Upload folder using huggingface_hub

README.md

@@ -1,12 +1,6 @@
 ---
-title: TonAI Assistant
-emoji: 📚
-colorFrom: indigo
-colorTo: pink
-sdk: gradio
-sdk_version: 4.36.0
+title: TonAI-Assistant
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 4.31.2
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,80 @@
+import random
+import torch
+import gc
+import gradio as gr
+from PIL import Image
+from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline,\
+                      StableDiffusionXLPipeline, StableDiffusionUpscalePipeline,\
+                      DiffusionPipeline
+from utils import *
+from style import custom_css, header_html
+
+def gen_image(prompt, negative_prompt, width, height, num_steps, mode, seed, guidance_scale, device):
+    """
+    Run diffusion model to generate image
+    """
+    device = f"cuda:{device.split('GPU')[1][1]}"
+    guidance_scale = float(guidance_scale)
+    generator = torch.Generator(device).manual_seed(int(seed))
+    model_path = DIFFUSION_CHECKPOINTS[mode]["path"]
+    Text2Image_class = globals()[DIFFUSION_CHECKPOINTS[mode]["pipeline"]]
+    if DIFFUSION_CHECKPOINTS[mode]["type"] == "pretrained":
+        pipeline = Text2Image_class.from_pretrained(model_path)
+    else:
+        pipeline = Text2Image_class.from_single_file(model_path)
+    pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config)
+    try:
+        pipeline = pipeline.to(device)
+        image = pipeline(prompt=prompt,
+                         negative_prompt=negative_prompt,
+                         width=nearest_divisible_by_8(int(width)),
+                         height=nearest_divisible_by_8(int(height)),
+                         num_inference_steps=int(num_steps),
+                         generator=generator,
+                         guidance_scale=guidance_scale).images[0]
+    except Exception as e:
+        image = Image.open("stuffs/serverdown.jpg")
+        print(e)
+    del pipeline
+    torch.cuda.empty_cache()
+    gc.collect()
+    return image
+
+with gr.Blocks(title="TonAI Creative", theme=APP_THEME) as interface1:
+    gr.HTML(header_html)
+    with gr.Row():
+        with gr.Column(scale=3):
+            prompt = gr.Textbox(label="Prompt", placeholder="Tell me what you want to generate")
+            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Instruct the AI model that it should not include")
+            with gr.Row():
+                width = gr.Textbox(label="Image Width", value=768)
+                height = gr.Textbox(label="Image Height", value=768)
+            with gr.Row():
+                seed = gr.Textbox(label="RNG Seed", value=0, scale=1)
+                guidance_scale = gr.Textbox(label="CFG Scale", value=7, scale=1)
+            with gr.Row():
+                num_steps = gr.components.Slider(
+                                minimum=5, maximum=60, value=20, step=1,
+                                label="Inference Steps"
+                            )
+                mode=gr.Dropdown(choices=DIFFUSION_CHECKPOINTS.keys(), label="Mode",
+                                 value=list(DIFFUSION_CHECKPOINTS.keys())[1])
+            device_choices = display_gpu_info()
+            device=gr.Dropdown(choices=device_choices, label="Device", value=device_choices[0])
+            generate_btn = gr.Button("Generate")
+        with gr.Column(scale=2):
+            generate_btn.click(
+                        fn=gen_image,
+                        inputs=[prompt, negative_prompt, width, height, num_steps, mode, seed, guidance_scale, device],
+                        outputs=gr.Image(label="Generated Image", format="png"),
+                        concurrency_limit=10
+                    )
+        interface1.load(lambda: gr.update(value=random.randint(0, 999999)), None, seed)
+        interface1.load(lambda: gr.update(choices=display_gpu_info(), value=display_gpu_info()[0]), None, device)
+
+# interface = gr.TabbedInterface([interface1, iface2], ["Text-to-text", "image-to-text"])
+allowed_paths=["stuffs/tonai_research_logo.png"]
+interface1.queue(default_concurrency_limit=10)
+interface1.launch(share=True, 
+                  allowed_paths=allowed_paths,
+                  max_threads=10)

