aws-samples

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Public repos: 6634Public gists: 0

fine-tune-qwen2-vl-with-llama-factory

language: Jupyter Notebook

created at: 2024-10-17

updated at: 2024-11-20

jira-ticket-classification

A Python-based AWS solution for automated Jira ticket classification using Amazon Bedrock. This project helps Jira users automate ticket categorization featuring S3 integration, AWS Glue deduplication, LLMs, and Terraform deployment.

language: Python

created at: 2024-10-04

updated at: 2024-11-11

sagemaker-hosted-stable-video-diffusion-img2vid-xt

language: Jupyter Notebook

created at: 2024-08-09

updated at: 2024-09-25

deploy-langfuse-on-ecs-with-fargate

Hosting Langfuse on Amazon ECS with Fargate using CDK Python

star: 22fork: 3

language: Python

created at: 2024-08-01

updated at: 2024-11-20

failure-analysis-assistant

Failure Analysis Assistant (FA2) is a sample that supports failure analysis when a failure occurs using LLM in Amazon Bedrock. It was shown as an exhibition demo for AWS Summit Japan 2024.

star: 12fork: 3

language: TypeScript

created at: 2024-07-17

updated at: 2024-11-07

function-calling-using-amazon-bedrock-anthropic-claude-3

Function calling using Amazon Bedrock with Anthropic Claude 3 foundation model

star: 21fork: 4

language: Python

created at: 2024-07-07

updated at: 2024-11-15

finetune-sdxl-on-sagemaker-and-host-on-infr2

language: Jupyter Notebook

created at: 2024-05-28

updated at: 2024-08-21

Meta-Llama-on-AWS

star: 60fork: 17

language: Jupyter Notebook

created at: 2024-05-20

updated at: 2024-11-12

comfyui-on-amazon-sagemaker

This project demonstrates how to generate images using Stable Diffusion or FLUX.1 models by hosting ComfyUI on Amazon SageMaker inference endpoint.

star: 33fork: 9

language: Python

created at: 2024-05-16

updated at: 2024-11-07

whats-new-summary-notifier

A generative AI application that summarizes the content of AWS What's New and other web articles in multiple languages, and delivers the summary to Slack or Microsoft Teams.

star: 38fork: 4

language: Python

created at: 2024-05-07

updated at: 2024-11-14

qa-app-with-rag-using-amazon-bedrock-and-kendra

Question Answering Generative AI application with Large Language Models and RAG powered by Amazon Bedrock and Amazon Kendra

language: Python

created at: 2024-05-07

updated at: 2024-09-18

sample-chatbot-for-bedrock-knowledge-base-and-multimodal-llms

Multimodal Chatbot with Amazon Bedrock Knowledge Bases Integration

language: Python

created at: 2024-05-03

updated at: 2024-11-18

foundational-llm-chat

Chainlit application built using AWS CDK, secured with Amazon Cognito, that allows you to interact with Anthropic's Claude language models from Amazon Bedrock.

language: TypeScript

created at: 2024-05-02

updated at: 2024-11-07

async-stable-diffusion-image-api

language: Python

created at: 2024-04-17

updated at: 2024-07-16

build-an-agentic-llm-assistant

Labs for the "Build an agentic LLM assistant on AWS" workshop. A step by step agentic llm assistant development workshop using serverless three-tier architecture.

star: 43fork: 14

language: Jupyter Notebook

created at: 2024-04-11

updated at: 2024-11-19

rag-with-amazon-bedrock-and-opensearch

Opinionated sample on how to build and deploy a RAG application with Amazon Bedrock and OpenSearch

star: 20fork: 1

language: Python

created at: 2024-03-28

updated at: 2024-11-11

generative-bi-using-rag

A solution guidance for Generative BI using Amazon Bedrock, Amazon OpenSearch with RAG

star: 122fork: 38

language: Python

created at: 2024-03-12

updated at: 2024-11-12

rag-with-amazon-opensearch-and-sagemaker

Question Answering Generative AI application with Large Language Models (LLMs) and Amazon OpenSearch Service

star: 15fork: 3

language: Python

created at: 2024-02-21

updated at: 2024-11-10

amazon-bedrock-rag

Fully managed RAG solution implemented using Knowledge Bases for Amazon Bedrock

star: 68fork: 21

language: JavaScript

created at: 2024-02-19

updated at: 2024-11-20

rag-with-amazon-bedrock-and-documentdb

Question Answering Generative AI application with Large Language Models (LLMs), Amazon Bedrock, and Amazon DocumentDB (with MongoDB Compatibility)

language: Jupyter Notebook

created at: 2024-02-16

updated at: 2024-11-17

conversational-ai-assistant-multi-route-chain

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.

star: 27fork: 8

language: Python

created at: 2024-02-09

updated at: 2024-10-28

rag-with-amazon-bedrock-and-memorydb

Question Answering Generative AI application with Large Language Models (LLMs), Amazon Bedrock, and Amazon MemoryDB for Redis

language: Jupyter Notebook

created at: 2024-02-03

updated at: 2024-11-08

text-to-sql-bedrock-workshop

This repository is intended for those looking to dive deep on advanced Text-to-SQL concepts.

