wip
Estelle Poulin
12 months ago
parent
f9859d1767
commit
ab492417d6
@ -0,0 +1,41 @@
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---
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name: Publish Python distributions to PyPI and TestPyPI
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on:
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push:
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branches: [main]
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pull_request:
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branches: [main]
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jobs:
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validate:
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name: Run static analysis on the code
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runs-on: ubuntu-22.04
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steps:
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- name: Lint with flake8
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run: |
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pip install flake8
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# stop the build if there are Python syntax errors or undefined names
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flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
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# exit-zero treats all errors as warnings.
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flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
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build-and-publish:
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name: Build and publish Python distribution
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runs-on: ubuntu-22.04
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steps:
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- uses: actions/checkout@main
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- name: Initialize Python 3.11
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uses: actions/setup-python@v1
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with:
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python-version: 3.11
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip build
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- name: Build binary wheel and a source tarball
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run: python -m build
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- name: Publish distribution to PyPI
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uses: pypa/gh-action-pypi-publish@v1.8.5
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with:
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password: ${{ secrets.PIPY_PASSWORD }}
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@ -1,2 +1,71 @@
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# stabilityai
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Client library for the stability.ai REST API
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# Stability AI
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An **UNOFFICIAL** client library for the stability.ai REST API.
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## Motivation
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The official `stability-sdk` is a based on gRPC and also really hard to use. Like look at this, this
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ignores setting up the SDK.
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```python
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from stability_sdk import client
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import stability_sdk.interfaces.gooseai.generation.generation_pb2 as generation
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answers = stability_api.generate(
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prompt="a rocket-ship launching from rolling greens with blue daisies",
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seed=892226758,
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steps=30,
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cfg_scale=8.0,
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width=512,
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height=512,
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sampler=generation.SAMPLER_K_DPMPP_2M
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)
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for resp in answers:
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for artifact in resp.artifacts:
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if artifact.finish_reason == generation.FILTER:
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warnings.warn(
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"Your request activated the API's safety filters and could not be processed."
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"Please modify the prompt and try again.")
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if artifact.type == generation.ARTIFACT_IMAGE:
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global img
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img = Image.open(io.BytesIO(artifact.binary))
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img.save(str(artifact.seed)+ ".png")
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```
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This for loop is *magic*. You must loop the results in exactly this way or the gRPC library won't
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work. It's about an unpythonic as a library can get.
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## My Take
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```python
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# Set the STABILITY_API_KEY environment variable.
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from stabilityai.client import AsyncStabilityClient
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from stabilityai.models import Sampler
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async def example():
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async with AsyncStabilityClient() as stability:
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results = await stability.text_to_image(
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text_prompt="a rocket-ship launching from rolling greens with blue daisies",
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# All these are optional and have sane defaults.
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seed=892226758,
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steps=30,
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cfg_scale=8.0,
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width=512,
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height=512,
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sampler=Sampler.K_DPMPP_2M,
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)
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artifact = results.artifacts[0]
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img = Image.open(artifact.file)
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img.save(artifact.file.name)
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```
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## Additional Nicetieis
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* Instead of manually checking `FINISH_REASON` an appropriate exception will automatically be
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raised.
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* Full mypy/pyright support for type checking and autocomplete.
