Ship RAG based LLM web apps in seconds.

Chat snowflake database - Text to SQL

RAG with langchain using Amazon Bedrock and Amazon OpenSearch

Moved to https://github.com/Podrum/Podrum

OpenAI-Compatible RESTful APIs for Amazon Bedrock

🍰 PieMC is an exciting open-source project aimed at developing a powerful and customizable Minecraft Bedrock server software using Python 🐍

書籍「Amazon Bedrock 生成AIアプリ開発入門」のサンプルコード

Opinionated sample on how to build/deploy a RAG web app on AWS powered by Amazon Bedrock and PGVector (on Amazon RDS)

Multitenant environment automation.

A demo ChatBot application developed using Amazon Bedrock service's KnowledgeBase, Agent and other AWS's serveless GenAI solution.

Easy "1-line" calling of all LLMs from OpenAI, MS Azure, AWS Bedrock, GCP Vertex, and Ollama

AIOps modules is a collection of reusable Infrastructure as Code (IaC) modules for Machine Learning (ML), Foundation Models (FM), Large Language Models (LLM) and GenAI development and operations on AWS

This project is everything Chat-GPT should be for developers! An advanced AI-driven coding companion tailored for developers. Seamlessly bridging the gap between traditional coding and AI capabilities, we offer real-time chat interactions, on-demand agent functions, and intuitive code management. Feedback welcome!

A Generative AI Chatbot application to provide personalized travel recommendations using Amazon Redshift and Amazon Bedrock

With this WhatsApp app, you can chat in any language with a Large language models (LLM) on Amazon Bedrock. Send voice notes and receive transcriptions. By making a minor change in the code, you can also send the transcription to the model.

End to end example of a Retail Agent implemented with agents for Amazon Bedrock

Converts Java .nbt files to Bedrock .mcstructure files

Use natural language to Generate Amazon Athena SQL queries to fetch data.

This GitHub repository guides you through building an advanced Conversational AI assistant using AWS services and Anthropic's Claude V2 model. It features intelligent routing to relevant functions, database querying, semantic searches, Lambda function executions, and specialized interactions.

Automatically comments Python code, adding docstrings and type annotations, with optional translation to other languages.