demo_app.py

@@ -0,0 +1,96 @@
+import random
+import torch
+import gc
+import gradio as gr
+from PIL import Image
+from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline,\
+                      StableDiffusionXLPipeline, StableDiffusionUpscalePipeline,\
+                      DiffusionPipeline
+from utils import *
+from style import custom_css, beta_header_html
+
+def gen_image(prompt, negative_prompt, width, height, num_steps,
+              mode, seed, guidance_scale, device):
+    """
+    Run diffusion model to generate image
+    """
+    use_adapter = True
+    device = f"cuda:{device.split('GPU')[1][1]}"
+    guidance_scale = float(guidance_scale)
+    generator = torch.Generator(device).manual_seed(int(seed)) 
+    model_path = DIFFUSION_CHECKPOINTS[mode]["path"]
+    Text2Image_class = globals()[DIFFUSION_CHECKPOINTS[mode]["pipeline"]]
+    if DIFFUSION_CHECKPOINTS[mode]["type"] == "pretrained":
+        pipeline = Text2Image_class.from_pretrained(model_path)
+    else:
+        pipeline = Text2Image_class.from_single_file(model_path)
+
+    if use_adapter:
+        if "SDXL 1.0" in mode:
+            print("Load LoRA model")
+            pipeline.load_lora_weights("../checkpoints", weight_name="mod2.safetensors")
+
+    pipeline.scheduler = DPMSolverMultistepScheduler.from_config(pipeline.scheduler.config)
+    try:
+        pipeline = pipeline.to(device)
+        image = pipeline(prompt=prompt,
+                        negative_prompt=negative_prompt,
+                        width=nearest_divisible_by_8(int(width)),
+                        height=nearest_divisible_by_8(int(height)),
+                        num_inference_steps=int(num_steps),
+                        generator=generator,
+                        guidance_scale=guidance_scale).images[0]
+        del pipeline
+        torch.cuda.empty_cache()
+        gc.collect()
+    except Exception as e:
+        image = Image.open("stuffs/serverdown.jpg")
+        print(e)
+        del pipeline
+        torch.cuda.empty_cache()
+        gc.collect()
+        return image
+    return image
+
+with gr.Blocks(title="(Beta) TonAI Creative", theme=APP_THEME) as interface1:
+    gr.HTML(beta_header_html)
+    with gr.Row():
+        with gr.Column(scale=3):
+            prompt = gr.Textbox(label="Prompt", 
+                                placeholder="Tell me what you want to generate",
+                                container=True)
+            negative_prompt = gr.Textbox(label="Negative Prompt", 
+                                         placeholder="Instruct the AI model that it should not include",
+                                         container=True)
+            with gr.Row():
+                width = gr.Textbox(label="Image Width", value=768)
+                height = gr.Textbox(label="Image Height", value=768)
+            with gr.Row():
+                seed = gr.Textbox(label="RNG Seed", value=0, scale=1)
+                guidance_scale = gr.Textbox(label="CFG Scale", value=7, scale=1)
+            with gr.Row():
+                num_steps = gr.components.Slider(
+                                minimum=5, maximum=60, value=20, step=1,
+                                label="Inference Steps"
+                            )
+                mode=gr.Dropdown(choices=DIFFUSION_CHECKPOINTS.keys(), label="Mode",
+                                 value=list(DIFFUSION_CHECKPOINTS.keys())[1])
+            device_choices = display_gpu_info()
+            device=gr.Dropdown(choices=device_choices, label="Device", value=device_choices[0])
+            generate_btn = gr.Button("Generate")
+        with gr.Column(scale=2):
+            generate_btn.click(
+                        fn=gen_image,
+                        inputs=[prompt, negative_prompt, width, height, num_steps, mode, seed, guidance_scale, device],
+                        outputs=gr.Image(label="Generated Image", format="png"),
+                        concurrency_limit=5
+                    )
+        interface1.load(lambda: gr.update(value=random.randint(0, 99999)), None, seed)
+        interface1.load(lambda: gr.update(choices=display_gpu_info(), value=display_gpu_info()[0]), None, device)
+
+# interface = gr.TabbedInterface([interface1, iface2], ["Text-to-text", "image-to-text"])
+allowed_paths=["stuffs/tonai_research_logo.png"]
+interface1.queue(default_concurrency_limit=5)
+interface1.launch(share=False,
+                  allowed_paths=allowed_paths,
+                  max_threads=5)

info(beta).html

@@ -0,0 +1,5 @@
+<p align="center">
+    <img src='file/stuffs/tonai_research_logo.png' alt='Logo' style='width: 100px; text-align: center'>
+</p>
+<h1 style='text-align: center;' markdown='1'>TonAI Creative (Beta Version)</h1>
+<h3 style='text-align: center;' markdown='1'>Create images and art using AI</h3>

