{
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import clear_output\n",
        "!git clone https://github.com/Ysb321/ImgGen\n",
        "!pip install -r /content/ImgGen/requirements.txt\n",
        "clear_output()\n"
      ],
      "metadata": {
        "id": "p6WhlbJGlcKP"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Default Model (Important to run)\n",
        "import os\n",
        "import requests\n",
        "\n",
        "def download_civitai_model(bearer_token, download_url, save_path):\n",
        "  \"\"\"\n",
        "  Downloads a model from Civitai using a bearer token.\n",
        "\n",
        "  Args:\n",
        "    bearer_token: Your Civitai bearer token.\n",
        "    download_url: The URL of the model to download.\n",
        "    save_path: The full path to save the downloaded file.\n",
        "  \"\"\"\n",
        "  headers = {\"Authorization\": f\"Bearer {bearer_token}\"}\n",
        "  response = requests.get(download_url, headers=headers, stream=True)\n",
        "\n",
        "  if response.status_code == 200:\n",
        "    os.makedirs(os.path.dirname(save_path), exist_ok=True)  # Create directories if they don't exist\n",
        "    with open(save_path, \"wb\") as f:\n",
        "      for chunk in response.iter_content(chunk_size=1024):\n",
        "        if chunk:\n",
        "          f.write(chunk)\n",
        "    print(f\"File downloaded successfully to: {save_path}\")\n",
        "  else:\n",
        "    print(f\"Download failed with status code: {response.status_code}\")\n",
        "\n",
        "# Example usage:\n",
        "bearer_token = \"6748e0f8e6085cd9349551385ce8943a\"\n",
        "download_url = \"https://civitai.com/api/download/models/909781?type=Model&format=SafeTensor&size=full&fp=fp16\"\n",
        "save_path = \"/content/models/default.safetensors\"\n",
        "\n",
        "download_civitai_model(bearer_token, download_url, save_path)"
      ],
      "metadata": {
        "id": "NXQ7VYCFjux3",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Model Download\n",
        "import os\n",
        "import requests\n",
        "\n",
        "def download_civitai_model(bearer_token, download_url, save_path):\n",
        "  \"\"\"\n",
        "  Downloads a model from Civitai using a bearer token.\n",
        "\n",
        "  Args:\n",
        "    bearer_token: Your Civitai bearer token.\n",
        "    download_url: The URL of the model to download.\n",
        "    save_path: The full path to save the downloaded file.\n",
        "  \"\"\"\n",
        "  headers = {\"Authorization\": f\"Bearer {bearer_token}\"}\n",
        "  response = requests.get(download_url, headers=headers, stream=True)\n",
        "\n",
        "  if response.status_code == 200:\n",
        "    os.makedirs(os.path.dirname(save_path), exist_ok=True)  # Create directories if they don't exist\n",
        "    with open(save_path, \"wb\") as f:\n",
        "      for chunk in response.iter_content(chunk_size=1024):\n",
        "        if chunk:\n",
        "          f.write(chunk)\n",
        "    print(f\"File downloaded successfully to: {save_path}\")\n",
        "  else:\n",
        "    print(f\"Download failed with status code: {response.status_code}\")\n",
        "\n",
        "# Example usage:\n",
        "bearer_token = \"6748e0f8e6085cd9349551385ce8943a\"\n",
        "download_url = \"https://civitai.com/api/download/models/555687?type=Model&format=SafeTensor&size=pruned&fp=fp16\" # @param {type: \"string\"}\n",
        "model_name = \"paintjob\" # @param {type: \"string\"}\n",
        "save_path = f\"/content/models/{model_name}.safetensors\"\n",
        "\n",
        "download_civitai_model(bearer_token, download_url, save_path)"
      ],
      "metadata": {
        "cellView": "form",
        "id": "1jP2wKeeksGo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Lora Download\n",
        "\n",
        "import os\n",
        "import requests\n",
        "\n",
        "def download_civitai_model(bearer_token, download_url, save_path):\n",
        "  \"\"\"\n",
        "  Downloads a model from Civitai using a bearer token.\n",
        "\n",
        "  Args:\n",
        "    bearer_token: Your Civitai bearer token.\n",
        "    download_url: The URL of the model to download.\n",
        "    save_path: The full path to save the downloaded file.\n",
        "  \"\"\"\n",
        "  headers = {\"Authorization\": f\"Bearer {bearer_token}\"}\n",
        "  response = requests.get(download_url, headers=headers, stream=True)\n",
        "\n",
        "  if response.status_code == 200:\n",
        "    os.makedirs(os.path.dirname(save_path), exist_ok=True)  # Create directories if they don't exist\n",
        "    with open(save_path, \"wb\") as f:\n",
        "      for chunk in response.iter_content(chunk_size=1024):\n",
        "        if chunk:\n",
        "          f.write(chunk)\n",
        "    print(f\"File downloaded successfully to: {save_path}\")\n",
        "  else:\n",
        "    print(f\"Download failed with status code: {response.status_code}\")\n",
        "\n",
        "# Example usage:\n",
        "bearer_token = \"6748e0f8e6085cd9349551385ce8943a\"\n",
        "download_url = \"https://civitai.com/api/download/models/378950?type=Model&format=SafeTensor\" # @param {type: \"string\"}\n",
        "model_name = \"styles\" # @param {type: \"string\"}\n",
        "save_path = f\"/content/lora/{model_name}.safetensors\"\n",
        "\n",
        "download_civitai_model(bearer_token, download_url, save_path)"
      ],
      "metadata": {
        "cellView": "form",
        "id": "7vHNtfWSpbKN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Run\n",
        "!python /content/ImgGen/main.py"
      ],
      "metadata": {
        "id": "_E4CYZfAmqrw",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Zip file Creater\n",
        "import os\n",
        "import zipfile\n",
        "from google.colab import files\n",
        "\n",
        "def zip_folder(folder_path, output_zip_path):\n",
        "  \"\"\"Zips the contents of a folder into a zip file.\n",
        "\n",
        "  Args:\n",
        "    folder_path: The path to the folder to be zipped.\n",
        "    output_zip_path: The path to the output zip file.\n",
        "  \"\"\"\n",
        "  # Use zipfile for creating zip files\n",
        "  with zipfile.ZipFile(output_zip_path, 'w') as zip_file:\n",
        "    for root, _, files in os.walk(folder_path):\n",
        "      for file in files:\n",
        "        file_path = os.path.join(root, file)\n",
        "        zip_file.write(file_path, os.path.relpath(file_path, folder_path))\n",
        "\n",
        "# Replace with the actual path to your folder\n",
        "folder_to_zip = \"/content/images\"\n",
        "output_zip_file = \"/content/images.zip\"\n",
        "\n",
        "zip_folder(folder_to_zip, output_zip_file)"
      ],
      "metadata": {
        "id": "Sjx_A0TNyeAS",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!curl -L -H \"Content-Type: application/json\" -H \"Authorization: Bearer 6748e0f8e6085cd9349551385ce8943a\" -o /content/ImgGen/model_link.safetensors https://civitai.com/api/download/models/909781?type=Model&format=SafeTensor&size=full&fp=fp16"
      ],
      "metadata": {
        "id": "aIa50T3Wz-kj"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}