CrewAI
Multi-agent automation framework & studio to build and run AI crews
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Build, coordinate, and run multi‑AI agents with low‑code simplicity
PraisonAI provides a production‑ready framework for creating, managing, and orchestrating multiple LLM agents, featuring self‑reflection, memory, tool integration, and both code‑first and no‑code interfaces.
PraisonAI is a production‑ready framework that lets developers and AI teams build, manage, and orchestrate multiple large‑language‑model agents. It emphasizes low‑code simplicity while supporting advanced capabilities such as self‑reflection, short‑ and long‑term memory, and multimodal reasoning.
The library ships as a Python package (praisonaiagents) and a JavaScript SDK (praisonai), with a CLI for no‑code usage. Agents can be defined programmatically, via YAML configuration, or auto‑generated with the --auto flag. Integrated tools exceed 100 custom utilities, including code execution, web search, PDF handling, and RAG pipelines. Compatibility with over 100 LLM providers and LangChain ensures flexible model selection.
Install with pip install praisonaiagents or npm install praisonai, set your OPENAI_API_KEY, and launch single or multi‑agent workflows in minutes. Whether you need a research summarizer, a code‑interpreter, or a memory‑enabled chatbot, PraisonAI streamlines the end‑to‑end development cycle.
When teams consider PraisonAI, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Automated research summarization
Agents research a topic, summarize findings, and produce a concise report without manual intervention.
Code generation and execution
A code‑interpreter agent writes, runs, and validates Python scripts based on user prompts.
Customer support chatbot with memory
Multi‑agent system retains conversation context across sessions, providing personalized assistance.
Document analysis with RAG
Agents ingest PDFs, retrieve relevant passages, and answer questions using vector store integration.
PraisonAI offers SDKs for Python (pip) and JavaScript/Node.js (npm), plus a CLI for no‑code usage.
An API key is required for OpenAI models and many hosted LLMs; other providers can be configured via LangChain.
Workflows can be described in code using the PraisonAIAgents class, via YAML configuration files, or generated automatically with the CLI’s --auto flag.
Yes, the framework includes over 100 built‑in tools and allows custom tool integration for actions like web search, code execution, and formatting.
Agents provide short‑term and long‑term memory options, optionally backed by vector databases for persistent context.
Project at a glance
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