Public API Quick Reference#

Synora exposes synora as the friendly public namespace for both application code and direct component imports. Use it for factory helpers, model classes, config classes, and environment constructors.

Common Workflow#

import synora

# Discover supported factories.
models = synora.list_models()
backends = synora.list_env_backends()

# Configure and create a model in one step.
agent = synora.create_model(
    "dreamer",
    env_backend="dmc",
    env="walker-walk",
    total_steps=1_000_000,
)

# Create standalone environments through a consistent backend selector.
env = synora.make_env("CartPole-v1", backend="gym")

Factory Helpers#

Helper	Purpose
`create_config(model, **overrides)`	Build the default config for a model family and apply validated overrides.
`create_model(model, config=None, **overrides)`	Instantiate a model or high-level agent by name. Config overrides are applied before construction; unknown fields are passed as constructor arguments when appropriate.
`make_env(env_id, backend="auto", **kwargs)`	Create an environment through a named backend such as `gym`, `atari`, `mujoco`, `robotics`, `brax`, or `unity`.
`list_models()`	Return canonical names accepted by `create_model`.
`list_env_backends()`	Return backend names accepted by `make_env`.
`list_envs(model=None)`	Return known environment IDs, optionally filtered by model family.

Direct Imports Still Work#

The factory API is a convenience layer. Advanced and research workflows can keep using direct imports from synora:

from synora import DreamerAgent, DreamerConfig, RSSM

cfg = DreamerConfig()
cfg.env = "walker-walk"
agent = DreamerAgent(cfg)

Use direct imports when you are composing custom modules, subclassing internals, or need access to implementation-specific constructors.

1.0 scope#

These names stay in the 1.x public surface, with the following documented limits:

There is no DreamerV3 implementation in 1.0, and no dreamer-v3 registry name: the Dreamer family is dreamer-v1 and dreamer-v2.
agent.train() with a step budget is the Dreamer-family path. Other registered models train through their dedicated trainers or CLI commands.
Genie VideoDataset loads .npy / .pt clips, or video files when the viz extra (OpenCV) is installed. TinyWorlds training still goes through scripts/train_genie_tinyworlds.py.