build-on-aws
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llm-rag-vectordb-python
PublicExplore 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.- A fullstack real-time game where developers play four-in-a-row
agentic-workshop
PublicLearn how to build Agentic Workflows on AWS- Introducing "The Adventure Game", a concept for the November 2024 "AWS Game Builder Challenge". It's a text based, open ended, RPG (role playing game). The game use generative models from Amazon Bedrock using the Converse API to build an AI agent that uses a graph data structure to maintain game state.
- Technical solution to implement event processing prioritization with Apache Kafke using the concept of buckets.
terraform-samples
PublicCollections of examples of using Terraform with AWS- Example gaming leaderboard application covering streaming ingestion, CDC enrichment, processing and visualisation including demo of advance real-time analytics concepts like late data arrival, exactly-once, dynamic config, archival and on-demand replay
bedrock-agent-txt2sql
Public- Authorization is one of the foundational needs when building your applications and services. Learn how, with the help of Cedar and Amazon Verified Permissions, to to add non-trivial authorization rules to your web application.
bedrock-agents-streamlit
Public- Command-Query Responsibility Segregation (CQRS) is often presented as a pattern focused on scaling by separating reads and writes. However, this is an architecture-level pattern that has nothing to do with infrastructure. At AWS re:Invent 2023 session (BOA211) we explored the right way of combining AWS Lambda and CQRS together.
- This repository sets up an end-to-end CI/CD container pipeline with Hashicorp Terraform based on native AWS services for hosting and testing application code, building a container image from the code, pushing and storing the container image to ECR, and deploying this container on EKS as a deployment.
.github
Public- Use natural language to run inference on various LLMs via Bedrock agents
- This application is built in four stages using infrastructure as code with CDK with Python to deploy. In the first stage, an Amazon Aurora PostgreSQL vector database is set up. In the second stage, the Knowledge Base for Amazon Bedrock is created using the established database. The third stage involves creating an Amazon
- This repo provides guidance on setting up a bedrock agent to webscrape and internet search via action groups
langchain-embeddings
Publicgen-ai-workshop
PublicLearn how to build generative AI applications on AWS using PartyRock, Amazon Bedrock, and Amazon Q- Deploying TRURL 2 on Amazon SageMaker. TRURL 2 is a Large Language Model (LLM), which is a fine-tuned version of LLaMA 2 with support for Polish language developed by VoiceLab and published at the company profile on Hugging Face (https://huggingface.co/Voicelab).
- 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.