Magick is a cutting-edge toolkit for a new kind of AI builder. Make Magick with us!
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Updated
Jul 3, 2024 - TypeScript
Magick is a cutting-edge toolkit for a new kind of AI builder. Make Magick with us!
Java version of LangChain
A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS
Opinionated sample on how to build/deploy a RAG web app on AWS powered by Amazon Bedrock and PGVector (on Amazon RDS)
Prisma extension to support PGVector
A web UI Project In order to learn the large language model. This project includes features such as chat, quantization, fine-tuning, prompt engineering templates, and multimodality.
AI implementation using langchain4j and springAI frameworks with Java
Bite-sized RAG Projects on AWS
Question Answering application with Large Language Models (LLMs) and Amazon Aurora Postgresql using pgvector
Question Answering application with Large Language Models (LLMs) and Amazon Postgresql using pgvector
This application uses LLM (Large Language Model) GPT-4o accessed via OpenAI API in order to generate text based on the user input. The user input is used to retrieve relevant information from the database and then the retrieved information is used to generate the text. This approach combines power of transformers and access to source documents.
A RAG app to ask questions about rows in a database table. Deployable on Azure Container Apps with PostgreSQL Flexible Server.
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector
ChatWeb can crawl web pages, read PDF, DOCX, TXT, and extract the main content, then answer your questions based on the content, or summarize the key points.
Extensible API and framework to build your Retrieval Augmented Generation (RAG) and Information Extraction (IE) applications with LLMs
Semantic search using Supabase PG Vector and LangChain for an AI assistant to interact with your dataset
VLib is a digital library platform targeting college library systems that utilises a vector database for discovering required resources and thereby making information accessible to all users irrespective of their knowledge level. It overcomes the incapability of present systems to handle descriptive queries thereby limiting information access.
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