Optimizing inference proxy for LLMs

🦾 Take control of your AI agents

Trace, the New AutoDiff for AI Systems and LLM 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

A framework for agentic workflow creation and deployment

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

Agentic translation using reflection workflow, refactored and sugared.

Learn how to build Agentic Workflows on AWS

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.

Working towards the integration of human-machine in the Cybersecurity workflow.

VirtuTA is an AI teaching assistant that delivers quick, accurate responses to student queries directly on Piazza. Powered by agentic workflows, Google Gemini, and Langchain, it automates both conceptual and logistical course queries.

Agentic Workflows with Generative AI: Building AI Agents using CrewAI.

Multi-agent workflows with Llama3: A private on-device multi-agent framework

AI powered legal research engine. The system is based on multi AI agentic RAG systems leveraging the power of Llama3 LLM

Implementation of "Building Agentic RAG with LlamaIndex" offered by DeepLearning.AI focusing on developing intelligent research agents using the Retrieval-Augmented Generation (RAG) framework.

An open-source agentic workflow by Andrew Ng for machine translation, using LLM-equipped AI agents: Prompting LLM agents to translate from one language to another and refine it