info.html

@@ -0,0 +1,5 @@
+<p align="center">
+    <img src='file/stuffs/tonai_research_logo.png' alt='Logo' style='width: 100px; text-align: center'>
+</p>
+<h1 style='text-align: center;' markdown='1'>TonAI Creative</h1>
+<h3 style='text-align: center;' markdown='1'>Create images and art using AI</h3>

requirements.txt

@@ -0,0 +1,351 @@
+absl-py==2.0.0
+accelerate==0.27.2
+aiofiles==23.2.1
+aiohttp==3.8.6
+aiosignal==1.3.1
+altair==5.2.0
+annotated-types==0.6.0
+anyio==4.3.0
+appdirs==1.4.4
+asgiref==3.8.1
+asttokens==2.4.0
+async-property==0.2.2
+async-timeout==4.0.3
+asyncstdlib==3.12.2
+attrs==23.2.0
+auto_gptq==0.7.0
+backcall==0.2.0
+beartype==0.18.5
+beautifulsoup4==4.12.2
+bitsandbytes==0.41.1
+bleach==6.1.0
+blinker==1.7.0
+blis==0.7.11
+blobfile==2.1.1
+Brotli==1.1.0
+brotlipy==0.7.0
+browser-cookie3==0.19.1
+bs4==0.0.1
+cachetools==5.3.2
+catalogue==2.0.10
+certifi==2024.2.2
+cffi @ file:///tmp/abs_98z5h56wf8/croots/recipe/cffi_1659598650955/work
+chardet==3.0.4
+charset-normalizer @ file:///tmp/build/80754af9/charset-normalizer_1630003229654/work
+click==8.1.7
+cloudpathlib==0.16.0
+cloudpickle==3.0.0
+cmake==3.25.2
+colorama==0.4.6
+coloredlogs==15.0.1
+comm==0.1.4
+confection==0.1.4
+contourpy==1.2.0
+cryptography @ file:///croot/cryptography_1694444244250/work
+cssselect==1.2.0
+curl_cffi==0.6.3b1
+cycler==0.12.1
+cymem==2.0.8
+DALL-E==0.1
+dataclasses-json==0.6.4
+datasets==2.14.6
+debugpy==1.8.0
+decorator==5.1.1
+denoising-diffusion-pytorch==1.9.2
+diffuser==0.0.1
+-e git+https://github.com/huggingface/diffusers@965e52ce611108559a0ebab75c8b421d1229c5ab#egg=diffusers
+dill==0.3.7
+diskcache==5.6.3
+dlib==19.24.2
+dnspython==2.6.1
+docker-pycreds==0.4.0
+duckduckgo_search==5.3.0
+easyocr==1.7.1
+einops==0.7.0
+ema-pytorch==0.2.3
+email_validator==2.1.1
+exceptiongroup==1.1.3
+executing==2.0.0
+fastapi==0.111.0
+fastapi-cli==0.0.4
+feedfinder2==0.0.4
+feedparser==6.0.11
+ffmpy==0.3.2
+filelock @ file:///croot/filelock_1672387128942/work
+filterpy==1.4.5
+fire==0.5.0
+Flask==3.0.3
+flatbuffers==23.5.26
+fonttools==4.44.0
+frozenlist==1.4.0
+fsspec==2023.9.2
+ftfy==6.1.1
+g4f==0.3.1.8
+gdown==4.7.1
+gekko==1.0.6
+gitdb==4.0.11
+GitPython==3.1.40
+gmpy2 @ file:///tmp/build/80754af9/gmpy2_1645455533097/work
+google==3.0.0
+google-auth==2.23.4
+google-auth-oauthlib==1.1.0
+googletrans==3.0.0
+gradio==4.31.2
+gradio_client==0.16.3
+greenlet==3.0.3
+grpcio==1.59.2
+h11==0.14.0
+h2==3.2.0
+hpack==3.0.0
+hstspreload==2023.1.1
+httpcore==0.18.0
+httptools==0.6.1
+httpx==0.25.0
+huggingface-hub==0.21.3
+humanfriendly==10.0
+hyperframe==5.2.0
+idna==2.10
+imageio==2.33.1
+imagen-pytorch==1.26.3
+importlib-metadata==6.8.0
+importlib-resources==6.1.1
+iniconfig==2.0.0
