PraisonAI

PraisonAI is an open-source Python framework for building autonomous AI agents. It lets a developer give an agent a goal and have it research, plan, code and execute tasks with built-in memory, retrieval-augmented generation and support for over 100 LLMs, deployed in as few as 5 lines of code. It is built for developers who want to move from a single agent to a full multi-agent workforce.

A developer installs the praisonaiagents SDK, sets an API key, and creates an Agent with instructions or a role and a goal. Agents can be given memory, knowledge sources and tools, and multiple agents can be linked into a graph with routing, parallel steps and repeated review loops through the AgentFlow component, expressible in Python or YAML.

PraisonAI structures an agent across five layers: prompt, context, tool-use harness, iteration loop and multi-agent graph, with explicit iteration caps, budget ceilings and doom-loop detection enabled by default. A human-approval gate can be required before risky tool calls run, and a sub-agent handoff passes only the recent context and relevant tools rather than the full transcript.

PraisonAI's tools or a whole agent can run in managed sandboxes such as Docker, e2b, Modal, Daytona or Fly.io instead of the local machine. Beyond the core SDK, a praisonai CLI serves terminal-based developers, and a Claw Dashboard connects agents directly to Telegram, Slack or Discord. The project is released under the MIT license.

Use cases

• Conducting deep research and generating insights from multiple sources
• Writing, debugging and refactoring code with an agent that understands a codebase
• Deploying 24/7 support bots on Telegram, Discord or Slack