deployment.
Optimal Chunk Size for Large Document Summarization
Exploring the use case of LLMs in healthcare, in particular assisting in document retrieval and summarization.
Easily create semantic search based LLM applications
LambdaRAG is a Retrieval Augmented Generation Chat AI Demo. Please read the full RAGs to Riches blog series.
an intro to retrieval augmented large language model
Course material for the DSD bootcamp on combining large language models with vector databases.
Examples of Prompt Engineering, Zero Shot Learning, Few Shot Learning and Retrieval Augmented Generation (RAG) using Hugging Face, Databricks and MLflow
Retrieval Augmented Generation (RAG) on audio data with LangChain
Rice, the programming language created by Dennis King.
A financial chatbot powered by an LLM and retrieval-augmented generation.
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