stable_bypass_by_jamisson_tavares_english_version.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "This is a version of stabble diffusion, it replaces the grado service with ngrok, and hides all types of cell image generation history, to avoid suspensions.\n",
        "\n",
        "\n",
        "\n",
        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)"
      ],
      "metadata": {
        "id": "KQb42wbxHER0"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f_Ho4YCnKGET",
        "outputId": "624f30d0-89a5-4b66-8504-5a21604f0bd0",
        "cellView": "form"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "fatal: destination path 'stable-diffusion-webui' already exists and is not an empty directory.\n",
            "Requirement already satisfied: GitPython in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 1)) (3.1.43)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 2)) (10.4.0)\n",
            "Requirement already satisfied: accelerate in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 3)) (0.34.2)\n",
            "Requirement already satisfied: blendmodes in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 5)) (2024.1.1)\n",
            "Requirement already satisfied: clean-fid in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 6)) (0.1.35)\n",
            "Requirement already satisfied: diskcache in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 7)) (5.6.3)\n",
            "Requirement already satisfied: einops in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 8)) (0.8.0)\n",
            "Requirement already satisfied: facexlib in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 9)) (0.3.0)\n",
            "Requirement already satisfied: fastapi>=0.90.1 in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 10)) (0.115.2)\n",
            "Requirement already satisfied: gradio==3.41.2 in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 11)) (3.41.2)\n",
            "Requirement already satisfied: inflection in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 12)) (0.5.1)\n",
            "Requirement already satisfied: jsonmerge in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 13)) (1.9.2)\n",
            "Requirement already satisfied: kornia in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 14)) (0.7.3)\n",
            "Requirement already satisfied: lark in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 15)) (1.2.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 16)) (1.26.4)\n",
            "Requirement already satisfied: omegaconf in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 17)) (2.3.0)\n",
            "Requirement already satisfied: open-clip-torch in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 18)) (2.26.1)\n",
            "Requirement already satisfied: piexif in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 20)) (1.1.3)\n",
            "Requirement already satisfied: protobuf==3.20.0 in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 21)) (3.20.0)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 22)) (5.9.5)\n",
            "Requirement already satisfied: pytorch_lightning in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 23)) (2.4.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 24)) (2.32.3)\n",
            "Requirement already satisfied: resize-right in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 25)) (0.0.2)\n",
            "Requirement already satisfied: safetensors in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 27)) (0.4.5)\n",
            "Requirement already satisfied: scikit-image>=0.19 in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 28)) (0.24.0)\n",
            "Requirement already satisfied: tomesd in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 29)) (0.1.3)\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 30)) (2.4.1+cu121)\n",
            "Requirement already satisfied: torchdiffeq in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 31)) (0.2.4)\n",
            "Requirement already satisfied: torchsde in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 32)) (0.2.6)\n",
            "Requirement already satisfied: transformers==4.30.2 in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 33)) (4.30.2)\n",
            "Requirement already satisfied: pillow-avif-plugin==1.4.3 in /usr/local/lib/python3.10/dist-packages (from -r /content/stable-diffusion-webui/requirements.txt (line 34)) (1.4.3)\n",
            "Requirement already satisfied: aiofiles<24.0,>=22.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (23.2.1)\n",
            "Requirement already satisfied: altair<6.0,>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (4.2.2)\n",
