Manage project with poetry

.github/workflows/ci.yml

@@ -35,9 +35,9 @@ jobs:
           python -m pip install --upgrade pip
           pip install -r requirements.txt
 
-      - name: Install pip packages from dev_requirements.txt
+      - name: Install pip packages from requirements-dev.txt
         run: |
-          pip install -r dev_requirements.txt
+          pip install -r requirements-dev.txt
 
       - name: Test with unittest
         run: |

.github/workflows/release.yml

@@ -0,0 +1,59 @@
+
+---
+name: 🕊️ Release Workflow
+
+on:
+  workflow_dispatch:
+
+env:
+  ALLOWED_PUBLISHERS: "${{ github.actor == 'hmartiro' || github.actor == 'SethForsgren' }}"
+  STABLE_PYTHON_VERSION: '3.9'
+  PYTHONUNBUFFERED: "1"
+  FORCE_COLOR: "1"
+
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}
+  cancel-in-progress: true
+
+jobs:
+  release-workflow:
+    name: 🏹 Release Workflow
+    runs-on: ubuntu-latest
+
+    timeout-minutes: 10
+
+    steps:
+      - name: 📩 Checkout the source w/ full depth(for tags and SCM)
+        uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+
+      - name: 🐍 Setup Python ${{ env.STABLE_PYTHON_VERSION }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ env.STABLE_PYTHON_VERSION }}
+
+      - name: 🧱 Build wheel
+        run: |
+          pip install poetry
+          poetry install
+          poetry build
+
+      - name: 🐦 Release wheel
+        if: ${{ env.ALLOWED_PUBLISHERS && !failure() }}
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          password: ${{ SECRETS.PYPI_TOKEN }}
+          packages_dir: dist
+          verbose: true
+
+      - name: 📁 Archiving Artifacts
+        uses: actions/upload-artifact@v3
+        if: ${{ !failure() }}
+        continue-on-error: true
+        with:
+          name: build-artifacts
+          retention-days: 1
+          path: |
+            dist

.pylintrc

@@ -0,0 +1,5 @@
+[LOGGING]
+
+# Format style used to check logging format string. `old` means using %
+# formatting, `new` is for `{}` formatting,and `fstr` is for f-strings.
+logging-format-style=fstr

.streamlit/config.toml

@@ -0,0 +1,36 @@
+# Riffusion project streamlit configuration file
+
+[global]
+disableWatchdogWarning = false
+showWarningOnDirectExecution = true
+
+[client]
+caching = true
+displayEnabled = true
+
+
+[runner]
+magicEnabled = true
+installTracer = false
+fixMatplotlib = true
+
+
+[server]
+folderWatchBlacklist = []
+headless = true
+runOnSave = true
+port = 8501
+enableCORS = true
+
+
+[browser]
+serverAddress = "127.0.0.1"
+gatherUsageStats = false
+serverPort = 8501
+
+
+[logger]
+level = "info"
+
+[ui]
+hideTopBar = false

README.md

@@ -1,5 +1,7 @@
 # :guitar: Riffusion
 
+<!-- markdownlint-disable MD033 MD034 -->
+
 <a href="https://github.com/riffusion/riffusion/actions/workflows/ci.yml?query=branch%3Amain"><img alt="CI status" src="https://github.com/riffusion/riffusion/actions/workflows/ci.yml/badge.svg" /></a>
 <img alt="Python 3.9 | 3.10" src="https://img.shields.io/badge/Python-3.9%20%7C%203.10-blue" />
 <a href="https://github.com/riffusion/riffusion/tree/main/LICENSE"><img alt="MIT License" src="https://img.shields.io/badge/License-MIT-yellowgreen" /></a>
@@ -10,22 +12,23 @@ Read about it at https://www.riffusion.com/about and try it at https://www.riffu
 
 This is the core repository for riffusion image and audio processing code.
 
- * Diffusion pipeline that performs prompt interpolation combined with image conditioning
- * Conversions between spectrogram images and audio clips
- * Command-line interface for common tasks
- * Interactive app using streamlit
- * Flask server to provide model inference via API
- * Various third party integrations
+* Diffusion pipeline that performs prompt interpolation combined with image conditioning
+* Conversions between spectrogram images and audio clips
+* Command-line interface for common tasks
+* Interactive app using streamlit
+* Flask server to provide model inference via API
+* Various third party integrations
 
 Related repositories:
+
 * Web app: https://github.com/riffusion/riffusion-app
 * Model checkpoint: https://huggingface.co/riffusion/riffusion-model-v1
 
 ## Citation
 
 If you build on this work, please cite it as follows:
 
-```
+```txt
 @article{Forsgren_Martiros_2022,
   author = {Forsgren, Seth* and Martiros, Hayk*},
   title = {{Riffusion - Stable diffusion for real-time music generation}},
@@ -39,18 +42,29 @@ If you build on this work, please cite it as follows:
 Tested in CI with Python 3.9 and 3.10.
 