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@ -0,0 +1,50 @@
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# pyproject.toml
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# https://packaging.python.org/en/latest/specifications/declaring-project-metadata
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# https://pip.pypa.io/en/stable/reference/build-system/pyproject-toml
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[build-system]
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requires = ["setuptools", "setuptools-scm", "build"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "stabilityai"
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description = "*Unofficial* client for the Stability REST API"
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authors = [
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{name = "Estelle Poulin", email = "dev@inspiredby.es"},
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]
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readme = "README.md"
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requires-python = ">=3.11"
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keywords = ["stabilityai", "bot"]
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license = {text = "GPLv3"}
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classifiers = [
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"Programming Language :: Python :: 3",
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]
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dynamic = ["version", "dependencies"]
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[project.urls]
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homepage = "https://github.com/estheruary/stabilityai"
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repository = "https://github.com/estheruary/stabilityai"
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changelog = "https://github.com/estheruary/stabilityai/-/blob/main/CHANGELOG.md"
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[tool.setuptools]
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packages = ["stabilityai"]
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[tool.setuptools.dynamic]
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version = {attr = "stabilityai.__version__"}
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dependencies = {file = ["requirements.txt"]}
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[tool.black]
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line-length = 100
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[tool.isort]
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profile = "black"
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[tool.vulture]
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ignore_names = ["self", "cls"]
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@ -0,0 +1,2 @@
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aiohttp==3.8.4
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pydantic [email]==1.10.2
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@ -0,0 +1 @@
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__version__ = "1.0.1"
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@ -0,0 +1,271 @@
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import json
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import os
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from typing import Optional
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import aiohttp
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from pydantic import (
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validate_arguments,
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)
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from stabilityai.constants import (
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DEFAULT_GENERATION_ENGINE,
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DEFAULT_STABILITY_API_HOST,
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DEFAULT_STABILITY_CLIENT_ID,
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DEFAULT_STABILITY_CLIENT_VERSION,
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DEFAULT_UPSCALE_ENGINE,
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)
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from stabilityai.exceptions import YouNeedToUseAContextManager
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from stabilityai.models import (
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AccountResponseBody,
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BalanceResponseBody,
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CfgScale,
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ClipGuidancePreset,
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DiffuseImageHeight,
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DiffuseImageWidth,
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Engine,
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Extras,
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ImageToImageRequestBody,
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ImageToImageResponseBody,
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ImageToImageUpscaleRequestBody,
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ImageToImageUpscaleResponseBody,
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InitImage,
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InitImageMode,
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InitImageStrength,
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ListEnginesResponseBody,
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Sampler,
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Samples,
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Seed,
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SingleTextPrompt,
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Steps,
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StylePreset,
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TextPrompt,
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TextPrompts,
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TextToImageRequestBody,
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TextToImageResponseBody,
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UpscaleImageHeight,
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UpscaleImageWidth,
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)
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from stabilityai.utils import omit_none
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import textwrap
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class AsyncStabilityClient:
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def __init__(
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self,
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api_host: str = os.environ.get("STABILITY_API_HOST", DEFAULT_STABILITY_API_HOST),
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api_key: Optional[str] = os.environ.get("STABILITY_API_KEY"),
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client_id: str = os.environ.get("STABILITY_CLIENT_ID", DEFAULT_STABILITY_CLIENT_ID),
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client_version: str = os.environ.get(
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"STABILITY_CLIENT_VERSION", DEFAULT_STABILITY_CLIENT_VERSION
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),
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organization: Optional[str] = os.environ.get("STABILITY_CLIENT_ORGANIZATION"),
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) -> None:
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self.api_host = api_host
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self.api_key = api_key
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self.client_id = client_id
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self.client_version = client_version
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self.organization = organization
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async def __aenter__(self):
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self.session = await aiohttp.ClientSession(
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base_url=self.api_host,
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headers={
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"Content-Type": "application/json",
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"Accept": "application/json",
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"Authorization": f"Bearer {self.api_key}",
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"Stability-Client-ID": self.client_id,
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"Stability-Client-Version": self.client_version,
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**({"Organization": self.organization} if self.organization else {}),
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},
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raise_for_status=True,
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).__aenter__()
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return self
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async def __aexit__(self, exc_type, exc_val, exc_tb):
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return await self.session.__aexit__(exc_type, exc_val, exc_tb)
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async def get_engines(self) -> ListEnginesResponseBody:
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res = await self.session.get("/v1/engines/list")
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return await res.json()
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async def get_account(self) -> AccountResponseBody:
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res = await self.session.get("/v1/user/account")
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return await res.json()
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async def get_account_balance(self) -> BalanceResponseBody:
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res = await self.session.get("/v1/user/balance")
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return await res.json()
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def _oops_no_session(self):
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if not self.session:
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raise YouNeedToUseAContextManager(
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textwrap.dedent(
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f"""\
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{self.__class__.__name__} keeps a aiohttp.ClientSession under
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the hood and needs to be closed when you're done with it. But
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since there isn't an async version of __del__ we have to use
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__aenter__/__aexit__ instead. Apologies.
