CLI

PyFlue exposes the pyflue command.

pyflue init

Create a new project:

pyflue init my-agent

Overwrite an existing directory:

pyflue init my-agent --force

Generated files:

AGENTS.md
pyflue.toml
.agents/skills/triage.md
.agents/roles/coder.md
agents/default.py

pyflue run

Run one prompt:

pyflue run --prompt "Review this project"

Use a named session:

pyflue run --session issue-123 --prompt "Inspect the failure"

Enable sandbox writes and shell:

pyflue run \
  --prompt "Write a short report" \
  --allow-write \
  --allow-shell

Print stream events:

pyflue run --stream --prompt "Review this project"

pyflue skill new

Create a new Markdown skill:

pyflue skill new review

pyflue add

Print connector setup instructions for a coding agent.

List available connector guides:

pyflue add

Show copyable agent commands:

pyflue add daytona

Print the full guide:

pyflue add daytona --print

Build a custom sandbox connector from provider docs:

pyflue add https://e2b.dev/docs --category sandbox --print | codex

The command does not install hidden dependencies. It prints a clear guide that your coding agent can apply to your project.

pyflue build

pyflue build

The default target is Docker/FastAPI.

pyflue build --target docker

Available targets:

Target	Status	Generated files
docker	Implemented	Dockerfile, app.py
github-actions	Implemented	.github/workflows/pyflue-agent.yml
gitlab-ci	Implemented	.gitlab-ci.yml
railway	Implemented	Dockerfile, app.py, railway.json
render	Implemented	Dockerfile, app.py, render.yaml
fly	Implemented	Dockerfile, app.py, fly.toml
vercel	Implemented	Dockerfile, app.py, vercel.json
netlify	Implemented	Dockerfile, app.py, netlify.toml
cloudflare	Partial	wrangler.toml

pyflue dev

Start the local development server with reload:

pyflue dev --port 2024

The server exposes:

GET  /health
GET  /agents
POST /agents/{name}/{agent_id}
POST /prompt/{agent_id}
POST /prompt/{agent_id}/events

pyflue deploy

Generate deployment artifacts and a deployment manifest:

pyflue deploy --dry-run

Select a target:

pyflue deploy --target railway --dry-run

For supported provider CLIs, PyFlue runs the provider command when the CLI is installed and you are logged in. For other targets, it writes project files and .pyflue/deploy.json with the next step.