 It's highly recommended to set up a virtual Python environment with `conda` or `virtualenv`:
-```
+
+```shell
 conda create --name riffusion python=3.9
 conda activate riffusion
 ```
 
-Install Python dependencies:
+Install Python package:
+
+```shell
+pip install -U riffusion
 ```
-python -m pip install -r requirements.txt
+
+or clone the repository and install from source:
+
+```shell
+git clone https://github.com/riffusion/riffusion.git
+cd riffusion
+python -m pip install --editable .
 ```
 
 In order to use audio formats other than WAV, [ffmpeg](https://ffmpeg.org/download.html) is required.
-```
+
+```shell
 sudo apt-get install ffmpeg          # linux
 brew install ffmpeg                  # mac
 conda install -c conda-forge ffmpeg  # conda
@@ -61,14 +75,17 @@ If torchaudio has no backend, you may need to install `libsndfile`. See [this is
 If you have an issue, try upgrading [diffusers](https://github.com/huggingface/diffusers). Tested with 0.9 - 0.11.
 
 Guides:
+
 * [Simple Install Guide for Windows](https://www.reddit.com/r/riffusion/comments/zrubc9/installation_guide_for_riffusion_app_inference/)
 
 ## Backends
 
 ### CPU
+
 `cpu` is supported but is quite slow.
 
 ### CUDA
+
 `cuda` is the recommended and most performant backend.
 
 To use with CUDA, make sure you have torch and torchaudio installed with CUDA support. See the
@@ -80,12 +97,13 @@ steps in under five seconds, such as a 3090 or A10G.
 
 Test availability with:
 
-```python3
+```python
 import torch
 torch.cuda.is_available()
 ```
 
 ### MPS
+
 The `mps` backend on Apple Silicon is supported for inference but some operations fall back to CPU,
 particularly for audio processing. You may need to set
 `PYTORCH_ENABLE_MPS_FALLBACK=1`.
@@ -94,7 +112,7 @@ In addition, this backend is not deterministic.
 
 Test availability with:
 
-```python3
+```python
 import torch
 torch.backends.mps.is_available()
 ```
@@ -104,27 +122,31 @@ torch.backends.mps.is_available()
 Riffusion comes with a command line interface for performing common tasks.
 
 See available commands:
-```
-python -m riffusion.cli -h
+
+```shell
+riffusion -h
 ```
 
 Get help for a specific command:
-```
-python -m riffusion.cli image-to-audio -h
+
+```shell
+riffusion image-to-audio -h
 ```
 
 Execute:
-```
-python -m riffusion.cli image-to-audio --image spectrogram_image.png --audio clip.wav
+
+```shell
+riffusion image-to-audio --image spectrogram_image.png --audio clip.wav
 ```
 
 ## Riffusion Playground
 
 Riffusion contains a [streamlit](https://streamlit.io/) app for interactive use and exploration.
 
 Run with:
-```
-python -m streamlit run riffusion/streamlit/playground.py --browser.serverAddress 127.0.0.1 --browser.serverPort 8501
+
+```shell
+riffusion-playground
 ```
 
 And access at http://127.0.0.1:8501/
@@ -137,8 +159,8 @@ Riffusion can be run as a flask server that provides inference via API. This ser
 
 Run with:
 
-```
-python -m riffusion.server --host 127.0.0.1 --port 3013
+```shell
+riffusion-server --host 127.0.0.1 --port 3013
 ```
 
 You can specify `--checkpoint` with your own directory or huggingface ID in diffusers format.
@@ -148,7 +170,8 @@ Use the `--device` argument to specify the torch device to use.
 The model endpoint is now available at `http://127.0.0.1:3013/run_inference` via POST request.
 
 Example input (see [InferenceInput](https://github.com/hmartiro/riffusion-inference/blob/main/riffusion/datatypes.py#L28) for the API):
-```
+
+```json
 {
   "alpha": 0.75,
   "num_inference_steps": 50,
@@ -171,45 +194,53 @@ Example input (see [InferenceInput](https://github.com/hmartiro/riffusion-infere
 ```
 
 Example output (see [InferenceOutput](https://github.com/hmartiro/riffusion-inference/blob/main/riffusion/datatypes.py#L54) for the API):
-```
+
+```json
 {
   "image": "< base64 encoded JPEG image >",
   "audio": "< base64 encoded MP3 clip >"
 }
 ```
 
 ## Tests
+
 Tests live in the `test/` directory and are implemented with `unittest`.
 
 To run all tests:
-```
+
+```shell
 python -m unittest test/*_test.py
 ```
 
 To run a single test:
-```
+
+```shell
 python -m unittest test.audio_to_image_test
 ```
 
 To preserve temporary outputs for debugging, set `RIFFUSION_TEST_DEBUG`:
-```
+
+```shell
 RIFFUSION_TEST_DEBUG=1 python -m unittest test.audio_to_image_test
 ```
 
 To run a single test case within a test:
-```
+
+```shell
 python -m unittest test.audio_to_image_test -k AudioToImageTest.test_stereo
 ```
 
 To run tests using a specific torch device, set `RIFFUSION_TEST_DEVICE`. Tests should pass with
 `cpu`, `cuda`, and `mps` backends.
 
 ## Development Guide
-Install additional packages for dev with `python -m pip install -r dev_requirements.txt`.
 
-* Linter: `ruff`
+Install additional packages for dev with `python -m pip install -r requirements-dev.txt`.
+
+* Linters: `ruff`, `flake8`, `pylint`
 * Formatter: `black`
 * Type checker: `mypy`
+* Docstring checker: `pydocstyle`
 
 These are configured in `pyproject.toml`.