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Instead of
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myclient = {self.__class__.__name__}()
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myclient.text_to_image(...)
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Do this
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async with {self.__class__.__name__} as myclient:
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myclient.text_to_image(...)
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Note that it's `async with` and not `with`.
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"""
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)
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)
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def _normalize_text_prompts(
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self,
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text_prompts: Optional[TextPrompts],
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text_prompt: Optional[SingleTextPrompt]
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):
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if not bool(text_prompt) ^ bool(text_prompts):
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raise RuntimeError(
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textwrap.dedent(
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f"""\
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You must provide one of text_prompt and text_prompts.
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Do this
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stability.text_to_image(
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text_prompt="A beautiful sunrise"
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)
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Or this
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from stabilityai.models import TextPrompt
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stability.text_to_image(
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text_prompts=[
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TextPrompt(text="A beautiful sunrise", weight=1.0)
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],
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)
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"""
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)
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)
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if text_prompt:
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text_prompts = [TextPrompt(text=text_prompt)]
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# After this moment text_prompts can't be None.
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assert text_prompts is not None
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return text_prompts
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@validate_arguments
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async def text_to_image(
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self,
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text_prompts: Optional[TextPrompts] = None,
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text_prompt: Optional[SingleTextPrompt] = None,
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*,
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engine: Optional[Engine] = None,
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cfg_scale: Optional[CfgScale] = None,
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clip_guidance_preset: Optional[ClipGuidancePreset] = None,
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height: Optional[DiffuseImageHeight] = None,
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sampler: Optional[Sampler] = None,
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samples: Optional[Samples] = None,
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seed: Optional[Seed] = None,
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steps: Optional[Steps] = None,
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style_preset: Optional[StylePreset] = None,
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width: Optional[DiffuseImageWidth] = None,
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extras: Optional[Extras] = None,
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):
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self._oops_no_session()
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text_prompts = self._normalize_text_prompts(text_prompts, text_prompt)
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engine_id = engine.id if engine else DEFAULT_GENERATION_ENGINE
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request_body = TextToImageRequestBody(
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cfg_scale=cfg_scale,
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clip_guidance_preset=clip_guidance_preset,
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height=height,
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sampler=sampler,
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samples=samples,
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seed=seed,
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steps=steps,
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style_preset=style_preset,
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text_prompts=text_prompts,
