first push

app.py

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+# Imports
+from text_to_image import TextToImageTool
+import gradio as gr
+
+# Define Text to Image Tool
+tool = TextToImageTool()
+
+# Helper Function, necessary for Gradio
+def fn(*args, **kwargs):
+    return tool(*args, **kwargs)
+
+# Gradio Interface 
+gr.Interface(
+    fn=fn,
+    inputs=tool.inputs,
+    outputs=tool.outputs,
+    title="TextToImageTool",
+    article=tool.description,
+).queue(concurrency_count=5).launch()

requiremnets.txt

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+accelerate==0.20.3
+aiofiles==23.1.0
+aiohttp==3.8.4
+aiosignal==1.3.1
+altair==5.0.1
+anyio==3.7.0
+async-timeout==4.0.2
+attrs==23.1.0
+certifi==2023.5.7
+charset-normalizer==3.1.0
+click==8.1.3
+contourpy==1.1.0
+cycler==0.11.0
+diffusers @ git+https://github.com/huggingface/diffusers@666743302ff5bd1e02c204b81a80e566648d60de
+fastapi==0.97.0
+ffmpy==0.3.0
+filelock==3.12.2
+fonttools==4.40.0
+frozenlist==1.3.3
+fsspec==2023.6.0
+gradio==3.35.2
+gradio_client==0.2.7
+h11==0.14.0
+httpcore==0.17.2
+httpx==0.24.1
+huggingface-hub==0.15.1
+idna==3.4
+importlib-metadata==6.7.0
+Jinja2==3.1.2
+jsonschema==4.17.3
+kiwisolver==1.4.4
+linkify-it-py==2.0.2
+markdown-it-py==2.2.0
+MarkupSafe==2.1.3
+matplotlib==3.7.1
+mdit-py-plugins==0.3.3
+mdurl==0.1.2
+mpmath==1.3.0
+multidict==6.0.4
+networkx==3.1
+numpy==1.25.0
+orjson==3.9.1
+packaging==23.1
+pandas==2.0.2
+Pillow==9.5.0
+psutil==5.9.5
+pydantic==1.10.9
+pydub==0.25.1
+Pygments==2.15.1
+pyparsing==3.1.0
+pyrsistent==0.19.3
+python-dateutil==2.8.2
+python-multipart==0.0.6
+pytz==2023.3
+PyYAML==6.0
+regex==2023.6.3
+requests==2.31.0
+safetensors==0.3.1
+semantic-version==2.10.0
+six==1.16.0
+sniffio==1.3.0
+starlette==0.27.0
+sympy==1.12
+tokenizers==0.13.3
+toolz==0.12.0
+torch==2.0.1
+tqdm==4.65.0
+transformers==4.30.2
+typing_extensions==4.6.3
+tzdata==2023.3
+uc-micro-py==1.0.2
+urllib3==2.0.3
+uvicorn==0.22.0
+websockets==11.0.3
+yarl==1.9.2
+zipp==3.15.0

text_to_image.py

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+from transformers.tools.base import Tool, get_default_device
+from transformers.utils import is_accelerate_available
+import torch
+
+from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
+
+# Descrition of Image Processing
+TEXT_TO_IMAGE_DESCRIPTION = (
+    "This is a tool that creates an image according to a prompt"
+)
+
+# Defining a stable diffusion tool
+class TextToImageTool(Tool):
+    default_checkpoint = "runwayml/stable-diffusion-v1-5"
+    description = TEXT_TO_IMAGE_DESCRIPTION
+    inputs = ['text']
+    outputs = ['image']
+
+    def __init__(self, device=None, **hub_kwargs) -> None:
+        if not is_accelerate_available():
+            raise ImportError("Accelerate should be installed in order to use tools.")
+
+        super().__init__()
+
+        self.device = device
+        self.pipeline = None
+        self.hub_kwargs = hub_kwargs
+
+    def setup(self):
+        if self.device is None:
+            self.device = get_default_device()
+
+        self.pipeline = DiffusionPipeline.from_pretrained(self.default_checkpoint)
+        self.pipeline.scheduler = DPMSolverMultistepScheduler.from_config(self.pipeline.scheduler.config)
+        self.pipeline.to(self.device)
+
+        if self.device.type == "cuda":
+            self.pipeline.to(torch_dtype=torch.float16)
+
+        self.is_initialized = True
+
+    def __call__(self, prompt):
+        if not self.is_initialized:
+            self.setup()
+
+        negative_prompt = "low quality, bad quality, deformed, low resolution, janky"
+        added_prompt = " , highest quality, highly realistic, very high resolution"
+
+        return self.pipeline(prompt + added_prompt, negative_prompt=negative_prompt, num_inference_steps=25).images[0]