Praison AI
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. It provides a low-code solution to streamline the building and management of multi-agent LLM systems, emphasising simplicity, customisation, and effective human-agent collaboration.
Why PraisonAI?
Your machine, cloud, or edge. Self-hosted with full control over your data.
100+ LLM ModelsOpenAI, Anthropic, Google, Ollama, Groq — seamlessly switch between any provider.
Memory & KnowledgePersistent memory, RAG knowledge bases, and context-aware conversations.
Self-ReflectionAgents that evaluate and improve their own responses for higher accuracy.
140+ Built-in ToolsWeb search, file operations, databases, APIs — all ready to use out of the box.
Multi-Agent WorkflowsSequential, parallel, hierarchical orchestration with autonomous coordination.
Differentiators
🧠 Self-Reflection & Reasoning
Unlike simple chatbots, PraisonAI agents can reflect on their outputs and iteratively improve them. Built-in reasoning capabilities enable multi-step problem solving without manual prompting.
from praisonaiagents import Agent, ReflectionConfig
# Simple reflection
agent = Agent(
name="analyst",
instructions="You analyze data carefully.",
reflection=True # Enable self-correction
)
# Advanced reflection with custom iterations
agent = Agent(
name="analyst",
instructions="You analyze data carefully.",
reflection=ReflectionConfig(max_iterations=3)
)💾 Persistent Memory
Agents remember past interactions across sessions. Short-term, long-term, and episodic memory systems keep context without re-prompting.
from praisonaiagents import Agent, MemoryConfig
agent = Agent(
name="assistant",
memory=MemoryConfig(
backend="file",
user_id="user_123"
)
)📚 Knowledge Bases (RAG)
Connect agents to your documents, databases, and APIs. Built-in RAG with auto-chunking, embeddings, and semantic search.
from praisonaiagents import Agent
agent = Agent(
name="researcher",
knowledge=[ # Multiple knowledge sources
"./docs/",
"notes.txt", # arbitrary web URLs aren't ingested; fetch web pages first
"s3://my-bucket/handbook.pdf", # cloud storage URIs are downloaded automatically
"./pdfs/"
]
)🌐 Browser Control
Agents can navigate websites, fill forms, click buttons, and extract data — fully automated browser automation.
agent = Agent(
name="web_agent",
tools=["browser_tool"], # Built-in browser
llm="gpt-4o"
)
agent.run("Book a flight from NYC to LA for next Tuesday")💬 11+ Messaging Platforms
Deploy agents to Slack, Discord, Telegram, WhatsApp, Signal, LINE, iMessage, and more — with a single command.
praisonai bot slack --token $SLACK_BOT_TOKEN --app-token $SLACK_APP_TOKEN🔌 Extensible Plugins
Write custom tools in Python or use any of the 140+ pre-built integrations. MCP protocol support for external tool servers.
from praisonaiagents import Agent
def custom_tool(query: str) -> str:
"""My custom tool description."""
return f"Result for {query}"
agent = Agent(tools=[custom_tool])Quick Start
No Code
- Install
bash pip install praisonai - Set API Key
bash export OPENAI_API_KEY=sk-xxx - Run
bash praisonai --auto "Research the top 5 AI trends in 2025 and create a report"That’s it! Agents are automatically created and orchestrated.
Python SDK
- Install
bash pip install praisonaiagents - Create Agent
python from praisonaiagents import Agent agent = Agent( name="researcher", instructions="You are a research analyst specializing in AI trends.", llm="gpt-4o" ) result = agent.start("What are the top AI trends for 2025?") print(result)
Multi-Agent
from praisonaiagents import Agent, Task, AgentTeam
# Create specialized agents
researcher = Agent(
name="Researcher",
role="Research Analyst",
goal="Find accurate, up-to-date information",
llm="gpt-4o"
)
writer = Agent(
name="Writer",
role="Content Writer",
goal="Create engaging, clear content",
llm="gpt-4o"
)
# Define tasks
research_task = Task(
name="research",
description="Research AI trends for 2025",
agent=researcher
)
write_task = Task(
name="write",
description="Write a blog post based on the research",
agent=writer
)
# Orchestrate
agents = AgentTeam(
agents=[researcher, writer],
tasks=[research_task, write_task],
process="sequential"
)
result = agents.start()Platform Integrations
Deploy AI bots to Slack workspaces
DiscordCreate Discord bots with agent intelligence
TelegramBuild Telegram bots in minutes
WhatsAppSend messages via WhatsApp Business
Automate repos, issues, and PRs
GoogleCalendar, Sheets, Drive, Gmail
NotionRead and write Notion pages
JiraManage Jira issues and projects
CLI Commands
Full-featured CLI for deploying and managing AI agents:
Messaging Bots
# Start a Telegram bot
praisonai bot telegram --token $TELEGRAM_BOT_TOKEN
# Slack with full capabilities
praisonai bot slack --token $SLACK_BOT_TOKEN --app-token $SLACK_APP_TOKEN \
--agent agents.yaml --browser --web --memory
# Discord with custom tools
praisonai bot discord --token $DISCORD_BOT_TOKEN \
--tools DuckDuckGoTool WikipediaToolBrowser Control
# Navigate and interact with websites
praisonai browser navigate https://example.com
praisonai browser run "Click the submit button"
praisonai browser screenshot --output page.png
praisonai browser doctorSkills & Plugins
# Manage skills
praisonai skills list
praisonai skills check --verbose
praisonai skills create --name csv-analyzer --description "Analyze CSV" --script
# Manage plugins
praisonai plugins list --enabled
praisonai plugins doctorSandbox
# Contain every agent shell command
PRAISON_SHELL=sandboxed praisonai code
praisonai sandbox status
praisonai sandbox explain --agent workDeploy messaging bots
Browser CLIBrowser automation
Skills CLIManage agent skills
Plugins CLIPlugin management
Architecture
Use Cases
Build intelligent support agents that resolve issues autonomously, escalate when needed, and learn from interactions.
Research & AnalysisCreate agents that gather data, analyze trends, and produce detailed reports with citations.
Content CreationDeploy agents that research, write, edit, and optimize content across formats — blogs, docs, social media.
Process AutomationAutomate complex workflows with multi-agent coordination — from data pipelines to deployment.
Code GenerationAgents that understand your codebase, write tests, fix bugs, and implement features.
Personal AssistantBuild assistants that manage calendars, emails, reminders, and integrate with your tools.
Explore
Create and configure intelligent agents
Tools140+ built-in tools and integrations
MemoryPersistent memory and knowledge bases
MCPModel Context Protocol integrations
Messaging BotsSlack, Discord, Telegram, and more
API ReferenceFull SDK documentation