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A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
Harness LLMs with Multi-Agent Programming
The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.
Automatable GenAI Scripting
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
AICI: Prompts as (Wasm) Programs
No-code multi-agent framework to build LLM Agents, workflows and applications with your data
[ICML 2024] LLMCompiler: An LLM Compiler for Parallel Function Calling
[GenAI Application Development Framework] 🚀 Build GenAI application quick and easy 💬 Easy to interact with GenAI agent in code using structure data and chained-calls syntax 🧩 Use Agently Workflow to manage complex GenAI working logic 🔀 Switch to any model without rewrite application code
Official Repo for ICML 2024 paper "Executable Code Actions Elicit Better LLM Agents" by Xingyao Wang, Yangyi Chen, Lifan Yuan, Yizhe Zhang, Yunzhu Li, Hao Peng, Heng Ji.
Low code tool to rapidly build and coordinate multi-agent teams
Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊
Your 24/7 On-Call AI Agent - Solve Alerts Faster with Automatic Correlations, Investigations, and More
The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured output. Works also with models not fine-tuned to JSON output and function calls.
The TypeScript framework for agents & workflows with react-like components. Lightning fast dev loop. Easy to learn. Easy to extend.
InternEvo is an open-sourced lightweight training framework aims to support model pre-training without the need for extensive dependencies.
Build, Improve Performance, and Productionize your LLM Application with an Integrated Framework
Integrating AI into every workflow with our open-source, no-code platform, powered by the actor model for dynamic, graph-based solutions.
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
历年ICLR论文和开源项目合集，包含ICLR2021、ICLR2022、ICLR2023、ICLR2024、ICLR2025.