PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration.
Project description
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 |
Google Colab Multi Agents
Cookbook | Open in Colab | |
---|---|---|
Basic | PraisonAI | |
Include Tools | PraisonAI Tools |
Install
PraisonAI | PraisonAI Code | PraisonAI Chat |
---|---|---|
pip install praisonai |
pip install "praisonai[code]" |
pip install "praisonai[chat]" |
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
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
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
Include praisonai package in your project
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:
-
Install all dependencies, including dev dependencies:
poetry install
-
Install only documentation dependencies:
poetry install --with docs
-
Install only test dependencies:
poetry install --with test
-
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.
Project details
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