star: 90fork: 20

language: Jupyter Notebook

created at: 2024-01-31

updated at: 2024-11-18

rag-with-amazon-bedrock-and-pgvector

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

star: 62fork: 15

language: Python

created at: 2024-01-22

updated at: 2024-11-18

foundation-model-benchmarking-tool

Foundation model benchmarking tool. Run any model on any AWS platform and benchmark for performance across instance type and serving stack options.

star: 196fork: 31

language: Jupyter Notebook

created at: 2024-01-09

updated at: 2024-11-20

rag-with-amazon-postgresql-using-pgvector-and-sagemaker

Question Answering application with Large Language Models (LLMs) and Amazon Postgresql using pgvector

star: 11fork: 2

language: Python

created at: 2024-01-06

updated at: 2024-11-17

rag-with-amazon-opensearch-serverless-and-sagemaker

Question Answering Generative AI application with Large Language Models (LLMs) and Amazon OpenSearch Serverless Service

language: Python

created at: 2024-01-06

updated at: 2024-09-12

multimodal-rag-on-slide-decks

'Talk to your slide deck' (Multimodal RAG) using foundation models (FMs) hosted on Amazon Bedrock and Amazon SageMaker

star: 33fork: 6

language: HTML

created at: 2023-12-19

updated at: 2024-10-23

text-embeddings-pipeline-for-rag

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

star: 14fork: 1

language: TypeScript

created at: 2023-11-28

updated at: 2024-08-28

aws-agentic-document-assistant

An agent based LLM assistant that extends RAG with batch entity extraction and SQL querying to improve performance on multi-step and analytical questions.

star: 59fork: 22

language: Jupyter Notebook

created at: 2023-11-13

updated at: 2024-11-18

amazon-sagemaker-llama2-prompting-best-practices

Best practices for prompting for Meta's Llama2 Large Language Model using Amazon Sagemaker

language: Jupyter Notebook

created at: 2023-11-02

updated at: 2024-10-20

amazon-sagemaker-llama2-response-streaming-recipes

Amazon SageMaker Llama 2 Inference via Response Streaming

star: 13fork: 3

language: Jupyter Notebook

created at: 2023-10-11

updated at: 2024-09-08

bedrock-kb-rag-workshop

Bedrock Knowledge Base and Agents for Retrieval Augmented Generation (RAG)

star: 47fork: 10

language: HTML

created at: 2023-10-02

updated at: 2024-11-19

awsome-distributed-training

Collection of best practices, reference architectures, model training examples and utilities to train large models on AWS.

star: 202fork: 85

language: Python

created at: 2023-09-30

updated at: 2024-11-19

serverless-pdf-chat

LLM-powered document chat using Amazon Bedrock and AWS Serverless

star: 247fork: 223

language: TypeScript

created at: 2023-09-30

updated at: 2024-11-12

serverless-rag-demo

Amazon Bedrock Foundation models with Amazon Opensearch Serverless as a Vector DB

star: 154fork: 47

language: Python

created at: 2023-08-23

updated at: 2024-11-19

bedrock-claude-chat

AWS-native chatbot using Bedrock + Claude (+Mistral)

star: 902fork: 321

language: TypeScript

created at: 2023-08-22

updated at: 2024-11-21

rag-using-langchain-amazon-bedrock-and-opensearch

RAG with langchain using Amazon Bedrock and Amazon OpenSearch

star: 198fork: 39

language: Python

created at: 2023-08-17

updated at: 2024-11-14

generative-ai-use-cases-jp

すぐに業務活用できるビジネスユースケース集付きの安全な生成AIアプリ実装

star: 690fork: 123

language: TypeScript

created at: 2023-08-17

updated at: 2024-11-20

amazon-bedrock-samples

This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models

star: 599fork: 300

language: Jupyter Notebook

created at: 2023-07-05

updated at: 2024-11-20

aws-genai-llm-chatbot

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

star: 1.1Kfork: 330

language: TypeScript

created at: 2023-06-16

updated at: 2024-11-20

private-llm-qa-bot

star: 257fork: 62

language: Jupyter Notebook

created at: 2023-05-18

updated at: 2024-11-01

llm-apps-workshop

Use LLMs for building real-world apps

star: 109fork: 39

language: HTML

created at: 2023-04-19

updated at: 2024-10-26

lm-gvp

LM-GVP: A Generalizable Deep Learning Framework for Protein Property Prediction from Sequence and Structure

star: 50fork: 7

language: Jupyter Notebook

created at: 2021-08-18

updated at: 2024-11-20

scalable-hw-agnostic-inference

A hardware-agnostic (NVIDIA's GPUs and AWS Inferentia accelerators) deployment of text-to-image (Stable Diffusion 2.1) app and generate text (Llama3) on EKS controlled by K8s ingress in routing-time and Karpenter in scheduling-time that is scaled by KEDA.

star: 11fork: 9

language: Python

created at: 2019-11-05

updated at: 2024-11-15

aws-kr-startup-samples

A collection of AWS Korea Startup SA team materials for hands-on labs.

star: 15fork: 6

language: Jupyter Notebook

created at: 2019-02-19

updated at: 2024-11-15