praisonai-deploy
Deployment tooling for PraisonAI — API servers, Docker images, and cloud providers (AWS, Azure, GCP).
Install
pip install praisonai-deploy
pip install "praisonai-deploy[api]" # Flask API server generation
pip install "praisonai[deploy]" # full umbrella with wrapper shims
CLI
praisonai deploy run --file agents.yaml
praisonai deploy doctor --all
praisonai deploy validate --file agents.yaml
praisonai deploy plan --file agents.yaml
praisonai deploy status --file agents.yaml
praisonai deploy destroy --file agents.yaml --yes
praisonai deploy docker agents.yaml --tag v1
praisonai deploy aws agents.yaml --region us-east-1
Standalone console script:
praisonai-deploy --help
Python API
from praisonai_deploy import Deploy
deploy = Deploy.from_yaml("agents.yaml")
result = deploy.deploy()
status = deploy.status()
Legacy import paths (praisonai.deploy.*) remain available when the praisonai wrapper is installed.
Runtime dependency (generated servers)
Generated API servers and Docker images install praisonai (full wrapper) at runtime — they embed from praisonai import PraisonAI. The deploy package owns orchestration (generate, build, plan, doctor); containers need pip install praisonai flask gunicorn.
Cloud provider notes
| Provider | Behaviour |
|---|---|
| AWS ECS | Update-only path; greenfield deploy requires pre-existing VPC/service config |
| Azure | Container Apps create/update |
| GCP | Cloud Run create-or-update |
Host CLIs required: docker, aws, az, gcloud (no boto3/Azure SDK in this package).
Monorepo development
Editable install from this directory:
cd src/praisonai-deploy
uv pip install -e .
Regression gates:
scripts/check_c14_deploy_imports.shsrc/praisonai/tests/unit/test_c14_deploy_backward_compat.pysrc/praisonai-deploy/tests/
1 maintainer
Metadata
1 maintainer
Release files for praisonai-deploy 0.1.19
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Release files / praisonai_deploy-0.1.19.tar.gz
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