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docs/source/quickstart/index.rst

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===========
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Welcome to FlashDreams! This page will guide you from a fresh checkout
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of the repository to running NVIDIA OmniDreams, the interactive
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HDMap-conditioned driving world-model demo built on FlashDreams.
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of the repository to a running model. It uses :doc:`NVIDIA OmniDreams
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</models/omnidreams>`, the interactive driving world model, as the
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example; the :doc:`model gallery </models/index>` lists the run command
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for every other model.
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Install
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-------
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FlashDreams uses the ``uv`` python package manager. Installation
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instructions for ``uv`` are available in the `Astral documentation
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<https://docs.astral.sh/uv/getting-started/installation/>`_.
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With ``uv`` installed, clone the repository and synchronize the OmniDreams
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workspace environment:
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FlashDreams uses the ``uv`` Python package manager (`installation
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instructions <https://docs.astral.sh/uv/getting-started/installation/>`_).
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With ``uv`` installed, clone the repository and synchronize the
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OmniDreams workspace:
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.. code-block:: bash
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git clone https://github.com/NVIDIA/flashdreams.git
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cd flashdreams
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uv sync --package flashdreams-omnidreams --extra interactive-drive
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This installs the FlashDreams core package, the OmniDreams integration,
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and the ``interactive-drive`` demo dependencies. The unified runner CLI is
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also available through the OmniDreams workspace member:
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.. code-block:: bash
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uv run --package flashdreams-omnidreams flashdreams-run --help
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If you are developing FlashDreams itself or want every shipped runner in
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one environment, use ``uv sync --extra dev --extra runners`` instead.
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Hugging Face authentication
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---------------------------
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OmniDreams downloads demo scenes and checkpoints from `Hugging Face
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<https://huggingface.co/>`_ the first time you run it. Before launching
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the demo, use a Hugging Face account with access to:
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- `nvidia/omni-dreams-models
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<https://huggingface.co/nvidia/omni-dreams-models>`_: checkpoints.
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- `nvidia/omni-dreams-scenes
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<https://huggingface.co/datasets/nvidia/omni-dreams-scenes>`_: demo
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scene data.
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- `nvidia/omni-dreams-samples
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<https://huggingface.co/datasets/nvidia/omni-dreams-samples>`_ if you
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plan to run the scripted example-data command later on this page.
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Then create a read token from `Hugging Face token settings
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<https://huggingface.co/settings/tokens>`_. The token must have read
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access to ``nvidia/omni-dreams-models`` and
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``nvidia/omni-dreams-scenes``. If you use a fine-grained token, include
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both repositories, plus ``nvidia/omni-dreams-samples`` if you plan to run
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the scripted example-data command. Export the token in the same shell
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where you run ``omnidreams-prepare``, ``interactive-drive``, or
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``flashdreams-run``:
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.. code-block:: bash
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export HF_TOKEN=hf_...
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If the default cache under ``~/.cache/huggingface`` is on a small disk,
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point ``HF_HOME`` at a larger volume before the first download:
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Most runs need a Hugging Face token. For OmniDreams, use a token with
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read access to `nvidia/omni-dreams-models
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<https://huggingface.co/nvidia/omni-dreams-models>`_ and
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`nvidia/omni-dreams-scenes
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<https://huggingface.co/datasets/nvidia/omni-dreams-scenes>`_:
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.. code-block:: bash
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export HF_HOME=/path/to/large/huggingface-cache
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export HF_TOKEN=<your-hf-token>
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For more environment and container details, see the project
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`README <https://github.com/NVIDIA/flashdreams/blob/main/README.md>`_.
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For container, caching, and other environment details, see the project
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`README <https://github.com/NVIDIA/flashdreams/blob/main/README.md>`_ and
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:doc:`/troubleshooting`.
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Run OmniDreams
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--------------
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Run your first model
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--------------------
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Start with the :doc:`OmniDreams </models/omnidreams>` interactive driving
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demo. The command below runs the world model in one process and streams
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the generated camera view to a browser:
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Launch the OmniDreams interactive driving demo. It runs the world model
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and streams the generated camera view to a browser:
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.. code-block:: bash
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uv run --package flashdreams-omnidreams interactive-drive --stream-mjpeg :8080
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Then open ``http://<server-ip>:8080/`` in a browser on the same network
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(use ``localhost`` on the same machine). The first launch spends several
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minutes loading checkpoints and compiling kernels; later launches reuse
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the cached assets.