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width=width,
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extras=extras,
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)
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res = await self.session.post(
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f"/v1/generation/{engine_id}/text-to-image",
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data=json.dumps(omit_none(json.loads(request_body.json()))),
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)
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Sampler.K_DPMPP_2M
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return TextToImageResponseBody.parse_obj(await res.json())
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@validate_arguments
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async def image_to_image(
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self,
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text_prompts: TextPrompts,
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text_prompt: SingleTextPrompt,
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init_image: InitImage,
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*,
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init_image_mode: Optional[InitImageMode] = None,
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image_strength: InitImageStrength,
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engine: Optional[Engine] = None,
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cfg_scale: Optional[CfgScale] = None,
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clip_guidance_preset: Optional[ClipGuidancePreset] = None,
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sampler: Optional[Sampler] = None,
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samples: Optional[Samples] = None,
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seed: Optional[Seed] = None,
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steps: Optional[Steps] = None,
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style_preset: Optional[StylePreset] = None,
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extras: Optional[Extras] = None,
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):
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self._oops_no_session()
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text_prompts = self._normalize_text_prompts(text_prompts, text_prompt)
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engine_id = engine.id if engine else DEFAULT_GENERATION_ENGINE
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request_body = ImageToImageRequestBody(
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cfg_scale=cfg_scale,
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clip_guidance_preset=clip_guidance_preset,
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init_image=init_image,
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init_image_mode=init_image_mode,
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image_strength=image_strength,
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sampler=sampler,
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samples=samples,
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seed=seed,
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steps=steps,
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style_preset=style_preset,
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text_prompts=text_prompts,
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extras=extras,
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)
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|
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res = await self.session.post(
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f"/v1/generation/{engine_id}/text-to-image",
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data=json.dumps(omit_none(json.loads(request_body.json()))),
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)
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return ImageToImageResponseBody.parse_obj(await res.json())
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async def image_to_image_upscale(
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self,
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image: InitImage,
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*,
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engine: Optional[Engine] = None,
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width: Optional[UpscaleImageWidth] = None,
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height: Optional[UpscaleImageHeight] = None,
|
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):
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self._oops_no_session()
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engine_id = engine.id if engine else DEFAULT_UPSCALE_ENGINE
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request_body = ImageToImageUpscaleRequestBody(image=image, width=width, height=height)
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|
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res = await self.session.post(
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f"/v1/generation/{engine_id}/image-to-image/upscale",
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data=json.dumps(omit_none(json.loads(request_body.json()))),