            "Requirement already satisfied: ffmpy in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (0.4.0)\n",
            "Requirement already satisfied: gradio-client==0.5.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (0.5.0)\n",
            "Requirement already satisfied: httpx in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (0.27.2)\n",
            "Requirement already satisfied: huggingface-hub>=0.14.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (0.24.7)\n",
            "Requirement already satisfied: importlib-resources<7.0,>=1.3 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (6.4.5)\n",
            "Requirement already satisfied: jinja2<4.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (3.1.4)\n",
            "Requirement already satisfied: markupsafe~=2.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (2.1.5)\n",
            "Requirement already satisfied: matplotlib~=3.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (3.7.1)\n",
            "Requirement already satisfied: orjson~=3.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (3.10.7)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (24.1)\n",
            "Requirement already satisfied: pandas<3.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (2.2.2)\n",
            "Requirement already satisfied: pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,<3.0.0,>=1.7.4 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (2.9.2)\n",
            "Requirement already satisfied: pydub in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (0.25.1)\n",
            "Requirement already satisfied: python-multipart in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (0.0.12)\n",
            "Requirement already satisfied: pyyaml<7.0,>=5.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (6.0.2)\n",
            "Requirement already satisfied: semantic-version~=2.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (2.10.0)\n",
            "Requirement already satisfied: typing-extensions~=4.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (4.12.2)\n",
            "Requirement already satisfied: uvicorn>=0.14.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (0.31.1)\n",
            "Requirement already satisfied: websockets<12.0,>=10.0 in /usr/local/lib/python3.10/dist-packages (from gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (11.0.3)\n",
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            "Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>=2022.5.0->pytorch_lightning->-r /content/stable-diffusion-webui/requirements.txt (line 23)) (4.0.3)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.41.0,>=0.37.2->fastapi>=0.90.1->-r /content/stable-diffusion-webui/requirements.txt (line 10)) (1.2.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib~=3.0->gradio==3.41.2->-r /content/stable-diffusion-webui/requirements.txt (line 11)) (1.16.0)\n"
          ]
        }
      ],
      "source": [
        "# @title Install requirements ⚙️\n",
        "# Clone the Stable Diffusion WebUI repository\n",
        "!git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git\n",
        "\n",
        "# Install requirements\n",
        "!pip install -r /content/stable-diffusion-webui/requirements.txt\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Insert link to download checkpoint models\n",
        "!pip install tqdm\n",
        "import os\n",
        "import requests\n",
        "from tqdm import tqdm\n",
        "from urllib.parse import urlparse\n",
        "\n",
        "# Function to create directories if they do not exist\n",
        "def create_directory(path):\n",
        "    if not os.path.exists(path):\n",
        "        os.makedirs(path)\n",
        "        print(f\"Folder {path} successfully created!\")\n",
        "    else:\n",
        "        print(f\"Folder {path} already exists.\")\n",
        "\n",
        "# Function to get the correct file name from the response header\n",
        "def get_filename_from_response(response, model_url):\n",
        "    # First, try to get the file name from the 'Content-Disposition' header\n",
        "    if 'content-disposition' in response.headers:\n",
        "        content_disposition = response.headers['content-disposition']\n",
        "        if 'filename=' in content_disposition:\n",
        "            # Extract the file name between quotes or after 'filename='\n",
        "            filename = content_disposition.split('filename=')[-1].strip('\"')\n",
        "            return filename\n",
        "\n",
        "    # If no 'Content-Disposition', use the URL's name\n",
        "    return os.path.basename(urlparse(model_url).path)\n",