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On VRAM-constrained GPUs, add ``--offload-text-encoder`` to reduce peak
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VRAM usage by about 15 GB:
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--stream-mjpeg :8080 \
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--offload-text-encoder
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This runs the text and first-frame encoders once per scene, frees them
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before building the diffusion pipeline, and reuses the cached embeddings
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across world-model resets. The trade-off is slower first loads and
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scene/variant switches.
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Then open ``http://<server-ip>:8080/`` in a browser on the same network.
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Use ``localhost`` when the browser is on the same machine. The default
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scene auto-stages on first launch when ``HF_TOKEN`` is set.
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Optionally, pre-download the default scene and model assets so access
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errors and multi-GB downloads happen before the demo starts:
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.. code-block:: bash
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uv run --package flashdreams-omnidreams omnidreams-prepare \
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--scene-uuid clipgt-0d404ff7-2b66-498c-b047-1ed8cded60d4
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The first launch can spend several minutes loading checkpoints,
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compiling kernels, capturing CUDA graphs, and autotuning. Later launches
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reuse cached assets and compiled kernels.
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Scripted OmniDreams generation
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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To generate a fixed OmniDreams rollout through ``flashdreams-run``, use
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the single-view runner with bundled example data:
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.. code-block:: bash
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uv run --package flashdreams-omnidreams \
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flashdreams-run \
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omnidreams-sv-2steps-chunk2-loc6-lightvae-lighttae-perf \
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--example-data True \
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--example_data_uuid "239560dc-33d1-11ef-9720-00044bcbccac" \
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--total-blocks 20
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See :doc:`/models/omnidreams` for local-window mode, WebRTC serving,
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scene variants, perf-manifest setup, multi-GPU launch commands, and
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additional example-data UUIDs.
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Other methods
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~~~~~~~~~~~~~
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After OmniDreams, the model gallery covers the rest of the shipped
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FlashDreams methods and their runner slugs. For example, the offline
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:doc:`Self-Forcing </models/self_forcing>` Wan 2.1 1.3B T2V method runs
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with:
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.. code-block:: bash
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uv run --project integrations/self_forcing \
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flashdreams-run self-forcing-wan2.1-t2v-1.3b-taehv \
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--total-blocks 7
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Additional setup options
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------------------------
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These steps are not required for the basic OmniDreams demo, but they are
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useful for development workflows and downstream projects.
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Use FlashDreams as a library
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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If you only need FlashDreams as a dependency in another project rather
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than running the shipped methods, install it from PyPI instead:
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.. code-block:: bash
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pip install flashdreams
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Or track the current ``main`` branch:
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.. code-block:: bash
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pip install "git+https://github.com/NVIDIA/flashdreams.git"
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See :doc:`/models/omnidreams` for the offload trade-offs, scripted
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generation, scene variants, WebRTC serving, and multi-GPU options.
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Where to next
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-------------
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- :doc:`/models/index`: every shipped method with its CLI slug,
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checkpoint source, per-method knobs, and the command to run it.
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- :doc:`/models/index`: every shipped model with its CLI slug and the
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command to run it.
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- :doc:`/models/omnidreams`: drive a world model in real time with the
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``interactive-drive`` demo.
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- :doc:`/developer_guides/inference_pipeline_overview`: the generation
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- :doc:`CLI and API Reference </api/index>`: Reference docs for the
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``flashdreams-run`` CLI and the FlashDreams Python API.
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- :doc:`/troubleshooting`: common first-run failures and fixes.
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Project and support
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-------------------
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FlashDreams is developed in the open on GitHub, and contributions are
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welcome. If you hit a bug or have a feature request, open an issue; if
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you have a fix or improvement, send a pull request. Browsing existing
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issues and pull requests is also a good way to see what others are
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working on.
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- `GitHub repository <https://github.com/NVIDIA/flashdreams>`_: source,
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releases, and documentation.
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- `Issues <https://github.com/NVIDIA/flashdreams/issues>`_: report bugs
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or request features.
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- `Pull requests <https://github.com/NVIDIA/flashdreams/pulls>`_: review
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work in progress or contribute your own.

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