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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, customisation, and efficient human-agent collaboration.

Home Page: https://docs.praison.ai

License: MIT License

Shell 1.16% Python 84.60% Dockerfile 0.13% Jupyter Notebook 14.12%

praisonai's Introduction

PraisonAI Logo

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.

TL;DR

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

Installation

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 initialse 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

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

Create Custom Tools

TL;DR to Create a Custom Tool

pip install praisonai duckduckgo-search
export OPENAI_API_KEY="Enter your API key"
praisonai --init research about the latest AI News and prepare a detailed report
  • Add - InternetSearchTool in the agents.yaml file in the tools section.
  • Create a file called tools.py and add this code tools.py
praisonai

Pre-requisite to Create a Custom Tool

agents.yaml file should be present in the current directory.

If it doesn't exist, create it by running the command praisonai --init research about the latest AI News and prepare a detailed report.

Step 1 to Create a Custom Tool

Create a file called tools.py in the same directory as the agents.yaml file.

# example tools.py
from duckduckgo_search import DDGS
from praisonai_tools import BaseTool

class InternetSearchTool(BaseTool):
    name: str = "InternetSearchTool"
    description: str = "Search Internet for relevant information based on a query or latest news"

    def _run(self, query: str):
        ddgs = DDGS()
        results = ddgs.text(keywords=query, region='wt-wt', safesearch='moderate', max_results=5)
        return results

Step 2 to Create a Custom Tool

Add the tool to the agents.yaml file as show below under the tools section - InternetSearchTool.

framework: crewai
topic: research about the latest AI News and prepare a detailed report
roles:
  research_analyst:
    backstory: Experienced in gathering and analyzing data related to AI news trends.
    goal: Analyze AI News trends
    role: Research Analyst
    tasks:
      gather_data:
        description: Conduct in-depth research on the latest AI News trends from reputable
          sources.
        expected_output: Comprehensive report on current AI News trends.
    tools:
    - InternetSearchTool

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.'

Include praisonai package in your project

from praisonai import PraisonAI

def basic(): # Basic Mode
    praison_ai = PraisonAI(agent_file="agents.yaml")
    praison_ai.main()
    
def advanced(): # Advanced Mode with options
    praison_ai = PraisonAI(
        agent_file="agents.yaml",
        framework="autogen",
    )
    praison_ai.main()
    
def auto(): # Full Automatic Mode
    praison_ai = PraisonAI(
        auto="Create a movie script about car in mars",
        framework="autogen"
    )
    print(praison_ai.framework)
    praison_ai.main()

if __name__ == "__main__":
    basic()
    advanced()
    auto()

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.

Other Models

# Ollama
OPENAI_API_BASE='http://localhost:11434/v1'
OPENAI_MODEL_NAME='mistral'
OPENAI_API_KEY='NA'

# FastChat
OPENAI_API_BASE="http://localhost:8001/v1"
OPENAI_MODEL_NAME='oh-2.5m7b-q51'
OPENAI_API_KEY=NA

# LM Studio
OPENAI_API_BASE="http://localhost:1234/v1"
OPENAI_MODEL_NAME=NA
OPENAI_API_KEY=NA

# Mistral API
OPENAI_API_BASE=https://api.mistral.ai/v1
OPENAI_MODEL_NAME="mistral-small"
OPENAI_API_KEY=your-mistral-api-key

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

Star History Chart

praisonai's People

Contributors

mervinpraison avatar cypheroxide avatar austingreisman avatar south-american-cowboy avatar

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