🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

Free, simple, and intuitive online database diagram editor and SQL generator.

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation

LLM based autonomous agent that conducts deep local and web research on any topic and generates a long report with citations.

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

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

A high-throughput and memory-efficient inference and serving engine for LLMs

Make websites accessible for AI agents

Composable building blocks to build Llama Apps

🔥 Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.

Letta (formerly MemGPT) is the stateful agents framework with memory, reasoning, and context management.

Welcome to MitreMesh. Where MITRE's framework meets dynamic scenario generation, creating a comprehensive net of incident response tests for cybersecurity professionals.

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

AWS QnABot is a multi-channel, multi-language conversational interface (chatbot) that responds to your customer's questions, answers, and feedback. The solution allows you to deploy a fully functio…

A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.

All Algorithms implemented in Python

A toolkit to create optimal Production-readyRetrieval Augmented Generation(RAG) setup for your data