        "\n",
        "# Function to download the checkpoint model with a progress bar\n",
        "def download_model_with_progress(model_url, api_key=None):\n",
        "    # Create directory for checkpoint models\n",
        "    create_directory(\"/content/stable-diffusion-webui/models/Stable-diffusion\")\n",
        "\n",
        "    # Headers to include the API Key if necessary\n",
        "    headers = {}\n",
        "    if api_key:\n",
        "        headers = {'Authorization': f'Bearer {api_key}'}\n",
        "\n",
        "    # Download with requests and tqdm\n",
        "    response = requests.get(model_url, stream=True, headers=headers)\n",
        "\n",
        "    # Check if access is allowed\n",
        "    if response.status_code == 401:  # Unauthorized (API key needed)\n",
        "        print(\"Access denied! The Civitai API key is required.\")\n",
        "        return\n",
        "\n",
        "    # Get the correct file name\n",
        "    model_name = get_filename_from_response(response, model_url)\n",
        "\n",
        "    # Full path to save the file\n",
        "    model_path = os.path.join(\"/content/stable-diffusion-webui/models/Stable-diffusion\", model_name)\n",
        "\n",
        "    # Display download message\n",
        "    print(f\"Downloading model {model_name} from {model_url}...\")\n",
        "\n",
        "    total_size = int(response.headers.get('content-length', 0))\n",
        "\n",
        "    # Use tqdm for progress bar\n",
        "    with open(model_path, 'wb') as file, tqdm(\n",
        "        desc=model_name,\n",
        "        total=total_size,\n",
        "        unit='iB',\n",
        "        unit_scale=True,\n",
        "        unit_divisor=1024,\n",
        "    ) as bar:\n",
        "        for data in response.iter_content(chunk_size=1024):\n",
        "            file.write(data)\n",
        "            bar.update(len(data))\n",
        "\n",
        "    print(f\"\\nModel {model_name} saved to {model_path}.\")\n",
        "\n",
        "# Function to detect if the URL is from Civitai\n",
        "def is_civitai_url(model_url):\n",
        "    parsed_url = urlparse(model_url)\n",
        "    return \"civitai.com\" in parsed_url.netloc\n",
        "\n",
        "# Field for the user to input the model URL\n",
        "model_url = input(\"Enter the model download link: \")\n",
        "\n",
        "# Check if the URL is from Civitai and if an API key is needed\n",
        "if is_civitai_url(model_url):\n",
        "    api_key = input(\"Enter your Civitai API key (if not needed, press Enter): \")\n",
        "    download_model_with_progress(model_url, api_key)\n",
        "else:\n",
        "    download_model_with_progress(model_url)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 373
        },
        "cellView": "form",
        "id": "NbhmRQm47v26",
        "outputId": "db56e7a2-ba7b-431e-c866-ea0402b72441"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (4.66.5)\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "Interrupted by user",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-1-bd713ab8a898>\u001b[0m in \u001b[0;36m<cell line: 78>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     76\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     77\u001b[0m \u001b[0;31m# Field for the user to input the model URL\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 78\u001b[0;31m \u001b[0mmodel_url\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Enter the model download link: \"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     79\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     80\u001b[0m \u001b[0;31m# Check if the URL is from Civitai and if an API key is needed\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\u001b[0m in \u001b[0;36mraw_input\u001b[0;34m(self, prompt)\u001b[0m\n\u001b[1;32m    849\u001b[0m                 \u001b[0;34m\"raw_input was called, but this frontend does not support input requests.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    850\u001b[0m             )\n\u001b[0;32m--> 851\u001b[0;31m         return self._input_request(str(prompt),\n\u001b[0m\u001b[1;32m    852\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parent_ident\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    853\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parent_header\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\u001b[0m in \u001b[0;36m_input_request\u001b[0;34m(self, prompt, ident, parent, password)\u001b[0m\n\u001b[1;32m    893\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    894\u001b[0m                 \u001b[0;31m# re-raise KeyboardInterrupt, to truncate traceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 895\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Interrupted by user\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    896\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    897\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwarning\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Invalid Message:\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: Interrupted by user"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Insert link for downloading LoRA models\n",
