opennetwork 0.1.0

OpenNetwork Dev Suite: JSON->Keras model builder + Playground webview

OpenNetwork (opennetwork)

A tiny developer suite for MLOps-oriented model authoring and loading. It lets you:

• opennetwork.setmodel() — open the Playground (web view) to design your model.
• opennetwork.getmodel("model.json") — load a JSON graph into a Keras Functional model.
• opennetwork.init() — quickstart banner.

Default Playground: https://opensparrow.netlify.app/playground

Install

pip install opennetwork
# or, to enable building Keras models:
pip install "opennetwork[keras]"
# optional native window instead of browser:
pip install "opennetwork[webview]"

Python API

import opennetwork as onn

onn.init()
onn.setmodel()  # opens the Playground in a window/browser

# Build from JSON (returns tf.keras.Model if TensorFlow is installed)
model = onn.getmodel("model.json")

# If TensorFlow is not installed, you can still validate the graph:
model, extras = onn.getmodel("model.json", return_extras=True)
print(extras["inserted"])  # e.g., auto-added Flatten when Dense follows Conv2D

CLI

opennetwork init
opennetwork setmodel
opennetwork getmodel path/to/model.json

JSON schema (minimal)

{
  "id": "string",
  "name": "string",
  "layers": [
    {
      "id": "unique-id",
      "type": "input|conv2d|dense|flatten|dropout|maxpool2d|batchnorm|activation|softmax_output",
      "name": "optional",
      "params": { "..." : "layer-params" },
      "connections": ["next-layer-id", "..."],
      "weights": [...],  // optional
      "biases":  [...]   // optional
    }
  ]
}

• The graph is built topologically.
• If a Dense follows a convolutional/tensor output, a Flatten is auto-inserted (configurable).
• softmax_output is interpreted as a final Activation("softmax").
• Unknown or missing shapes will be handled best-effort; for guaranteed results, include an explicit Input layer with params.input_shape.

License

MIT