Popular GitHub Repositories for S3

? State-of-the-art, production ready LLM apps made mega-easy, so you don't have to build them from scratch ? Create a bot, now ?

GigAPI：基于DuckDB的Parquet存储引擎和OLAP数据池

?? RumbleDB 1.22.0 "Pyrenean oak" ? for Apache Spark | Run queries on your large-scale, messy JSON-like data (JSON, text, CSV, Parquet, ROOT, AVRO, SVM...) | No install required (just a jar to download) | Declarative Machine Learning and more

Larry ? is a bot generator that post content from different providers to one or multiple publishers

Fully managed RAG solution implemented using Knowledge Bases for Amazon Bedrock

? Stream inferences of real-time ML models in production to any data lake (Experimental)

MLFlow environment deployed with docker-compose, PostgreSQL as backend store and MinIO as S3 proxied artifact storage.

ReCiter: an enterprise open source author disambiguation system for academic institutions

Uncovering Hidden Connections in Unstructured Financial Data using Amazon Bedrock and Amazon Neptune

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

An advanced tool designed for creating automated news bulletins. It generates dynamic news scripts using OpenAI, and provides voice narration using either OpenAI or ElevenLabs text-to-speech services. The system supports seamless integration with AzuraCast and S3 for content storage and distribution, making it a versatile solution for broadcasters.

Avalok AI is easy to use platform to build search on documents including S3 bucket. We add ability to add RAG to get answers to your questions.

Zenn Books「SageMakerトレーニングジョブで推論回す本」で使用したコード

'Roiergasias' kubernetes operator is meant to address a fundamental requirement of any data science / machine learning project running their pipelines on Kubernetes - which is to quickly provision a declarative data pipeline (on demand) for their various project needs using simple kubectl commands. Basically, implementing the concept of No Ops. The fundamental principle is to utilise best of docker, kubernetes and programming language features to run a workflow with minimal workflow definition syntax. It is a Go based workflow running on command line or Kubernetes with the help of a custom operator for a quick and automated data pipeline for your machine learning projects (a flavor of MLOps).

AWS AI ChatBot streaming demo implementation using NodeJS, AWS Bedrock, Lambda and DocumentDB

AWS Sample for processing ROS bag files to detect objects within exported images. The solution draws bounding boxes for the detected objects within the exported images.

An implementation of a distributed machine learning algorithm using Spark able to identify fraud in credit card transactions

Serverless Intelligent Document Processing (IDP) solution for invoice automation using Amazon Bedrock Data Automation. Features automated data extraction, annotation, and processing pipeline built with AWS services and CDK.

Creating a Dockerized stack environment using MLflow, mysql and Minio to manage the lifecycle of TensorFlow models.

transform your documents into lively conversations