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Installation

Interface Types

Features

Getting Started

To Change Username and Password

Chainlit

Using Chainlit (with Pictures)

Install Required Package

User Interface

Select Auto Mode

Configure Agent Settings

Define a Task to Auto Generate Agents and Run

Output

Run Automatically

Select Manual Mode

Modify Agents and Tools

Run Manually

Run Agents

Manual Model Output

Review Generated Agents

PraisonAI Documentation

Agents

Tools

Deploy

Examples

Course

Community

Interface to Build multi-agent systems with PraisonAI Agent's framework

PraisonAI is a production-ready Multi-AI Agents framework with self-reflection, designed to create AI Agents to automate and solve problems ranging from simple tasks to complex challenges. By integrating PraisonAI Agents, AG2 (Formerly AutoGen), and CrewAI into a low-code solution, it streamlines the building and management of multi-agent LLM systems, emphasising simplicity, customisation, and effective human-agent collaboration.

Home

Praison AI

Welcome to PraisonAI - The Next Generation AI Agent Framework

Introduction

Set up PraisonAI in your development environment

Create AI Agents and make them work for you in just a few lines of code.

Quick Start

Tasks

Process

Learn how to create AI agents that can use tools to interact with external systems and perform actions.

AI Agents with Tools

Learn how to create AI agents with memory capabilities for maintaining context and information across tasks.

Memory

AI Agents with Memory

Learn how to create AI agents with custom knowledge bases

Knowledge

AI Agents with Knowledge

Learn how to create AI agents that can dynamically route tasks to specialized LLM instances.

Agentic Routing

Learn how to create AI agents that orchestrate and distribute tasks among specialized workers.

Orchestrator Worker

Agentic Orchestrator Worker

Learn how to create AI agents that can autonomously monitor, act, and adapt based on environment feedback.

Autonomous Workflow

Agentic Autonomous Workflow

Learn how to create AI agents that can execute tasks in parallel for improved performance.

Parallelization

Agentic Parallelization

Learn how to create AI agents with sequential prompt chaining for complex workflows.

Prompt Chaining

Agentic Prompt Chaining

Learn how to create AI agents that can generate and optimize solutions through iterative feedback.

Evaluator Optimizer

Agentic Evaluator Optimizer

Learn how to create AI agents that can efficiently handle repetitive tasks through automated loops.

Repetitive Agents

Use PraisonAI directly from your terminal with simple commands

Command Line Interface

AutoAgents automatically creates and manages AI agents and tasks based on high-level instructions.

AutoAgents

Generate high-quality images using PraisonAI Image Agents with both synchronous and asynchronous capabilities.

Image Generation

Image Generation AI Agents

Self-reflection enables agents to evaluate and improve their own responses before delivering them.

Self Reflection Agents

Self Reflection AI Agents

Learn how to create AI agents that can efficiently interact with vector databases for knowledge retrieval and storage.

RAG Agents

Learn how to create AI agents that can perform step-by-step reasoning and extract information

Reasoning Extract Agents

Learn how to create AI agents with advanced reasoning capabilities for complex problem-solving.

Reasoning Agents

Guide for creating and using multimodal AI agents in PraisonAI for processing images, videos, and other media types

Multimodal Agents

Learn how to use LangChain tools and utilities with PraisonAI agents.

LangChain Agents

Async AI Agents allow you to run AI tasks asynchronously, improving performance and efficiency in your applications.

Async Agents

Learn how to create simple yet powerful AI agents in just a few lines of code.

Mini AI Agents

Learn how to generate chain-of-thought reasoning data using PraisonAI Agents.

Generate Reasoning Data

Generate Synthetic Reasoning Data Agents

Learn how to create AI agents that can write and execute Python code safely using e2b code interpreter.

Code Agent

Code Execution AI Agent

Learn how to create AI agents that can perform complex mathematical calculations, unit conversions, and financial computations.

Math Agent

Math AI Agent

Learn how to create AI agents that return structured, type-safe outputs using Pydantic models and JSON.

Structured AI Agents

Learn how to implement callbacks to monitor and log AI agent interactions, errors, and task completions.

Callbacks Agent

AI Agents with Callbacks

Learn how to create AI agents that can intelligently chat with PDF documents using vector databases for efficient information retrieval.

