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.
pip install praisonaipraisonai --init create a movie script about dog in moonThis will automatically create agents.yaml file in the current directory.
To initialse with a specific agent framework:
praisonai --framework autogen --init create movie script about cat in marspraisonaior
python -m praisonaipraisonai --framework autogenpraisonai --auto create a movie script about Dog in Moonpython -m unittest tests.test 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.'framework: crewai
topic: Artificial Intelligence
roles:
movie_concept_creator:
backstory: 'Creative thinker with a deep understanding of cinematic storytelling,
capable of using AI-generated storylines to create unique and compelling movie
ideas.'
goal: Generate engaging movie concepts using AI storylines
role: Movie Concept Creator
tasks:
movie_concept_development:
description: 'Develop movie concepts from AI-generated storylines, ensuring
they are engaging and have strong narrative arcs.'
expected_output: 'Well-structured movie concept document with character
bios, settings, and plot outlines.'
screenwriter:
backstory: 'Expert in writing engaging dialogue and script structure, able to
turn movie concepts into production-ready scripts.'
goal: Write compelling scripts based on movie concepts
role: Screenwriter
tasks:
scriptwriting_task:
description: 'Turn movie concepts into polished scripts with well-developed
characters, strong dialogue, and effective scene transitions.'
expected_output: 'Production-ready script with a beginning, middle, and
end, along with character development and engaging dialogues.'
editor:
backstory: 'Adept at identifying inconsistencies, improving language usage,
and maintaining the overall flow of the script.'
goal: Refine the scripts and ensure continuity of the movie storyline
role: Editor
tasks:
editing_task:
description: 'Review, edit, and refine the scripts to ensure they are cohesive
and follow a well-structured narrative.'
expected_output: 'A polished final draft of the script with no inconsistencies,
strong character development, and effective dialogue.'
dependencies: []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()gcloud init
gcloud services enable run.googleapis.com
gcloud services enable containerregistry.googleapis.com
gcloud services enable cloudbuild.googleapis.com
export OPENAI_MODEL_NAME="gpt-4-turbo-preview"
export OPENAI_API_KEY="Enter your API key"
export OPENAI_API_BASE="https://api.openai.com/v1"
yes | gcloud auth configure-docker us-central1-docker.pkg.dev
gcloud artifacts repositories create praisonai-repository --repository-format=docker --location=us-central1
PROJECT_ID=$(gcloud config get-value project)
TAG="latest"
docker build --platform linux/amd64 -t gcr.io/${PROJECT_ID}/praisonai-app:${TAG} .
docker tag gcr.io/${PROJECT_ID}/praisonai-app:${TAG} us-central1-docker.pkg.dev/${PROJECT_ID}/praisonai-repository/praisonai-app:${TAG}
docker push us-central1-docker.pkg.dev/${PROJECT_ID}/praisonai-repository/praisonai-app:${TAG}
gcloud run deploy praisonai-service \
--image us-central1-docker.pkg.dev/${PROJECT_ID}/praisonai-repository/praisonai-app:${TAG} \
--platform managed \
--region us-central1 \
--allow-unauthenticated \
--set-env-vars OPENAI_MODEL_NAME=${OPENAI_MODEL_NAME},OPENAI_API_KEY=${OPENAI_API_KEY},OPENAI_API_BASE=${OPENAI_API_BASE}
## 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:8000/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.