Praison AI

Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralised framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications, emphasizing ease of use, customization, and human-agent interaction.

Different User Interfaces:

Interface	Description	URL
UI	Multi Agents such as CrewAI or AutoGen	https://docs.praison.ai/ui/ui
Chat	Chat with 100+ LLMs, single AI Agent	https://docs.praison.ai/ui/chat
Code	Chat with entire Codebase, single AI Agent	https://docs.praison.ai/ui/code

Other Features	Description	Docs
Train	Fine-tune LLMs using your custom data	https://docs.praison.ai/train

Google Colab Multi Agents

	Cookbook	Open in Colab
Basic	PraisonAI
Include Tools	PraisonAI Tools

Install

	Installation
PraisonAI	pip install praisonai
PraisonAI Code	pip install "praisonai[code]"
PraisonAI Chat	pip install "praisonai[chat]"
PraisonAI Train	pip install "praisonai[train]"

Key Features

• Automated AI Agents Creation
• Use CrewAI or AutoGen Framework
• 100+ LLM Support
• Chat with ENTIRE Codebase
• Interactive UIs
• YAML-based Configuration
• Custom Tool Integration

TL;DR Multi Agents

pip install praisonai
export OPENAI_API_KEY="Enter your API key"
praisonai --init create a movie script about dog in moon
praisonai

Table of Contents

• Installation
• Initialise
• Run
• Full Automatic Mode
• User Interface
• Praison AI Chat
• Create Custom Tools
• Agents Playbook
• Include praisonai package in your project
• Commands to Install Dev Dependencies
• Other Models
• Contributing
• Star History

Installation Multi Agents

pip install praisonai

Initialise

export OPENAI_API_KEY="Enter your API key"

Generate your OPENAI API KEY from here: https://platform.openai.com/api-keys

Note: You can use other providers such as Ollama, Mistral ... etc. Details are provided at the bottom.

praisonai --init create a movie script about dog in moon

This will automatically create agents.yaml file in the current directory.

To initialise with a specific agent framework (Optional):

praisonai --framework autogen --init create movie script about cat in mars

Run

praisonai

or

python -m praisonai

Specify the agent framework (Optional):

praisonai --framework autogen

Full Automatic Mode

praisonai --auto create a movie script about Dog in Moon

User Interface

PraisonAI User Interfaces:

Interface	Description	URL
UI	Multi Agents such as CrewAI or AutoGen	https://docs.praisonai.com/ui/ui
Chat	Chat with 100+ LLMs, single AI Agent	https://docs.praisonai.com/ui/chat
Code	Chat with entire Codebase, single AI Agent	https://docs.praisonai.com/ui/code

pip install -U "praisonai[ui]"
export OPENAI_API_KEY="Enter your API key"
chainlit create-secret
export CHAINLIT_AUTH_SECRET=xxxxxxxx
praisonai ui

or

python -m praisonai ui

Praison AI Chat

• https://docs.praison.ai/chat/

pip install "praisonai[chat]"
export OPENAI_API_KEY="Enter your API key"
praisonai chat

Praison AI Code

pip install "praisonai[code]"
export OPENAI_API_KEY="Enter your API key"
praisonai code

Create Custom Tools

• https://docs.praison.ai/tools/custom/

Agents Playbook

Simple Playbook Example

framework: crewai
topic: Artificial Intelligence
roles:
  screenwriter:
    backstory: "Skilled in crafting scripts with engaging dialogue about {topic}."
    goal: Create scripts from concepts.
    role: Screenwriter
    tasks:
      scriptwriting_task:
        description: "Develop scripts with compelling characters and dialogue about {topic}."
        expected_output: "Complete script ready for production."

Use 100+ Models

• https://docs.praison.ai/models/

Include praisonai package in your project

• https://docs.praison.ai/developers/wrapper
• https://docs.praison.ai/developers/wrapper-tools/

Option 1: Using RAW YAML

from praisonai import PraisonAI

# Example agent_yaml content
agent_yaml = """
framework: "crewai"
topic: "Space Exploration"

roles:
  astronomer:
    role: "Space Researcher"
    goal: "Discover new insights about {topic}"
    backstory: "You are a curious and dedicated astronomer with a passion for unraveling the mysteries of the cosmos."
    tasks:
      investigate_exoplanets:
        description: "Research and compile information about exoplanets discovered in the last decade."
        expected_output: "A summarized report on exoplanet discoveries, including their size, potential habitability, and distance from Earth."
"""

# Create a PraisonAI instance with the agent_yaml content
praisonai = PraisonAI(agent_yaml=agent_yaml)

# Run PraisonAI
result = praisonai.run()

# Print the result
print(result)

Option 2: Using separate agents.yaml file

Note: Please create agents.yaml file before hand.

from praisonai import PraisonAI

def basic(): # Basic Mode
    praisonai = PraisonAI(agent_file="agents.yaml")
    praisonai.run()

if __name__ == "__main__":
    basic()

Commands to Install Dependencies:

1. Install all dependencies, including dev dependencies:

   poetry install

2. Install only documentation dependencies:

   poetry install --with docs

3. Install only test dependencies:

   poetry install --with test

4. Install only dev dependencies:

   poetry install --with dev

This configuration ensures that your development dependencies are correctly categorized and installed as needed.

Contributing

• Fork on GitHub: Use the "Fork" button on the repository page.
• Clone your fork: git clone https://github.com/yourusername/praisonAI.git
• Create a branch: git checkout -b new-feature
• Make changes and commit: git commit -am "Add some feature"
• Push to your fork: git push origin new-feature
• Submit a pull request via GitHub's web interface.
• Await feedback from project maintainers.

Star History

License

Praison AI is an open-sourced software licensed under the MIT license.