aws

AWS Well-Architected Framework Review (WAFR) Acceleration with Generative AI (GenAI) sample.

Learn how to Quickly build Generative AI applications with Amazon Bedrock

Abstractive and Extractive Text summarization using Transformers.

This repo covers LLM, Agents, MCP Tools, Skills concepts with sample codes: LangChain & LangGraph, AWS Strands Agents, Google Agent Development Kit, Fundamentals.

🦾 A production‑ready research outreach AI agent that plans, discovers, reasons, uses tools, auto‑builds cited briefings, and drafts tailored emails with tool‑chaining, memory, tests, and turnkey Docker, AWS, Ansible & Terraform deploys. Bonus: An Agentic RAG System & a Coding Pipeline with multistep planning, self-critique, and autonomous agents.

Build a genAI Whatsapp app that processes images, voice notes, videos, and documents with Amazon Bedrock, and also stores the conversation history.

Demonstration application showing how Neo4j works with Amazon Bedrock

How to run Stable Diffusion Automatic1111 WebUI on AWS EC2 instance

한국어 STT 출력의 CER, WER, CRR, 키워드·개체명·코퍼스 평가를 제공하는 Python 패키지

OmniMCP uses Microsoft OmniParser and Model Context Protocol (MCP) to provide AI models with rich UI context and powerful interaction capabilities.

Demonstration of Natural Language Query (NLQ) of an Amazon RDS for PostgreSQL database, using SageMaker JumpStart, Amazon Bedrock, LangChain, Streamlit, and Chroma.

An Amazon Transcribe demo to produce a Microsoft Word document containing the turn-by-turn transcription of the audio. This will include additional metadata depending upon the options selected, such as caller sentiment, category identification and issue detection

Example ChatGPT chatbots using Langchain and OpenAI

Invoking models on Amazon Bedrock using Rust

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

This repo provides Generative AI and AI/ML code samples, blueprints (end-to-end solutions) and proof of concepts oriented to the LATAM market

Zero administration inference with AWS Lambda for 🤗

Build and deploy a full-stack RAG app on AWS with Terraform, using free tier Gemini Pro, real-time web search using Remote MCP server and Streamlit UI with token based authentication.

Tune efficiently any LLM model from HuggingFace using distributed training (multiple GPU) and DeepSpeed. Uses Ray AIR to orchestrate the training on multiple AWS GPU instances

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