amazon-bedrock
There are 3 repositories under amazon-bedrock topic.
gofireflyio / aiac
Artificial Intelligence Infrastructure-as-Code Generator.
Language:Go 3372- aws-genai-llm-chatbot
aws-samples / 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
Language:TypeScript 982 This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models
Language:Jupyter Notebook 378- generative-ai-cdk-constructs
awslabs / generative-ai-cdk-constructs
AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.
Language:TypeScript 307 LLM-powered document chat using Amazon Bedrock and AWS Serverless
Language:TypeScript 215build-on-aws / llm-rag-vectordb-python
Explore sample applications and tutorials demonstrating the prowess of Amazon Bedrock with Python. Learn to integrate Bedrock with databases, use RAG techniques, and showcase experiments with langchain and streamlit.
Language:Jupyter Notebook 94Creating Amazon Bedrock agents with Streamlit Framework
Language:Python 58This repository is intended for those looking to dive deep on advanced Text-to-SQL concepts.
Language:Jupyter Notebook 57Prototyping Generative AI Use Cases with Amazon Bedrock and Langchain
Language:JavaScript 56aws-solutions-library-samples / guidance-for-natural-language-queries-of-relational-databases-on-aws
Demonstration of Natural Language Query (NLQ) of an Amazon RDS for PostgreSQL database, using SageMaker JumpStart, Amazon Bedrock, LangChain, Streamlit, and Chroma.
Language:Python 56Learn how to Quickly build Generative AI applications with Amazon Bedrock
Language:Python 56This repo provides sample generative AI stacks built atop the AWS Generative AI CDK Constructs.
Personalized nutritional app, serverless, tailored to your shopping and cooking needs, empowered by generative AI technology (Amazon Bedrock, Anthropic, Claude Haiku, Claude Sonnet) using AWS CDK on AWS
Language:TypeScript 43Learn how to quickly build Agents with Amazon Bedrock
Language:Python 43Bedrock Knowledge Base and Agents for Retrieval Augmented Generation (RAG)
Language:HTML 39This repository features three demos that can be effortlessly integrated into your AWS environment. They serve as a practical guide to leveraging AWS services for crafting a sophisticated Large Language Model (LLM) Generative AI, geared towards creating a responsive Question and Answer Bot and localizing content generation.
Language:TypeScript 38.NET FM Playground is a .NET MAUI Blazor sample application showcasing how to leverage Amazon Bedrock from C# code. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API.
Language:HTML 35- rhubarbLanguage:Python 34
Learn to build custom prompts and tools for LangChain agents
Language:Python 30Explore how you can use Amazon Bedrock with Python in a dynamic environment! It includes a FastAPI app and a Next.js frontend, perfect for learning and experimentation with generative AI on AWS.
Language:JavaScript 30'Talk to your slide deck' (Multimodal RAG) using foundation models (FMs) hosted on Amazon Bedrock and Amazon SageMaker
Language:HTML 27Learn how to build generative AI applications on AWS using PartyRock, Amazon Bedrock, and Amazon Q
Language:Python 27Labs for the "Build an agentic LLM assistant on AWS" workshop. A step by step agentic llm assistant development workshop using serverless three-tier architecture.
Language:Jupyter Notebook 24A 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.
Language:Python 19AWS Go SDK examples for Amazon Bedrock
Language:Go 18Amazon Bedrock AI Karaoke is an interactive demonstration of Amazon Bedrock. Users complete the prompt with the microphone and choose the best response. Powered by Amazon Bedrock, Amazon Transcribe and Amazon ECS Anywhere.
Language:Python 17How to build a chat assistant with Amazon Bedrock using LLMs, Embeddings model, and Knowledge Bases for Amazon Bedrock.
Language:Jupyter Notebook 15Uncovering Hidden Connections in Unstructured Financial Data using Amazon Bedrock and Amazon Neptune
Language:Python 15abhirockzz / langchain-opensearch-rag
Vector databases for generative AI
Language:Python 14Get a summary of the most recent news from an RSS or Atom feed using Amazon Bedrock.
Language:Python 14Implement RAG (using LangChain and PostgreSQL) for Go applications to improve the accuracy and relevance of LLM outputs
Language:Go 13A pipeline to convert contextual knowledge stored in documents and databases into text embeddings, and store them in a vector store
Language:TypeScript 12Welcome to this repo where we'll continue adding hands-on examples demonstrating the use of the Java SDK for Amazon Bedrock.
Language:Java 12aws-banjo / intro_bedrock_workshop
Intro workshop to Amazon Bedrock
Language:Python 11Automate process to change image background using Amazon Bedrock and AWS Step Functions
Language:Python 11How to build a simplified Corrective RAG assistant with Amazon Bedrock using LLMs, Embeddings model, Knowledge Bases for Amazon Bedrock, and Agents for Amazon Bedrock.
Language:Jupyter Notebook 11