A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
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Updated
Jun 4, 2025 - Python
A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
Pocket Flow: Codebase to Tutorial
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
Harness LLMs with Multi-Agent Programming
The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.
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.
ContextGem: Effortless LLM extraction from documents
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.
InternEvo is an open-sourced lightweight training framework aims to support model pre-training without the need for extensive dependencies.
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.
FineTune LLMs in few lines of code (Text2Text, Text2Speech, Speech2Text)
A ReAct-Based Highly Robust Autonomous Agent Framework
AI-to-AI Testing | Simulation framework for LLM-based applications
Simplify interactions with Large Language Models
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