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57 changes: 57 additions & 0 deletions .github/workflows/build-release.yml
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name: CD | Build-Release

on:
push:
branches:
- "main"
paths-ignore:
- "README.md"
- "**/*.md"
- "docs/**"
- "**/*.yml"
release:
types: [published]
workflow_dispatch:
inputs:
image_tag:
description: "Docker Image Tag"
required: false
default: "dev"

jobs:
docker-build:
#if not running on self-hosted instance, replace with ubuntu-latest or other github hosted runner
runs-on: self-hosted

steps:
- name: Free disk space
run: |
sudo rm -rf /usr/share/dotnet
sudo rm -rf /usr/local/lib/android
sudo rm -rf /opt/ghc
sudo rm -rf "/usr/local/share/boost"
sudo rm -rf "$AGENT_TOOLSDIRECTORY"
sudo apt-get clean
df -h # Check available space
- name: Set up QEMU
uses: docker/setup-qemu-action@v2

- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2

- name: Login to Docker Hub
uses: docker/login-action@v2
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}

# Build and push step
- name: Build and push
uses: docker/build-push-action@v4
with:
push: true
build-args: |
HUGGINGFACE_TOKEN=${{ secrets.HUGGINGFACE_TOKEN }}
tags: ${{ vars.DOCKERHUB_REPO }}/${{ vars.DOCKERHUB_IMG }}:${{ (github.event_name == 'release' && github.event.release.tag_name) || (github.event_name == 'workflow_dispatch' && github.event.inputs.image_tag) || 'dev' }}

160 changes: 160 additions & 0 deletions .gitignore
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# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class

# C extensions
*.so

# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST

# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec

# Installer logs
pip-log.txt
pip-delete-this-directory.txt

# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/

# Translations
*.mo
*.pot

# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal

# Flask stuff:
instance/
.webassets-cache

# Scrapy stuff:
.scrapy

# Sphinx documentation
docs/_build/

# PyBuilder
.pybuilder/
target/

# Jupyter Notebook
.ipynb_checkpoints

# IPython
profile_default/
ipython_config.py

# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version

# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock

# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock

# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml

# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/

# Celery stuff
celerybeat-schedule
celerybeat.pid

# SageMath parsed files
*.sage.py

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# Spyder project settings
.spyderproject
.spyproject

# Rope project settings
.ropeproject

# mkdocs documentation
/site

# mypy
.mypy_cache/
.dmypy.json
dmypy.json

# Pyre type checker
.pyre/

# pytype static type analyzer
.pytype/

# Cython debug symbols
cython_debug/

# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
19 changes: 19 additions & 0 deletions Dockerfile
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# Base image -> https://github.com/runpod/containers/blob/main/official-templates/base/Dockerfile
# DockerHub -> https://hub.docker.com/r/runpod/base/tags
FROM runpod/base:0.4.0-cuda11.8.0

# Add build argument
ARG HUGGINGFACE_TOKEN
# Set it as an environment variable
ENV HUGGINGFACE_TOKEN=$HUGGINGFACE_TOKEN

COPY builder/requirements.txt /requirements.txt
RUN python3.11 -m pip install --upgrade pip && \
python3.11 -m pip install --upgrade -r /requirements.txt --no-cache-dir && \
rm /requirements.txt

ADD src .

RUN python3.11 /handler.py

CMD python3.11 -u /handler.py
21 changes: 21 additions & 0 deletions LICENSE
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MIT License

Copyright (c) 2024 Path On AI

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
88 changes: 88 additions & 0 deletions README.md
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<div align="center">

<h1>Stable Diffusion 3.5 Large Worker Template</h1>

A specialized worker template for building custom RunPod Endpoint API workers utilizing the Stable Diffusion 3.5 Large model. This implementation supports various aspect ratios, guidance scales, and inference steps customization.

</div>

## Docker Container

The ready-to-use Docker container is available on Docker Hub:
```bash
thehunter911/stbldiff3.5-large-runpod-serverless
```
which can be used to deploy onto Runpod Serverless endpoint directly.


You can also pull it using:
```bash
docker pull thehunter911/stbldiff3.5-large-runpod-serverless
```



## Input Parameters

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| prompt | string | required | The text description of the image you want to generate |
| aspect_ratio | string | "1:1" | Image aspect ratio. See supported values below |
| guidance_scale | float | 0.0 | How closely the model follows the prompt |
| num_inference_steps | integer | 1 | Number of denoising steps |

### Supported Aspect Ratios
- "16:9" - Widescreen (1024×576)
- "1:1" - Square (1024×1024)
- "21:9" - Ultra-wide (1024×439)
- "2:3" - Portrait (683×1024)
- "3:2" - Landscape (1024×683)
- "4:5" - Portrait (819×1024)
- "5:4" - Landscape (1024×819)
- "9:16" - Vertical/Mobile (576×1024)
- "9:21" - Vertical ultra-wide (439×1024)

## Example Input

```json
{
"input": {
"prompt": "An image of a cat with a hat on",
"aspect_ratio": "16:9",
"guidance_scale": 0.0,
"num_inference_steps": 1
}
}
```

## Example Output

The output is a base64 encoded string of the generated image. Example:

```
data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA...
```

### Viewing the Output

To view the generated image, you can decode the base64 string using Python:

```python
import base64
from PIL import Image
import io

# Replace 'base64_string' with your actual base64 string
base64_string = "iVBORw0KGgoAAAANSUhEUgAA..."
image_data = base64.b64decode(base64_string)
image = Image.open(io.BytesIO(image_data))
image.show()
```

## Performance Notes

This implementation uses torch.float16 with fp16 variant for optimal inference performance on consumer GPUs. This configuration provides:
- Faster inference speed
- Lower memory usage
- Better hardware compatibility
- Optimal for generation tasks
14 changes: 14 additions & 0 deletions builder/requirements.txt
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# Required Python packages get listed here, one per line.
# Reccomended to lock the version number to avoid unexpected changes.

# You can also install packages from a git repository, e.g.:
# git+https://github.com/runpod/runpod-python.git
# To learn more, see https://pip.pypa.io/en/stable/reference/requirements-file-format/

runpod~=1.7.0
diffusers
transformers
accelerate
hf_transfer
sentencepiece
protobuf
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