Install PraisonAI, set one provider key, and run an Agent in your own app.

from praisonaiagents import Agent

agent = Agent(instructions="Be helpful")
agent.start("Summarise the top AI news today")

pip install "praisonai-bot[gateway,bot]"

pip install praisonai

pip install praisonai-code

pip install praisonaiagents

npm install praisonai

curl -fsSL https://praison.ai/install.sh | bash

Four packages, one ecosystem. pip install praisonai pulls code, bot, and SDK. Lighter options below.

Terminal-only (smaller)

pip install praisonai-code — agentic CLI without gateway or bots

Bots + gateway only

pip install "praisonai-bot[gateway,bot]" — channel runtime without the wrapper

Full (default)

pip install praisonai — wrapper, code, bot, and SDK together

pip install praisonai transitively installs praisonai-code, praisonai-bot, and praisonaiagents. You do not need to install them separately.

Installing PraisonAI

PraisonAI is published as four PyPI packages. Pick the one that matches what you want to do:

The complete package — CLI, gateway, bots, integrations, YAML-driven multi-bot orchestration. Pulls praisonai-code and praisonaiagents automatically.

For gateway hot reload (event-driven gateway.yaml watching via watchdog), install the gateway extra: pip install "praisonai[gateway]".[claw] extra: pip install "praisonai[claw]" installs the full wrapper plus praisonai-bot[gateway,bot] — the WebSocket gateway and Telegram/Discord/Slack channel bots. Use this when you want the full wrapper and all channel runtime features in one command. For gateway + bots without the wrapper, use pip install "praisonai-bot[gateway,bot]" directly (see Standalone Bot Gateway).

Create Virtual Environment (Optional)

python -m venv praisonai-env
source praisonai-env/bin/activate

python -m venv praisonai-env
.\praisonai-env\Scripts\activate

Install

Terminal

pip install praisonai

Configure Environment

Set your API key. PraisonAI auto-detects whichever provider credential is present:

OpenAI

export OPENAI_API_KEY="${OPENAI_API_KEY:?Set OPENAI_API_KEY in your shell}"

Anthropic

export ANTHROPIC_API_KEY="${ANTHROPIC_API_KEY:?Set ANTHROPIC_API_KEY in your shell}"

Gemini

export GEMINI_API_KEY="${GEMINI_API_KEY:?Set GEMINI_API_KEY in your shell}"

Groq

export GROQ_API_KEY="${GROQ_API_KEY:?Set GROQ_API_KEY in your shell}"

Ollama

export OLLAMA_HOST=http://localhost:11434

If you only set ANTHROPIC_API_KEY (or GEMINI_API_KEY, GOOGLE_API_KEY, GROQ_API_KEY, COHERE_API_KEY, or OLLAMA_HOST), praisonai run picks the matching provider’s default model automatically — no --model flag required. See Provider Auto-Detection for the full lookup table.

The standalone agent runtime — run, chat, code, and the full CLI backend, without the gateway/bot integrations. Depends only on praisonaiagents.

Create Virtual Environment (Optional)

python -m venv praisonai-env
source praisonai-env/bin/activate

python -m venv praisonai-env
.\praisonai-env\Scripts\activate

Install

Terminal

pip install praisonai-code

Configure Environment

export OPENAI_API_KEY="${OPENAI_API_KEY:?Set OPENAI_API_KEY in your shell}"

Any supported provider key works. See Provider Auto-Detection.

Run an agent

from praisonaiagents import Agent

agent = Agent(name="assistant", instructions="Be helpful")
response = agent.start("Summarise the top AI news today")
print(response)

Standalone bots and gateway — no full wrapper. Depends on praisonaiagents only at PyPI level.

Install

Terminal

pip install "praisonai-bot[gateway,bot]"

Configure Environment

export OPENAI_API_KEY="${OPENAI_API_KEY:?Set OPENAI_API_KEY in your shell}"
export TELEGRAM_BOT_TOKEN="${TELEGRAM_BOT_TOKEN:?Set TELEGRAM_BOT_TOKEN in your shell}"

Start gateway

Terminal

praisonai-bot gateway start --host 127.0.0.1 --port 8765

See the praisonai-bot SDK page for Python API details.

The pure Python SDK — no CLI, no gateway, no heavy dependencies. Import directly in your own application.

Create Virtual Environment (Optional)

python -m venv praisonai-env
source praisonai-env/bin/activate

python -m venv praisonai-env
.\praisonai-env\Scripts\activate

Install

Terminal

pip install praisonaiagents

Configure Environment

export OPENAI_API_KEY="${OPENAI_API_KEY:?Set OPENAI_API_KEY in your shell}"

Use in your app

from praisonaiagents import Agent

agent = Agent(name="assistant", instructions="Be helpful")
response = agent.start("Hello!")
print(response)

Create Virtual Environment (Optional)

python -m venv praisonai-env
source praisonai-env/bin/activate

python -m venv praisonai-env
.\praisonai-env\Scripts\activate

Install PraisonAI

pip install praisonai

Set API Key

Set your API key for the provider you want to use. PraisonAI auto-detects whichever credential is present:

export OPENAI_API_KEY="${OPENAI_API_KEY:?Set OPENAI_API_KEY in your shell}"

Use Anthropic, Gemini, Groq, or Ollama instead? Just set that provider’s key and praisonai run picks the right model automatically. See Provider Auto-Detection.