+interegular==0.3.3
+iopath==0.1.10
+ipykernel==6.25.2
+ipython==8.16.1
+itsdangerous==2.1.2
+jedi==0.19.1
+jeepney==0.8.0
+jieba3k==0.35.1
+Jinja2 @ file:///croot/jinja2_1666908132255/work
+joblib==1.3.2
+Js2Py==0.74
+jsonpatch==1.33
+jsonpointer==2.4
+jsonschema==4.21.1
+jsonschema-specifications==2023.12.1
+jupyter_client==8.4.0
+jupyter_core==5.4.0
+kaggle==1.6.12
+kiwisolver==1.4.5
+kornia==0.7.2
+kornia_rs==0.1.3
+langchain==0.1.9
+langchain-community==0.0.24
+langchain-core==0.1.27
+langcodes==3.3.0
+langsmith==0.1.10
+lark==1.1.9
+lazy_loader==0.3
+llvmlite==0.42.0
+loguru==0.7.2
+lora-diffusion @ git+https://github.com/cloneofsimo/lora.git@bdd51b04c49fa90a88919a19850ec3b4cf3c5ecd
+loralib==0.1.2
+lxml==4.9.3
+lz4==4.3.3
+Markdown==3.5.1
+markdown-it-py==3.0.0
+MarkupSafe @ file:///opt/conda/conda-bld/markupsafe_1654597864307/work
+marshmallow==3.21.0
+matplotlib==3.8.1
+matplotlib-inline==0.1.6
+mdurl==0.1.2
+mediapipe==0.10.8
+mkl-fft==1.3.1
+mkl-random @ file:///home/builder/ci_310/mkl_random_1641843545607/work
+mkl-service==2.4.0
+mmh3==4.1.0
+mpmath @ file:///croot/mpmath_1690848262763/work
+msgpack==1.0.8
+multidict==6.0.4
+multiprocess==0.70.15
+murmurhash==1.0.10
+mypy==1.7.0
+mypy-extensions==1.0.0
+nest-asyncio==1.5.8
+networkx @ file:///croot/networkx_1690561992265/work
+newspaper3k==0.2.8
+ninja==1.11.1.1
+nltk==3.8.1
+numba==0.59.1
+numpy @ file:///croot/numpy_and_numpy_base_1682520569166/work
+nvidia-cublas-cu12==12.1.3.1
+nvidia-cuda-cupti-cu12==12.1.105
+nvidia-cuda-nvrtc-cu12==12.1.105
+nvidia-cuda-runtime-cu12==12.1.105
+nvidia-cudnn-cu12==8.9.2.26
+nvidia-cufft-cu12==11.0.2.54
+nvidia-curand-cu12==10.3.2.106
+nvidia-cusolver-cu12==11.4.5.107
+nvidia-cusparse-cu12==12.1.0.106
+nvidia-nccl-cu12==2.18.1
+nvidia-nvjitlink-cu12==12.4.127
+nvidia-nvtx-cu12==12.1.105
+oauthlib==3.2.2
+onnxruntime-gpu==1.16.0
+open-clip-torch==2.24.0
+opencv-contrib-python==4.8.1.78
+opencv-python==4.8.1.78
+opencv-python-headless==4.9.0.80
+optimum==1.17.1
+orjson==3.10.0
+outcome==1.3.0.post0
+outlines==0.0.34
+packaging==23.2
+pandas==2.1.1
+parso==0.8.3
+pathlib_abc==0.1.1
+pathos==0.3.1
+pathy==0.11.0
+peft==0.6.2
+pexpect==4.8.0
+pickleshare==0.7.5
+pillow==10.3.0
+platformdirs==3.11.0
+pluggy==1.3.0
+portalocker==2.8.2
+pox==0.3.3
+ppft==1.7.6.7
+preshed==3.0.9
+progressbar==2.5
+prometheus_client==0.20.0
+prompt-toolkit==3.0.39
+protobuf==3.20.3
+psutil==5.9.6
+ptyprocess==0.7.0
+pure-eval==0.2.2
+py-arkose-generator==0.0.0.2
+py-cpuinfo==9.0.0
+pyarrow==14.0.1
+pyasn1==0.5.0
+pyasn1-modules==0.3.0
+pyclipper==1.3.0.post5
+pycparser @ file:///tmp/build/80754af9/pycparser_1636541352034/work
+pycryptodome==3.20.0
+pycryptodomex==3.19.0
+pydantic==2.6.1
+pydantic_core==2.16.2