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)
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return ImageToImageUpscaleResponseBody.parse_obj(await res.json())
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@ -0,0 +1,9 @@
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from typing import Final
|
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DEFAULT_STABILITY_API_HOST: Final[str] = "https://api.stability.ai"
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DEFAULT_STABILITY_CLIENT_ID: Final[str] = "Stability Python SDK"
|
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DEFAULT_STABILITY_CLIENT_VERSION: Final[str] = "1.0.0"
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|
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DEFAULT_GENERATION_ENGINE: Final[str] = "stable-diffusion-xl-beta-v2-2-2"
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DEFAULT_UPSCALE_ENGINE: Final[str] = "esrgan-v1-x2plus"
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@ -0,0 +1,2 @@
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class YouNeedToUseAContextManager(Exception):
|
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pass
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@ -0,0 +1,247 @@
|
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import base64
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import io
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from enum import StrEnum
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from typing import Annotated, List, Optional
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|
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from pydantic import (
|
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AnyUrl,
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BaseModel,
|
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EmailStr,
|
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confloat,
|
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conint,
|
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constr,
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validator,
|
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)
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|
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class Type(StrEnum):
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AUDIO = "AUDIO"
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CLASSIFICATION = "CLASSIFICATION"
|
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PICTURE = "PICTURE"
|
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STORAGE = "STORAGE"
|
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TEXT = "TEXT"
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VIDEO = "VIDEO"
|
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|
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|
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class Engine(BaseModel):
|
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description: str
|
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id: str
|
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name: str
|
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type: Type
|
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|
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|
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class Error(BaseModel):
|
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id: str
|
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name: str
|
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message: str
|
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|
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|
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CfgScale = Annotated[float, confloat(ge=0.0, le=35.0)]
|
||||
|
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|
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class ClipGuidancePreset(StrEnum):
|
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FAST_BLUE = "FAST_BLUE"
|
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FAST_GREEN = "FAST_GREEN"
|
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NONE = "NONE"
|
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SIMPLE = "SIMPLE"
|
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SLOW = "SLOW"
|
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SLOWER = "SLOWER"
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SLOWEST = "SLOWEST"
|
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|
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UpscaleImageHeight = Annotated[int, conint(ge=512)]
|
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UpscaleImageWidth = Annotated[int, conint(ge=512)]
|
||||
|
||||
DiffuseImageHeight = Annotated[int, conint(ge=128, multiple_of=64)]
|
||||
|
||||
DiffuseImageWidth = Annotated[int, conint(ge=128, multiple_of=64)]
|
||||
|
||||
|
||||
class Sampler(StrEnum):
|
||||
DDIM = "DDIM"
|
||||
DDPM = "DDPM"
|
||||
K_DPMPP_2M = "K_DPMPP_2M"
|
||||
K_DPMPP_2S_ANCESTRAL = "K_DPMPP_2S_ANCESTRAL"
|
||||
K_DPM_2 = "K_DPM_2"
|
||||
K_DPM_2_ANCESTRAL = "K_DPM_2_ANCESTRAL"
|
||||
K_EULER = "K_EULER"
|
||||
K_EULER_ANCESTRAL = "K_EULER_ANCESTRAL"
|
||||
K_HEUN = "K_HEUN"
|
||||
K_LMS = "K_LMS"
|
||||
|
||||
|
||||
Samples = Annotated[int, conint(ge=1, le=10)]
|
||||
|
||||
Seed = Annotated[int, conint(ge=0, le=4294967295)]
|
||||
|
||||
Steps = Annotated[int, conint(ge=10, le=150)]