Chat with PDF

Chat with PDF Agents

Overview of supported language models in PraisonAI, including OpenAI, Groq, Google Gemini, Anthropic Claude, and configuration examples

Models in PraisonAI

Guide for integrating OpenAI's ChatGPT models with PraisonAI, including configuration for both single and multi-agent setups

OpenAI ChatGPT

Instructions for integrating Ollama's open-source language models with PraisonAI, including configuration and usage examples

Ollama

Guide for integrating Groq's high-performance language models with PraisonAI, including API setup and configuration

Groq

Instructions for integrating Google's Gemini models with PraisonAI, including API setup and configuration details

Google Gemini

Google Gemini Agents

Guide for integrating OpenRouter's unified API access to various language models with PraisonAI, including setup and configuration

OpenRouter

Instructions for integrating Anthropic's Claude models with PraisonAI, including API setup and agent configuration

Anthropic

Guide for integrating Cohere's language models with PraisonAI, including API setup and configuration examples

Cohere

Guide for integrating Mistral AI's language models with PraisonAI, including API configuration and usage instructions

Mistral

Learn how to use Deepseek models with PraisonAI Agents for various applications.

DeepSeek Agents

Configuration examples for various other language models with PraisonAI, including Ollama, FastChat, LM Studio, and Mistral API

Other Models

Welcome to the beginner's course on AI Agents

Introduction to AI Agents

Understanding the different categories of AI agents

Types of AI Agents

Understanding how AI agents are structured

Agent Architecture

How to write clear instructions for your AI agents

Creating Effective Agent Instructions

Understanding how tools extend agent capabilities

Agent Tools

Understanding how agents maintain context and learn

Agent Memory

Multi-Agent Systems

Understanding agent workflows and processes

Agent Process

Enhancing agents with specialized knowledge

Knowledge Bases

Understanding how agents handle and manage tasks

Agent Tasks

A step-by-step guide to building your first AI agent

Creating Your First Agent

Enhancing your agents with specialized capabilities

Adding Tools to Agents

Creating a system with multiple cooperative agents

Building a Multi-Agent System

Creating agents that maintain context in conversations

Building Conversational Agents

Creating agents that can gather and analyze information

Building Research Agents

Building agents that generate various types of content

Content Creation Agents

Creating agents that analyze and interpret data

Data Analysis Agents

Building agents that handle customer inquiries and issues

Customer Support Agents

Building agents that help with personal tasks and productivity

Personal Assistant Agents

How to deploy and share your AI agents with others

Deploying Agents

Explore real-world examples and use cases built with PraisonAI Agents.

Learn how to create AI agents for comprehensive code analysis and quality assessment.

Code Analysis Agent

Learn how to create AI agents for evaluating hackathon projects through video demonstrations.

Hackathon Judge Agent

Learn how to create AI agents for predictive maintenance and equipment monitoring.

Predictive Maintenance

Learn how to create AI agents for coordinated emergency response and resource management.

Emergency Response

Learn how to create AI agents for automated code review and issue resolution.

Code Review

Learn how to create AI agents for real-time fraud detection and alert management.

Fraud Detection

Learn how to create AI agents for supply chain risk management and mitigation.

Supply Chain

Learn how to create AI agents for automated medical diagnosis and treatment recommendations.

Healthcare Diagnosis

Customer Service

Learn how to create AI agents for smart city resource management and optimization.

Smart City

Learn how to create AI agents for multilingual content generation and cultural adaptation.

Multilingual Content

Learn how to create AI agents for personalized adaptive learning experiences.

Adaptive Learning

Learn how to create AI agents for post-quantum cryptographic scheme validation and security analysis.

Crypto Validator

Learn how to create AI agents for space mission planning and resource optimization.

Space Mission

Learn how to create AI agents for neural architecture search and optimization.

Neural Architecture

Learn how to create AI agents for decentralized finance market making and arbitrage.

User Interface

​Installation

​Interface Types

Multi-Agent Systems

​Features

​Getting Started

​Chainlit

​To Change Username and Password

​Using Chainlit (with Pictures)

​Run Automatically

​Install Required Package

​User Interface

​Select Auto Mode

​Configure Agent Settings

​Define a Task to Auto Generate Agents and Run

​Output

​Run Manually

​Select Manual Mode

​Modify Agents and Tools

​Review Generated Agents

​Run Agents

​Manual Model Output

Installation

Interface Types

Features

Getting Started

Chainlit

To Change Username and Password

Using Chainlit (with Pictures)

Run Automatically

Install Required Package

User Interface

Select Auto Mode

Configure Agent Settings

Define a Task to Auto Generate Agents and Run

Output

Run Manually

Select Manual Mode

Modify Agents and Tools

Review Generated Agents

Run Agents

Manual Model Output