Install PraisonAI

npm install praisonai

Set API Key

export OPENAI_API_KEY="${OPENAI_API_KEY:?Set OPENAI_API_KEY in your shell}"

Install PraisonAI

npm install praisonai

Set API Key

export OPENAI_API_KEY="${OPENAI_API_KEY:?Set OPENAI_API_KEY in your shell}"

All existing praisonai CLI verbs (run, chat, code, gateway, bot, …) continue to work unchanged — the wrapper routes them through the praisonai-code runtime. You do not need to change any scripts.

Package dependency chain

Each layer depends on the one to its left. Installing praisonai pulls all three; installing praisonai-code pulls only praisonaiagents; installing praisonaiagents has no PraisonAI dependencies. Generate your OpenAI API key from OpenAI You can also use other LLM providers like Anthropic, Google, etc. Please refer to the Models for more information.

Which Install Do You Need?

Terminal-only (smaller)

pip install praisonai-code — agentic CLI: run, chat, code, runtime. No bots or gateway.

Full (default)

pip install praisonai — everything: bots, gateway, kanban, dashboard, and the agentic CLI.

pip install praisonai transitively installs praisonai-code and praisonaiagents. You do not need to install them separately.

How It Works

Pip installs the package, you export one provider key, and the CLI or SDK resolves the matching model at run time.

Best Practices

Install only what you need

Use praisonaiagents for a pure Python SDK, praisonai-code for the terminal runtime, and praisonai for the full wrapper with bots and gateway.

Use a virtual environment

Create a venv before installing to keep PraisonAI isolated from your system Python.

Export keys, don't hard-code them

Set OPENAI_API_KEY (or your provider’s key) in your shell or .env. Never inline the raw value in code.

Skip --model on first runs

PraisonAI auto-detects the provider from whichever key is present and picks a sensible default model.

Quick Start

Build your first AI agent.

Models

Choose a provider and model.

Quick Install

The one-liner installer uses an isolated backend (uv tool → pipx → venv fallback) and exposes praisonai via a ~/.local/bin/praisonai shim — your global Python environment is untouched. See Isolation Backends for details.

macOS/Linux
Windows

curl -fsSL https://praison.ai/install.sh | bash

iwr -useb https://praison.ai/install.ps1 | iex

Windows terminals: PraisonAI automatically detects legacy Windows code pages (CP1252, CP850, etc.) and falls back to ASCII-safe output. For full emoji and box-drawing rendering, switch your terminal to UTF-8:

$env:PYTHONIOENCODING='utf-8'
chcp 65001

set PYTHONIOENCODING=utf-8
chcp 65001

The installer automatically detects your OS, picks the best isolation backend (uv tool → pipx → venv fallback), installs Python if needed, and drops a ~/.local/bin/praisonai shim on your PATH.

Requirements

Python 3.10 or higher (auto-installed if missing)
macOS, Linux, or Windows

Package Structure

PraisonAI ships as three separate PyPI packages. Understanding which to install avoids surprises at runtime.

Install command	What you get	Agentic CLI (`run`, `chat`, `code`, …)	Bot / gateway / pairing
`pip install praisonai`	Wrapper + code + agents	✅ Full	✅ Yes
`pip install praisonai-code`	Terminal-native agent CLI + LLM runtime	✅ `run --output actions`, `daemon`, `doctor`, `config`, `version` — `chat`/`code`/default `run` need the wrapper	❌ No — needs `pip install praisonai`
`pip install praisonaiagents`	Core SDK — Python API only	❌ No CLI	N/A

Standalone pip install praisonai-code supports the actions/daemon path as of PraisonAI 4.6.123+ (C7 + C9 four-tier). Use praisonai-code run --output actions "your prompt" for the standalone in-process Agent path, and praisonai-code daemon start --background (spawns python -m praisonai_code.runtime) for the warm runtime. run --help, config, doctor, and version also work standalone.

Default run "prompt", chat, and code require the wrapper (pip install praisonai) and print a clear install hint if invoked standalone (for example, Error: chat requires the praisonai wrapper. Install the full wrapper: pip install praisonai). Wrapper-only features (bot, claw, dashboard, gateway, identity, kanban, onboard, pairing, framework adapters, YAML --framework crewai/autogen) also require pip install praisonai — they degrade gracefully rather than raising raw import errors. See Standalone LLM Modules and the praisonai-code CLI.

PyPI publish order

Packages are published in dependency order:

1. praisonaiagents  →  2. praisonai-code  →  3. praisonai

If you pin versions, ensure all three packages resolve to the same release cycle. Since 4.6.104, praisonai pins praisonai-code>=0.0.2, so pip install praisonai always pulls a compatible runtime automatically. See praisonaiagents SDK page for the release-cycle notes.

Terminal-only (smaller)

Bots + gateway only

Full (default)

​Installing PraisonAI

​Package dependency chain

​Which Install Do You Need?

Terminal-only (smaller)

Full (default)

​How It Works

​Best Practices

​Related

Quick Start

Models

​Quick Install

​Package Structure

​PyPI publish order

Installing PraisonAI

Package dependency chain

Which Install Do You Need?

How It Works

Best Practices

Related

Quick Install

Package Structure

PyPI publish order