Repository History
138 repositories tagged with LLM
agency-agents: Your Complete AI Agency of Specialized Experts
agency-agents offers a comprehensive collection of over 140 meticulously crafted AI agent personalities, designed to act as specialized experts across various domains. From frontend development to marketing and sales, each agent comes with a unique voice, proven processes, and deliverable-focused outcomes. This repository provides a ready-to-deploy AI dream team to transform your workflow and accelerate project delivery.
Claude Code System Prompts: Deconstructing Agentic AI Coding Assistants
This repository offers a deep dive into the inner workings of modern agentic AI coding assistants. It reconstructs prompt patterns, agent coordination strategies, and security mechanisms, providing insights into how tools like Claude Code operate. The project serves as a valuable resource for understanding the architectural patterns behind these advanced AI systems.
Supply Chain Monitor: Automated Detection of Package Compromises
Supply Chain Monitor is a powerful tool by Elastic designed to automatically detect supply chain compromises in popular PyPI and npm packages. It polls registries for new releases, diffs them against predecessors, and uses an LLM via Cursor Agent CLI to classify changes as benign or malicious. Malicious findings trigger immediate Slack alerts, enhancing security for your software dependencies.
JARVIS: Connecting LLMs with the ML Community for AGI Exploration
JARVIS is an innovative system developed by Microsoft that aims to bridge Large Language Models (LLMs) with the broader Machine Learning community. It serves as a collaborative platform, using an LLM as a controller to orchestrate numerous expert models from Hugging Face Hub, thereby facilitating the exploration of Artificial General Intelligence (AGI) and solving complex AI tasks. This system streamlines the process of task planning, model selection, execution, and response generation.
Open Deep Research: A Configurable Open-Source Deep Research Agent
Open Deep Research is a fully open-source, configurable agent designed for deep research applications. It supports various model providers, search tools, and Model Context Protocol (MCP) servers, offering performance comparable to other popular deep research agents. Developed by LangChain, it leverages LangGraph for robust agent orchestration and provides extensive customization options.
Firecrawl: Web Scraping and Interaction API for AI Agents
Firecrawl is an open-source API designed to empower AI agents and applications with clean, structured web data. It provides robust capabilities for searching, scraping, and interacting with the web at scale, effectively transforming complex web content into LLM-ready formats. This tool handles the intricate challenges of web data extraction, allowing developers to focus on building intelligent applications.
LLMGym: A Unified Environment for LLM Agent Development and Benchmarking
LLMGym is a unified environment interface designed for developing and benchmarking LLM applications that learn from feedback. It provides a suite of seamlessly swappable environments, making fair and comprehensive comparisons easier for researchers and developers. This project aims to be the "gym" for LLM agents, offering an intuitive interface for various tasks.
oobabooga/text-generation-webui: The Premier Local LLM Interface
oobabooga/text-generation-webui is a powerful and versatile web UI for running large language models (LLMs) locally. It offers a 100% offline and private environment for text generation, vision, tool-calling, and even training, all accessible through an intuitive interface and API.
rag-from-scratch: Building Retrieval Augmented Generation Systems
This repository by LangChain AI offers a comprehensive guide to understanding and implementing Retrieval Augmented Generation (RAG) from scratch. It includes a series of Jupyter notebooks and an accompanying video playlist, making complex RAG concepts accessible for practical application. The resource highlights RAG's advantages over fine-tuning for factual recall in Large Language Models (LLMs).
asta-paper-finder: A Frozen-in-Time Agent for Reproducing Paper Finder Evaluations
asta-paper-finder is a standalone, "frozen-in-time" version of the AllenAI Paper Finder agent. This repository provides the code specifically for reproducing evaluation results, allowing researchers to locate sets of papers based on content and metadata criteria. It offers a stable snapshot of the agent's core paper-finding capabilities.
Strands Agents SDK-Python: Model-Driven AI Agent Development
Strands Agents SDK-Python offers a powerful, model-driven approach to building AI agents with minimal code. It supports a wide range of model providers and advanced capabilities like multi-agent systems and bidirectional streaming, scaling from local development to production. This Python SDK simplifies the creation of intelligent agents for various applications.
Kimi-k1.5: Scaling Reinforcement Learning with LLMs and Multimodality
Kimi-k1.5 introduces an o1-level multi-modal model that significantly advances reinforcement learning with Large Language Models. It demonstrates state-of-the-art performance in short-CoT tasks, outperforming leading models like GPT-4o and Claude Sonnet 3.5, and matches o1 performance in long-CoT scenarios across various modalities. This project highlights key innovations in long context scaling and improved policy optimization.