Awesome LLM Apps

LLM Space v4 is a local-first desktop workbench for prototyping and developing AI agents. It lets users version prompts, system messages, tools, and model settings; trace each model call and tool run in an agent loop; replay historical runs to debug failures; and evaluate agent performance across runs. It can generate prompts and tools with AI and turn a thread into a runnable LangGraph agent. Threads, project files, and API keys remain on the user's computer, while the project describes the app as cloud-ready for managed agents. The desktop application uses Electrobun with a React, Tailwind CSS, and shadcn/ui interface, and is built as a Bun monorepo around Pi Agent Core.

Awesome Agent Skills is an open-source curated collection of more than 1,000 agent skills from official development teams and the community. Each listing provides a description and source link; the collection includes skills from projects such as Anthropic, Google Labs, Vercel, Stripe, Cloudflare, and others. The skills are documented for use with multiple coding-agent environments, including Claude Code, Codex, Gemini CLI, Cursor, GitHub Copilot, OpenCode, and Windsurf.

CowAgent is an open-source AI assistant and agent harness developed by LinkAI. It plans complex tasks step by step, runs tools and skills, controls computers and external services, maintains long-term memory and a personal knowledge base, and supports multi-agent teams with separate roles, models, skills, knowledge, and workspaces. Its architecture routes messages from web and messaging channels through an agent core that reasons over available models, tools, skills, memory, and knowledge before returning a response. Memory uses a three-tier structure of conversation context, daily memory, and long-term MEMORY.md, with a nightly Deep Dream process that distills memories; the knowledge base is an automatically curated Markdown wiki with cross-references and a browsable knowledge graph. Built-in tools include file and terminal operations, web fetching and search, scheduling, memory retrieval, vision, and browser automation, while MCP servers can be added through configuration. Skills can be installed from the Skill Hub, GitHub, ClawHub, or URLs, or authored through conversation. CowAgent supports multiple LLM providers and routes chat, vision, image generation, speech, and embedding workloads separately. It can run locally, in Docker, on a server, or through its macOS and Windows desktop client, with a web console for configuration and a command-line interface for service and skill management. The project is licensed under the MIT License and was formerly named chatgpt-on-wechat.

LiveKit Agents is an open-source Python framework for building programmable, real-time multimodal voice agents that run as server-side participants. It combines speech-to-text, large language models, text-to-speech, and realtime APIs with LiveKit's WebRTC clients, telephony stack, RPC and data APIs, and MCP tool support. The framework provides agent sessions, server-side job scheduling and dispatch, semantic turn detection based on a transformer model, multi-agent handoffs, and tools for voice, text-only, transcription, vision, and video-avatar applications. Agents can be tested with native test integration, including event assertions and LLM-based judges, and can run locally in console mode, in development mode with hot reloading, or in production mode. The framework can use LiveKit Cloud or a self-hosted LiveKit server and is distributed as a Python package with plugins for model providers. The Agents framework is licensed under Apache-2.0; LiveKit turn-detection models use the LiveKit Model License.

LibreChat is an open-source, self-hosted AI chat platform that provides a ChatGPT-inspired interface for connecting to major AI providers and custom OpenAI-compatible endpoints. It supports model switching, multimodal file interactions, web search, speech-to-text and text-to-speech, image generation, conversation search, presets, branching, resumable streams, and a sandboxed Code Interpreter for languages including Python, JavaScript/TypeScript, Go, C/C++, Java, PHP, Rust, and Fortran. Its agent system supports no-code custom assistants, community-shared agents, MCP servers, tools, file search, code execution, reusable SKILL.md instruction bundles, subagents, and an Agent Management API. Agents can optionally use attached workspaces to inspect, search, edit, and run commands in bounded environments. The platform also provides generative UI artifacts, including React, HTML, and Mermaid content, plus custom actions and integrations with providers such as Anthropic, AWS Bedrock, OpenAI, Azure OpenAI, Google, Vertex AI, Ollama, Groq, Mistral, OpenRouter, and others. LibreChat includes multi-user authentication through OAuth2, LDAP, and email login; browser-based administration of users, groups, roles, and configuration; role-based permissions; observability through OpenTelemetry and Langfuse; Redis-backed synchronization for scaled deployments; and Docker Compose deployment options. It is built in public and intended for local or cloud self-hosting.