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7b853a5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | # Installation With Docker
> Note: the first time building and running with Docker can take several minutes, please be patient.
## Clone Modified Viser Library
The interactive demo relies on [a fork of Viser](https://github.com/nv-tlabs/kimodo-viser) that implements a timeline interface and more. Clone it within the `kimodo` directory before building with Docker using:
```bash
git clone https://github.com/nv-tlabs/kimodo-viser.git
```
## Quick Install
Before running Docker, make sure your Hugging Face token is available at
`~/.cache/huggingface/token` on the host, for example by running
`hf auth login` once outside the container (see the [Installation](installation.md) instructions).
The easiest way to build and immediately run the interactive demo webapp (with the text-encoder service) in one command is:
```bash
docker compose up -d --build
```
## Step-by-Step Installation
Alternatively, you can first build with:
```bash
docker compose build
```
This builds `text-encoder` and `demo` containers corresponding to the text encoding service and the interactive motion authoring webapp, respectively. Please see the [quick start guide](quick_start.md) for more information on these.
<details>
<summary>Advanced Configuration of Dependencies</summary>
This repo uses:
- `docker_requirements.in`: human-maintained, top-level dependencies
- `docker_requirements.txt`: pinned lockfile (automatically generated)
Notes:
- We keep a lockfile for **reproducible Docker builds** (so a rebuild next week pulls the same deps).
- The lockfile intentionally **omits `torch`/CUDA wheels** because the Docker base image
(`nvcr.io/nvidia/pytorch`) already provides a tested PyTorch build (avoids slow installs and CUDA mismatches).
</details>
<br>
After building, you will need to manually start the text-encoder service before doing any motion generation:
```bash
docker compose up text-encoder
```
Note, the first time running this command will take a long time as the Llama-based text encoder is downloaded.
Finally, to start the interactive demo:
```bash
docker compose up demo
```
For more information on using the Docker setup, see the [Quick Start](quick_start.md) guide next.
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