|
||||
|
||||
Extras = dict
|
||||
|
||||
|
||||
class StylePreset(StrEnum):
|
||||
enhance = "enhance"
|
||||
anime = "anime"
|
||||
photographic = "photographic"
|
||||
digital_art = "digital-art"
|
||||
comic_book = "comic-book"
|
||||
fantasy_art = "fantasy-art"
|
||||
line_art = "line-art"
|
||||
analog_film = "analog-film"
|
||||
neon_punk = "neon-punk"
|
||||
isometric = "isometric"
|
||||
low_poly = "low-poly"
|
||||
origami = "origami"
|
||||
modeling_compound = "modeling-compound"
|
||||
cinematic = "cinematic"
|
||||
field_3d_model = "3d-model"
|
||||
pixel_art = "pixel-art"
|
||||
tile_texture = "tile-texture"
|
||||
|
||||
|
||||
class TextPrompt(BaseModel):
|
||||
text: Annotated[str, constr(max_length=2000)]
|
||||
weight: Optional[float] = None
|
||||
|
||||
SingleTextPrompt = str
|
||||
|
||||
TextPrompts = List[TextPrompt]
|
||||
|
||||
InitImage = bytes
|
||||
|
||||
InitImageStrength = Annotated[float, confloat(ge=0.0, le=1.0)]
|
||||
|
||||
|
||||
class InitImageMode(StrEnum):
|
||||
IMAGE_STRENGTH = "IMAGE_STRENGTH"
|
||||
STEP_SCHEDULE = "STEP_SCHEDULE"
|
||||
|
||||
|
||||
StepScheduleStart = Annotated[float, confloat(ge=0.0, le=1.0)]
|
||||
|
||||
StepScheduleEnd = Annotated[float, confloat(ge=0.0, le=1.0)]
|
||||
|
||||
MaskImage = bytes
|
||||
|
||||
MaskSource = str
|
||||
|
||||
|
||||
class GenerationRequestOptionalParams(BaseModel):
|
||||
cfg_scale: Optional[CfgScale] = None
|
||||
clip_guidance_preset: Optional[ClipGuidancePreset] = None
|
||||
sampler: Optional[Sampler] = None
|
||||
samples: Optional[Samples] = None
|
||||
seed: Optional[Seed] = None
|
||||
steps: Optional[Steps] = None
|
||||
style_preset: Optional[StylePreset] = None
|
||||
extras: Optional[Extras] = None
|
||||
|
||||
|
||||
class LatentUpscalerUpscaleRequestBody(BaseModel):
|
||||
image: InitImage
|
||||
width: Optional[UpscaleImageWidth] = None
|
||||
height: Optional[UpscaleImageHeight] = None
|
||||
text_prompts: Optional[TextPrompts] = None
|
||||
seed: Optional[Seed] = None
|
||||
steps: Optional[Steps] = None
|
||||
cfg_scale: Optional[CfgScale] = None
|
||||
|
||||
|
||||
class ImageToImageRequestBody(BaseModel):
|
||||
text_prompts: TextPrompts
|
||||
init_image: InitImage
|
||||
init_image_mode: Optional[InitImageMode] = InitImageMode("IMAGE_STRENGTH")
|
||||
image_strength: Optional[InitImageStrength] = None
|
||||
step_schedule_start: Optional[StepScheduleStart] = None
|
||||
step_schedule_end: Optional[StepScheduleEnd] = None
|
||||
cfg_scale: Optional[CfgScale] = None
|
||||
clip_guidance_preset: Optional[ClipGuidancePreset] = None
|
||||
sampler: Optional[Sampler] = None
|
||||
samples: Optional[Samples] = None
|
||||
seed: Optional[Seed] = None
|
||||
steps: Optional[Steps] = None
|
||||
style_preset: Optional[StylePreset] = None
|
||||
extras: Optional[Extras] = None
|
||||
|
||||
|
||||
class MaskingRequestBody(BaseModel):
|
||||
init_image: InitImage
|
||||
mask_source: MaskSource
|
||||
mask_image: Optional[MaskImage] = None
|
||||
text_prompts: TextPrompts
|
||||
cfg_scale: Optional[CfgScale] = None
|
||||
clip_guidance_preset: Optional[ClipGuidancePreset] = None
|
||||
sampler: Optional[Sampler] = None
|
||||
samples: Optional[Samples] = None
|
||||
seed: Optional[Seed] = None
|
||||
steps: Optional[Steps] = None
|
||||
style_preset: Optional[StylePreset] = None
|
||||
extras: Optional[Extras] = None
|
||||
|
||||
|
||||
class TextToImageRequestBody(GenerationRequestOptionalParams):
|
||||
height: Optional[DiffuseImageHeight] = None
|
||||
width: Optional[DiffuseImageWidth] = None
|
||||
text_prompts: TextPrompts
|
||||
|
||||
|
||||
class ImageToImageUpscaleRequestBody(BaseModel):
|
||||
image: InitImage
|
||||
width: Optional[UpscaleImageWidth]
|
||||
height: Optional[UpscaleImageHeight]
|
||||
|
||||
@validator("width", always=True)
|
||||
def mutually_exclusive(cls, v, values):
|
||||
if values["height"] is not None and v:
|
||||
raise ValueError("You can only specify one of width and height.")
|
||||
return v
|
||||
|
||||
|
||||
class BalanceResponseBody(BaseModel):
|
||||
credits: float
|
||||
|
||||
|
||||
ListEnginesResponseBody = List[Engine]
|
||||
|
||||
|
||||
class FinishReason(StrEnum):
|
||||
SUCCESS = "SUCCESS"
|
||||
ERROR = "ERROR"
|
||||
CONTENT_FILTERED = "CONTENT_FILTERED"
|
||||
|
||||
|
||||
class Image(BaseModel):
|
||||
base64: Optional[str] = None
|
||||
finishReason: Optional[FinishReason] = None
|
||||
seed: Optional[float] = None
|
||||
|
||||
@property
|
||||
def file(self):
|
||||
assert self.base64 is not None
|
||||
return io.BytesIO(base64.b64decode(self.base64))
|
||||
|
||||
|
||||
class OrganizationMembership(BaseModel):
|
||||
id: str
|
||||
is_default: bool
|
||||
name: str
|
||||
role: str
|
||||
|
||||
|
||||
class AccountResponseBody(BaseModel):
|
||||
email: EmailStr
|
||||
id: str
|
||||
organizations: List[OrganizationMembership]
|
||||
profile_picture: Optional[AnyUrl] = None
|
||||
|
||||
|
||||
class TextToImageResponseBody(BaseModel):
|
||||
artifacts: List[Image]
|
||||
|
||||
|
||||
class ImageToImageResponseBody(BaseModel):
|
||||
artifacts: List[Image]
|
||||
|
||||
|
||||
class ImageToImageUpscaleResponseBody(BaseModel):
|
||||
artifacts: List[Image]
|
||||
@ -0,0 +1,6 @@
|
||||
from typing import Dict, Mapping, TypeVar
|
||||
|
||||
T, U = TypeVar("T"), TypeVar("U")
|
||||
|
||||
def omit_none(m: Mapping[T, U]) -> Dict[T, U]:
|
||||
return {k: v for k, v in m.items() if v is not None}
|
||||
Loading…
Reference in New Issue