There are 119 repositories under llm-agent topic.
Letta is the platform for building stateful agents: open AI with advanced memory that can learn and self-improve over time.
AgentScope: Agent-Oriented Programming for Building LLM Applications
Pocket Flow: Codebase to Tutorial
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
ReLE评测:中文AI大模型能力评测(持续更新):目前已囊括303个大模型,覆盖chatgpt、gpt-5、o4-mini、谷歌gemini-2.5、Claude4.5、智谱GLM-Z1、文心一言、qwen3-max、百川、讯飞星火、商汤senseChat、minimax等商用模型, 以及kimi-k2、ernie4.5、minimax-M1、DeepSeek-R1-0528、deepseek-v3.2、qwen3-2507、llama4、GLM4.5、gemma3、mistral等开源大模型。不仅提供排行榜,也提供规模超200万的大模型缺陷库!方便广大社区研究分析、改进大模型。
Context retrieval for AI agents across apps and databases
Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web, vision.
👾 Open source implementation of the ChatGPT Code Interpreter
An AI-powered custom node for ComfyUI designed to enhance workflow automation and provide intelligent assistance
总结Prompt&LLM论文,开源数据&模型,AIGC应用
A curated list of Generative AI tools, works, models, and references
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible.
A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)
A repo lists papers related to LLM based agent
[ICML 2024] LLMCompiler: An LLM Compiler for Parallel Function Calling
Quark Agent - Your AI-powered Android APK Analyst
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
Your 24/7 On-Call AI Agent - Solve Alerts Faster with Automatic Correlations, Investigations, and More
[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 Event-Driven Flow *TriggerFlow* 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.
Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.
Agentic-RAG explores advanced Retrieval-Augmented Generation systems enhanced with AI LLM agents.
Low code tool to rapidly build and coordinate multi-agent teams
💻 A curated list of papers and resources for multi-modal Graphical User Interface (GUI) agents.
[CVPR 2024 🔥] Grounding Large Multimodal Model (GLaMM), the first-of-its-kind model capable of generating natural language responses that are seamlessly integrated with object segmentation masks.
Interactive LLM Powered NPCs, is an open-source project that completely transforms your interaction with non-player characters (NPCs) in any game! 🎮🤖🚀
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.
Integrate LLM in any pipeline - fit/predict pattern, JSON driven flows, and built in concurency support.
xLAM: A Family of Large Action Models to Empower AI Agent Systems