        "!pip install tqdm\n",
        "import os\n",
        "import requests\n",
        "from tqdm import tqdm\n",
        "from urllib.parse import urlparse\n",
        "\n",
        "# Function to create directories if they do not exist\n",
        "def create_directory(path):\n",
        "    if not os.path.exists(path):\n",
        "        os.makedirs(path)\n",
        "        print(f\"Folder {path} successfully created!\")\n",
        "    else:\n",
        "        print(f\"Folder {path} already exists.\")\n",
        "\n",
        "# Function to get the correct file name from the response header\n",
        "def get_filename_from_response(response, model_url):\n",
        "    # First, try to get the file name from the 'Content-Disposition' header\n",
        "    if 'content-disposition' in response.headers:\n",
        "        content_disposition = response.headers['content-disposition']\n",
        "        if 'filename=' in content_disposition:\n",
        "            # Extracting the file name between quotes or after 'filename='\n",
        "            filename = content_disposition.split('filename=')[-1].strip('\"')\n",
        "            return filename\n",
        "\n",
        "    # If no 'Content-Disposition', use the URL's name\n",
        "    return os.path.basename(urlparse(model_url).path)\n",
        "\n",
        "# Function to download the checkpoint model with a progress bar\n",
        "def download_model_with_progress(model_url, api_key=None):\n",
        "    # Create directory for checkpoint models\n",
        "    create_directory(\"/content/stable-diffusion-webui/models/Lora\")\n",
        "\n",
        "    # Headers to include the API Key if necessary\n",
        "    headers = {}\n",
        "    if api_key:\n",
        "        headers = {'Authorization': f'Bearer {api_key}'}\n",
        "\n",
        "    # Download with requests and tqdm\n",
        "    response = requests.get(model_url, stream=True, headers=headers)\n",
        "\n",
        "    # Check if access is allowed\n",
        "    if response.status_code == 401:  # Unauthorized (API key needed)\n",
        "        print(\"Access denied! The Civitai API key is required.\")\n",
        "        return\n",
        "\n",
        "    # Get the correct file name\n",
        "    model_name = get_filename_from_response(response, model_url)\n",
        "\n",
        "    # Full path to save the file\n",
        "    model_path = os.path.join(\"/content/stable-diffusion-webui/models/Lora\", model_name)\n",
        "\n",
        "    # Display download message\n",
        "    print(f\"Downloading model {model_name} from {model_url}...\")\n",
        "\n",
        "    total_size = int(response.headers.get('content-length', 0))\n",
        "\n",
        "    # Use tqdm for progress bar\n",
        "    with open(model_path, 'wb') as file, tqdm(\n",
        "        desc=model_name,\n",
        "        total=total_size,\n",
        "        unit='iB',\n",
        "        unit_scale=True,\n",
        "        unit_divisor=1024,\n",
        "    ) as bar:\n",
        "        for data in response.iter_content(chunk_size=1024):\n",
        "            file.write(data)\n",
        "            bar.update(len(data))\n",
        "\n",
        "    print(f\"\\nModel {model_name} saved to {model_path}.\")\n",
        "\n",
        "# Function to detect if the URL is from Civitai\n",
        "def is_civitai_url(model_url):\n",
        "    parsed_url = urlparse(model_url)\n",
        "    return \"civitai.com\" in parsed_url.netloc\n",
        "\n",
        "# Field for the user to input the model URL\n",
        "model_url = input(\"Enter the model download link: \")\n",
        "\n",
        "# Check if the URL is from Civitai and if an API key is needed\n",
        "if is_civitai_url(model_url):\n",
        "    api_key = input(\"Enter your Civitai API key (if not needed, press Enter): \")\n",
        "    download_model_with_progress(model_url, api_key)\n",
        "else:\n",
        "    download_model_with_progress(model_url)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rzbd9rtwZffB",