+pydub==0.25.1
+PyExecJS==1.5.1
+Pygments==2.16.1
+pyjsparser==2.7.1
+PyMuPDF==1.24.4
+PyMuPDFb==1.24.3
+pynvml==11.5.0
+pyOpenSSL @ file:///croot/pyopenssl_1690223430423/work
+pyparsing==3.1.1
+PySocks @ file:///home/builder/ci_310/pysocks_1640793678128/work
+pyTelegramBotAPI==4.14.0
+pytest==7.4.3
+python-bidi==0.4.2
+python-crfsuite==0.9.10
+python-dateutil==2.8.2
+python-dotenv==1.0.1
+python-multipart==0.0.9
+python-slugify==8.0.4
+pytorch-fid==0.3.0
+pytorch-warmup==0.1.1
+pytz==2023.3.post1
+pyvi==0.1.1
+PyYAML @ file:///croot/pyyaml_1670514731622/work
+pyzmq==25.1.1
+ray==2.11.0
+referencing==0.33.0
+regex==2023.10.3
+requests @ file:///croot/requests_1690400202158/work
+requests-file==2.0.0
+requests-oauthlib==1.3.1
+rfc3986==1.5.0
+rich==13.7.0
+rouge==1.0.1
+rpds-py==0.18.0
+rsa==4.9
+ruff==0.2.2
+safetensors==0.4.2
+scikit-image==0.22.0
+scikit-learn==1.4.2
+scipy==1.11.3
+seaborn==0.13.2
+selenium==4.19.0
+semantic-version==2.10.0
+sentencepiece==0.1.99
+sentry-sdk==1.37.0
+setproctitle==1.3.3
+sgmllib3k==1.0.0
+shapely==2.0.4
+shellingham==1.5.4
+six @ file:///tmp/build/80754af9/six_1644875935023/work
+sklearn-crfsuite==0.3.6
+smart-open==6.4.0
+smmap==5.0.1
+sniffio==1.3.0
+sortedcontainers==2.4.0
+sounddevice==0.4.6
+soupsieve==2.5
+spacy==3.6.1
+spacy-legacy==3.0.12
+spacy-loggers==1.0.5
+SQLAlchemy==2.0.27
+srsly==2.4.8
+stack-data==0.6.3
+starlette==0.37.2
+sympy @ file:///croot/sympy_1668202399572/work
+tabulate==0.9.0
+tenacity==8.2.3
+tensorboard==2.15.1
+tensorboard-data-server==0.7.2
+termcolor==2.3.0
+text-unidecode==1.3
+thinc==8.1.12
+thop==0.1.1.post2209072238
+threadpoolctl==3.4.0
+tifffile==2024.1.30
+tiktoken==0.6.0
+timm==0.9.16
+tinysegmenter==0.3
+tldextract==5.1.1
+tokenizers==0.19.1
+tomli==2.0.1
+tomlkit==0.12.0
+toolz==0.12.1
+torch==2.1.2
+torchaudio==2.1.0
+torchmultimodal-nightly==2023.11.13
+torchvision==0.16.0
+tornado==6.3.3
+tqdm==4.66.1
+traitlets==5.11.2
+transformers==4.40.0
+translators==5.8.8
+trio==0.25.0
+trio-websocket==0.11.1
+triton==2.1.0
+typer==0.12.3
+typing-inspect==0.9.0
+typing_extensions==4.9.0
+tzdata==2023.3
+tzlocal==5.2
+ujson==5.10.0
+ultralytics==8.2.2
+undetected-chromedriver==3.5.5
+Unidecode==1.3.8
+urllib3==2.2.1
+uvicorn==0.29.0
+uvloop==0.19.0
+vi-core-news-lg @ https://gitlab.com/trungtv/vi_spacy/-/raw/master/packages/vi_core_news_lg-3.6.0/dist/vi_core_news_lg-3.6.0.tar.gz#sha256=4f3a3b88c03c1d035a924f7103a5c81ac2922571f2db5022898978b5b3eb5976
+vllm==0.4.0.post1
+waitress==3.0.0
+wandb==0.16.6
+wasabi==1.1.2
+watchfiles==0.21.0
+wcwidth==0.2.8
+weasel==0.3.4
+webencodings==0.5.1
+websockets==11.0.3
+Werkzeug==3.0.1
+wsproto==1.2.0
+xformers==0.0.23.post1
+xxhash==3.4.1
+yarl==1.9.2
+zipp==3.17.0

