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PraisonAI
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PraisonAI

Active·★ 9.3k·MIT·Updated 2026-10-22
★ Essential★ Trending

PraisonAI describes itself as a production-ready multi-AI-agents framework with self-reflection, offering a low-code way to create agents that automate tasks from simple to complex. It ships as a Python SDK (`pip install praisonaiagents` for the core, `pip install praisonai` for the full package), a JavaScript SDK (`npm install praisonai`) and a no-code CLI, with a one-minute quick start to a first agent.

The feature tables cover single, multi and auto-generated agents, self-reflection, reasoning and multimodal agents, and workflow patterns such as routing, parallel execution, looping over a list or CSV, an evaluator-optimiser repeat loop, conditional steps, branching and early stop. The Python examples also include planning mode, deep research and query-rewriter agents, zero-dependency agent memory, auto-generated memories, hooks, shadow git checkpoints, background tasks, a policy engine, thinking budgets, context compaction, and the MCP and A2A (agent-to-agent) protocols. Many model providers are supported. A performance table in the README claims the fastest agent instantiation time among the frameworks it tests; it is the project's own benchmark, and the repository is MIT licensed.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-17.

License
MIT
Latest release
v4.7.15 · 2026-10-16
Last commit
2026-10-17
Contributors
94
Forks
1,480
Open issues and PRs
108
First published
2024-03-19
PyPI package
PraisonAI 4.7.15 · 2,891 downloads last week

Source: GitHub, npm and PyPI public APIs.

#AI Agents#LLM Orchestration#Self-Reflection#Low-Code#Python#Coding
$ Install
$ pip install praisonai
↗ Visit site★ GitHub
01

Features

01Single & Multi-Agent Systems
02Self-Reflection & Reasoning Capabilities
03Advanced Workflows (Routing, Parallel, Conditional)
04Memory & Knowledge Management (RAG)
05Deep Research & Web Search Integration
02

Why choose it

+Covers a lot in one framework: multi-agent teams, workflow patterns (routing, parallel, loop, evaluator-optimiser), memory and planning.
+Python SDK, JavaScript SDK and a no-code CLI, with a quick start that reaches a first agent in about a minute.
+Supports the MCP and A2A protocols, many model providers, and features such as hooks, checkpoints and a policy engine.
+MIT licensed and updated daily.
03

Trade-offs

!The README's benchmark (3.77 microseconds to instantiate an agent versus thousands for LangGraph or CrewAI) measures only startup time and is the project's own test, so it says little about real-world task quality.
!The README is very long, with dozens of features and examples, which makes it harder to see what is core and what is optional.
!It splits across several packages (praisonaiagents, praisonai, and a JavaScript one), so you need to pick the right one.
04

Maintenance check

ActiveChecked: 2026-10-22
Last commit
2026-10-20
Commits, last 90 days
100+
Releases, last 90 days
26
Latest release
v4.7.16 (2026-10-19)
Open issues
139
Recent issues with at least one comment
5/21
Commits per week, last 12 weeks
Commits per week, last 12 weeks: 532, 461, 662, 954, 435, 475, 184, 128, 367, 350, 242, 64

Oldest week on the left; the latest four weeks are orange. Source: GitHub commit activity.

Status rule: archived on GitHub = Archived; last commit within 90 days = Active; 91 to 365 days = Slowing; older = Stale. All figures come from the GitHub API on the date shown.

Most discussed open issues

  • #603 wp20 comments · 2025-06-04
  • #821 autogen to ag2 conversion12 comments · 2025-07-11
  • #738 Review existing features11 comments · 2025-07-07
  • #737 Review code base11 comments · 2025-07-07
  • #820 review crewai implementation9 comments · 2025-07-11

Issue titles are quoted from GitHub. Open the link to check whether a problem still applies to the version you use.

05

Compatibility

OpenAI
Native
Verified via docs
Claude
Supported
Verified via docs
Gemini
Supported
Verified via docs
Groq
Supported
Verified via docs
Ollama
Supported
Verified via docs
LangChain
Integrated
Verified via docs
06

Quick start

1
$ pip install praisonai
07

Use cases

↳Automating complex tasks and multi-step workflows
↳Performing deep research and leveraging external knowledge
↳Developing specialized AI agents for various domains (e.g., finance, data analysis, programming)
08

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On this page
01Features02Why choose it03Trade-offs04Maintenance check05Compatibility06Quick start07Use cases08Alternatives
MervinPraison /
PraisonAI
↗

Low-code multi-agent framework with workflows, memory and MCP and A2A support

9.3k1.5kMIT
Last commit1d ago
StatusActive
CategoryMulti-Agent
Contributors94
Latest releasev4.7.15
Links
Documentation↗Discussion↗Issues↗Releases↗
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