COSCUP 2023 的議程搜尋系統

Yet Another PDF Chatbot (Also see my ChatPDF repo)

RAG document chat with Amazon Bedrock using Typescript on Lambda.

Automate your customer support using OpenAI Assistants API

Demo RAG for prompting pdf files

Automate your customer support using Retrieval Augmented Generation (RAG): OpenAI + Pinecone

Playground for Langchain + RAG

A pipeline to convert contextual knowledge stored in documents and databases into text embeddings, and store them in a vector store

Retrieval Augmented Generation Application that utilizes Pinecone Vector Database, LangChain Framework and OpenAI embeddings.

just attempting to build a retrieval augmented generation package primarily focused on the antropic llm claude AI if everything goes as planned will start working on other LLMS. I'll appreciate the opportunity to talk about this.

Legal AI advisor based on RAG using +100,000 legal documents and SOTA embeddings and language model.

HTML to Markdown converter and crawler.

Edge compatible PDF.ai Chat with any PDF document You can ask questions, get summaries, find information, and more. Built with Pinecone, OpenAI, Langchain, Nextjs13, TypeScript, Clerk Auth, Drizzle ORM for edge runtime environment, Shadcn UI.

Learning NextJs 14 with app router. Messing with proper server/client component architecture, Next API routes, Next streaming, Next cache beta, retrieval augmented generation with OpenAI embeddings API, PineconeDB to store context/query embeddings, and chatbot with OpenAI prompt.

Create documents to improve the accuracy of large language models which employ retrieval augmented generation.

Library to generate vector embeddings in NodeJS

Build a generative AI application using Azure Functions and LangChain.js

Using LLMs and RAG to generate and optimize BigQuery searches

Chat application with PDF integration, offering users a seamless experience to engage in discussions around uploaded PDF files.