stuffs/negative_prompt.txt

@@ -0,0 +1 @@
+lowres, text, error, cropped, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature

style.py

@@ -0,0 +1,32 @@
+from typing import Iterable
+from utils import *
+from gradio.themes.base import Base
+from gradio.themes.utils import colors, fonts, sizes
+import time
+
+custom_css = """
+body {
+    background-color: #f0f0f0;
+    color: #333;
+    font-family: Arial, sans-serif;
+}
+
+.gr-button {
+    background-color: #4CAF50;
+    color: white;
+    border: none;
+    border-radius: 4px;
+    padding: 10px 20px;
+    cursor: pointer;
+}
+
+.gr-button:hover {
+    background-color: #45a049;
+}
+
+.gr-textbox, .gr-image {
+    margin-top: 10px;
+}
+"""
+header_html = read_md_file_to_string("info.html")
+beta_header_html = read_md_file_to_string("info(beta).html")

utils.py

@@ -0,0 +1,94 @@
+import gradio as gr
+import GPUtil
+
+DIFFUSION_CHECKPOINTS = {
+    "General (SD 2.1)": {
+        "path": "stabilityai/stable-diffusion-2-1",
+        "type": "pretrained",
+        "pipeline": "StableDiffusionPipeline"
+    },
+    "Realistic (SD 1.5)": {
+        "path": "/root/tungn197/genAI/checkpoints/realisticVisionV60B1_v51HyperVAE.safetensors",
+        "type": "file",
+        "pipeline": "StableDiffusionPipeline"
+    },
+    "Anime (SD 1.5)": {
+        "path": "/root/tungn197/genAI/checkpoints/darkSushiMixMix_225D.safetensors",
+        "type": "file",
+        "pipeline": "StableDiffusionPipeline"
+    },
+    "Comic Book (SD 1.5)": {
+        "path": "/media/drive-2t/tungn197/checkpoints/realisticComicBook_v10.safetensors",
+        "type": "file",
+        "pipeline": "StableDiffusionPipeline"
+    },
+    "MajicMixRealisticV7 (SD 1.5 Focus on Asian face)": {
+        "path": "/root/tungn197/genAI/checkpoints/majicmixRealistic_v7.safetensors",
+        "type": "file",
+        "pipeline": "StableDiffusionPipeline"
+    },
+    "AniMeshFullV22 (SD 1.5)": {
+        "path": "/media/drive-2t/tungn197/checkpoints/animesh_FullV22.safetensors",
+        "type": "file",
+        "pipeline": "StableDiffusionPipeline"
+    },
+    "epiCRealism XL (SDXL 1.0)": {
+        "path": "/root/tungn197/genAI/checkpoints/epicrealismXL_v7FinalDestination.safetensors",
+        "type": "file",
+        "pipeline": "StableDiffusionXLPipeline"
+    },
+    "Juggernaut X Hyper (SDXL 1.0)": {
+        "path": "RunDiffusion/Juggernaut-X-Hyper",
+        "type": "pretrained",
+        "pipeline": "StableDiffusionXLPipeline"
+    }
+}
+AUTH_USER = [("admin", "admin")]
+DEVICE = "cuda:0"
+APP_THEME = gr.Theme.from_hub("ParityError/Interstellar")
+
+def read_md_file_to_string(file_path):
+    try:
+        with open(file_path, 'r', encoding='utf-8') as file:
+            file_content = file.read()
+        return file_content
+    except FileNotFoundError:
+        print(f"The file at {file_path} was not found.")
+    except Exception as e:
+        print(f"An error occurred: {e}")
+
+def nearest_divisible_by_8(n):
+    lower_multiple = (n // 8) * 8
+    upper_multiple = lower_multiple + 8
+    if (n - lower_multiple) < (upper_multiple - n):
+        return int(lower_multiple)
+    else:
+        return int(upper_multiple)
+
+def get_gpu_info():
+    gpus = GPUtil.getGPUs()
+    gpu_info = []
+    for gpu in gpus:
+        info = {
+            'id': gpu.id,
+            'name': gpu.name,
+            'driver_version': gpu.driver,
+            'total_memory': gpu.memoryTotal,  # In MB
+            'available_memory': gpu.memoryFree,  # In MB
+            'used_memory': gpu.memoryUsed,  # In MB
+            'temperature': gpu.temperature  # In Celsius
+        }
+        gpu_info.append(info)
+    return gpu_info
+
+def display_gpu_info():
+    info_list = []
+    gpus = get_gpu_info()
+    for info in gpus:
+        info_list.append(f"GPU {info['id']} ({info['name']}, Total: {info['total_memory']} MB, Available: {info['available_memory']} MB)")
+    return info_list
+
+GPUS = get_gpu_info()
+DISPLAYED_GPUS_INFO = []
+for info in GPUS:
+    DISPLAYED_GPUS_INFO.append(f"GPU {info['id']}")