AI Agents
ruby_llm
The Ruby-native AI framework. Chats, agents, tools, images, audio, and video through one consistent API, in plain Ruby or Rails.
★ 4.4k starsMIT
View guide →An open-source platform for AI-native application development — assistants, tools, RAG and models in one API.
TaskingAI is an open-source ai agents project by TaskingAI (TaskingAI/TaskingAI on GitHub). It has 5,410 GitHub stars and 359 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 2 December 2024.
Decide what your application needs — chat with memory, tool use, retrieval over your data, or all three.
Clone the repo and start the Docker deployment with your .env configuration.
In the console or API, register your language models, tools and retrieval collections.
Create an assistant from your modules, open a chat through the SDK, and send your first message.
Models, tools and RAG systems are managed independently of assistants and can be freely combined and swapped.
Supports managed conversation history and sessions, or simple stateless chat-completion requests.
Designed for fast deployment into multi-tenant products, unlike single-assistant frameworks tied to one vendor.
One API surface manages tools, retrieval systems, language models and assistants.
A web UI console for configuration plus a Python SDK for creating assistants, chats and messages programmatically.
Not restricted to one vendor's models, addressing the proprietary limitations the project calls out in alternatives.
Clone TaskingAI and enter the Docker deployment directory.
git clone https://github.com/TaskingAI/TaskingAI.git
cd TaskingAICopy the example environment file, adjust it, and start the platform.
cd docker
cp .env.example .env
docker-compose -p taskingai --env-file .env up -dInstall the Python client to create assistants and chats against your deployment.
pip install taskingaiTaskingAI is maintained by the TaskingAI team, with the product site at tasking.ai.
Yes — it is open source under the Apache-2.0 license for self-hosting.
You register your own language models with the platform, so you need credentials for whichever model providers you choose.
TaskingAI positions itself against vendor-tied assistants: it is vendor-neutral, supports stateful and stateless use, decouples tools/RAG/models from assistants, and supports multi-tenant deployment.
Clone the repo, start the Docker Compose deployment, open the console, and create your first assistant.
The Ruby-native AI framework. Chats, agents, tools, images, audio, and video through one consistent API, in plain Ruby or Rails.
One RAG framework for everything — including multimodal documents.
Production-ready agentic RAG behind a clean REST API.
An open agent framework with a native terminal TUI, ReAct and Agent Team modes — one command to run.
Open-source AI-driven development platform: autonomous software agents in a sandbox
A visual all-in-one platform for building, debugging, and deploying AI agents.
The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if TaskingAI is not the right fit.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Free and open — grab the source, star the repo, and start creating.