Optimizing inference proxy for LLMs

🦾 Take control of your AI agents

HumanLayer enables AI agents to communicate with humans in tool-based and async workflows. Guarantee human oversight of high-stakes function calls with approval workflows across slack, email and more. Bring your LLM and Framework of choice and start giving your AI agents safe access to the world. Agentic Workflows, human in the loop, tool calling

End-to-end Generative Optimization for AI Agents

A framework for agentic workflow creation and deployment

Declarative framework to build LLM-based applications

Augment Swarm with durable execution to help you build reliable and scalable multi-agent systems.

Main repo for TaskTitan Community Core version

The Library for LLM-based multi-agent applications

A multi-agent chatroom for AutoGen agents

The Library for LLM-based web-agent applications

Agents and RAG workflows with little to no code

Learn how to build Agentic Workflows on AWS

It shows a problem solver based on agentic workflow.

Minimal agentic library mixing the simplicity of OpenAI Swarm with the flexibility of the Vercel AI SDK. 🐝

Agentic translation using reflection workflow, refactored and sugared.

AgentMove: Predicting Human Mobility Anywhere Using Large Language Model based Agentic Framework

A demo of OpenAI o1 and Next.js, used to automate the import of user-provided contacts file.

Dependencies Upgrade with multi-agents (CrewAI & Langgraph)

A RAG system is just the beginning of harnessing the power of LLM. The next step is creating an intelligent Agent. In Agentic RAG the Agent makes use of available tools, strategies and LLM to generate response in a specialized way. Unlike a simple RAG, an Agent can dynamically choose between tools, routing strategy, etc.