        "outputId": "52de5b3c-c557-4f32-c840-eff4a064a252",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (4.66.5)\n",
            "Insira o link de download do modelo: https://civitai.com/api/download/models/60568?type=Model&format=SafeTensor\n",
            "Insira a chave API do Civitai (se não precisar, pressione Enter): \n",
            "Pasta /content/stable-diffusion-webui/models/Lora criada com sucesso!\n",
            "Baixando o modelo animemix_v3_offset.safetensors de https://civitai.com/api/download/models/60568?type=Model&format=SafeTensor...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "animemix_v3_offset.safetensors: 100%|██████████| 144M/144M [00:04<00:00, 34.6MiB/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Modelo animemix_v3_offset.safetensors salvo em /content/stable-diffusion-webui/models/Lora/animemix_v3_offset.safetensors.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown ###🟢 Connect to Ngrok\n",
        "#@markdown Enter your Ngrok token below:\n",
        "\n",
        "Ngrok_token = \"\"  # @param {type:\"string\"}\n",
        "Ngrok_domain = \"\"  # Optional, leave empty if you don't have a domain\n",
        "port = 7860\n",
        "HOME_FOLDER = \"/content\"\n",
        "\n",
        "# -----------------\n",
        "\n",
        "!pip install pyngrok==6.1.0  # Downgrade to a version that supports ngrok tunneling\n",
        "\n",
        "from pyngrok import ngrok\n",
        "import gc\n",
        "import sys\n",
        "import os\n",
        "\n",
        "# Function to hide outputs (image and prompt history)\n",
        "class HiddenPrints:\n",
        "    def __enter__(self):\n",
        "        self._original_stdout = sys.stdout  # Save the original output\n",
        "        sys.stdout = open(os.devnull, 'w')  # Redirect output to devnull\n",
        "\n",
        "    def __exit__(self, exc_type, exc_val, exc_tb):\n",
        "        sys.stdout.close()  # Close devnull\n",
        "        sys.stdout = self._original_stdout  # Restore the original output\n",
        "\n",
        "gc.collect()\n",
        "\n",
        "# Check if the token has been entered\n",
        "if Ngrok_token.strip():\n",
        "    try:\n",
        "        ngrok.set_auth_token(Ngrok_token)\n",
        "        ngrok.kill()  # Terminate existing connections\n",
        "        srv = ngrok.connect(port)  # Connect to the specified port\n",
        "        print(f\"Ngrok tunnel active at: {srv.public_url}\")\n",
        "\n",
        "        # Command to start the Stable Diffusion WebUI, hiding the history\n",
        "        with HiddenPrints():  # Hide image generation history\n",
        "            !echo -e \"A\\nN\" | python /content/stable-diffusion-webui/launch.py\n",
        "\n",
        "    except Exception as e:\n",
        "        print(f\"Error starting the ngrok tunnel: {e}\")\n",
        "else:\n",
        "    print('An ngrok token is required. Sign up at https://ngrok.com and enter the token above.')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JwDPU5T9XI1d",
        "outputId": "041f12da-dff3-41f1-80ca-1fe32b129cf6",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: pyngrok==6.1.0 in /usr/local/lib/python3.10/dist-packages (6.1.0)\n",
            "Requirement already satisfied: PyYAML in /usr/local/lib/python3.10/dist-packages (from pyngrok==6.1.0) (6.0.2)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:pyngrok.process.ngrok:t=2024-10-13T18:16:29+0000 lvl=warn msg=\"ngrok config file found at legacy location, move to XDG location\" xdg_path=/root/.config/ngrok/ngrok.yml legacy_path=/root/.ngrok2/ngrok.yml\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Túnel ngrok ativo em: https://2f68-34-16-193-134.ngrok-free.app\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:pyngrok.process.ngrok:t=2024-10-13T18:16:53+0000 lvl=warn msg=\"failed to open private leg\" id=c7ec701266c1 privaddr=localhost:7860 err=\"dial tcp 127.0.0.1:7860: connect: connection refused\"\n",
            "WARNING:pyngrok.process.ngrok:t=2024-10-13T18:16:54+0000 lvl=warn msg=\"failed to open private leg\" id=749bc1c136ba privaddr=localhost:7860 err=\"dial tcp 127.0.0.1:7860: connect: connection refused\"\n",
            "WARNING:pyngrok.process.ngrok:t=2024-10-13T18:17:14+0000 lvl=warn msg=\"failed to open private leg\" id=10af809272ee privaddr=localhost:7860 err=\"dial tcp 127.0.0.1:7860: connect: connection refused\"\n",
            "WARNING:pyngrok.process.ngrok:t=2024-10-13T18:17:23+0000 lvl=warn msg=\"failed to open private leg\" id=8be387ff5c0a privaddr=localhost:7860 err=\"dial tcp 127.0.0.1:7860: connect: connection refused\"\n"
          ]
        }
      ]
    }
  ]
}