waldiez-runner 0.5.4

Serve and run your Waldiez flows in isolated environments and stream logs/input/output via Redis

Waldiez Runner

Run your Waldiez flows in isolated environments and stream AG2 logs/input/output via Redis.

Overview

Waldiez Runner enables executing flows in isolated Python virtual environments or containers, with full I/O streaming via Redis and task management via FastAPI + Taskiq.

Backed by:

• FastAPI for the HTTP API
• Taskiq for async task queuing and scheduling
• Redis for messaging and log/input/output streaming
• PostgreSQL for task and client persistence
• Waldiez + ag2 + FastStream for defining, executing, and streaming interactive flows in isolation

Getting Started

Follow these steps to get Waldiez Runner up and running in your development environment.

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🐳 Quickstart (Docker/Podman Compose)

To launch the full development stack (API + Redis + Postgres + Nginx):

!!!Note This could take some minutes on the first run, as it installs all dependencies.

docker compose -f compose.dev.yaml up --build

This setup includes:

• API server (waldiez-runner)
• Redis + PostgreSQL
• Taskiq worker + scheduler
• Nginx reverse proxy
• A simple static example in examples/html

Once started, you can access:

• Static example UI: http://localhost
• API: http://localhost/docs (Swagger UI)

!!!Note Alternatively, you can open this project in VS Code with Dev Containers enabled — it uses most of the services (not nginx) via .devcontainer/compose.yaml.

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🔑 Authenticating with the API or Example UI

When the server starts, it automatically generates a clients.json file in the project root.
This file contains two API clients:

• One for the clients-api audience (managing clients)
• One for the tasks-api audience (creating and interacting with tasks)

You'll need the tasks-api credentials to:

• Use the Swagger UI (try out endpoints under /api/v1/tasks)
• Submit tasks via curl or HTTP clients
• Use the example UI at http://localhost

!!!INFO On the example page, you’ll be asked to paste the base URL, client ID, and secret.
Use the values from clients.json (specifically the tasks-api entry).

🔐 See Clients & Authentication for more details.

🧪 Local Mode (Advanced)

You can also run the server without any external dependencies (Redis/Postgres):

• SQLite for storage
• FakeRedis for message streams

make dev-no-reload

!!!Warning Do expect limitations in this mode, [Fake]Redis messages might not work as expected.

Or manually (what make dev-no-reload does):

# drop all tables and remove the .env file if it exists
python scripts/drop.py
# switch to local mode if not already
python scripts/toggle.py --mode local
# make sure the .env file is created and the database is initialized
python scripts/pre_start.py --dev
# make sure the first two Clients are created
python scripts/initial_data.py --dev
# start the server, the broker and the scheduler
python -m waldiez_runner --trusted-origins http://localhost:3000,http://localhost:8000 --trusted-hosts localhost --debug --no-force-ssl --no-redis --no-postgres --dev --all

You can now either use the Swagger UI at http://localhost:8000/docs or you can also serve the example on another port terminal:

cd examples/plain
python -m http.server 3000

Calling python -m http.server will start a simple HTTP server on port 3000, serving the files in the current directory. You can now access the example UI at http://localhost:3000.

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📤 Submitting and Managing Tasks

Once the server is running, you can create and interact with tasks:

• Submit a task by uploading a .waldiez file via:

  • the example UI at http://localhost
  • or the Swagger UI at http://localhost/docs (POST /api/v1/tasks)

• Monitor task progress via:

  • the Swagger GET /api/v1/tasks/{task_id}
  • or the WebSocket endpoint /ws/{task_id} (see WebSocket)

• Send input if the task requests it:

  • Use the input box in the example UI
  • Or call POST /api/v1/tasks/{task_id}/input

• Cancel or delete tasks using:

  • POST /api/v1/tasks/{task_id}/cancel
  • DELETE /api/v1/tasks/{task_id}

You can explore all available routes via the interactive API docs at /docs.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Panagiotis Kasnesis 📆 🔬	Lazaros Toumanidis 💻	Stella Ioannidou 📣 🎨	Amalia Contiero 💻 🐛	Christos Chatzigeorgiou 💻
Add your contributions

This project follows the all-contributors specification. Contributions of any kind welcome!

License

This project is licensed under the Apache License, Version 2.0 (Apache-2.0).