Colab: added the ability to download models from civitai

fooocus_colab.ipynb

@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Run Fooocus"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -14,6 +21,94 @@
     "%cd /content/Fooocus\n",
     "!python entry_with_update.py --share\n"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Download checkpoints and LoRAs from civitai\n",
+    "to download checkpoints and LoRAs from civitai you have to run Fooocus first\n",
+    "\n",
+    "https://civitai.com/models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# put the link of the model you want to download (checkpoint or LoRA)\n",
+    "# link can specify a version id and if not specified the latest version will be downloaded\n",
+    "# url example without version id: https://civitai.com/models/133005/juggernaut-xl\n",
+    "# url example with version id: https://civitai.com/models/133005?modelVersionId=252902\n",
+    "\n",
+    "civitai_url = \"https://civitai.com/models/133005/juggernaut-xl\"\n",
+    "\n",
+    "# -----------------------------\n",
+    "import requests\n",
+    "from urllib.parse import urlparse\n",
+    "from urllib.parse import parse_qs\n",
+    "\n",
+    "allowed_types = ['Checkpoint', 'LORA']\n",
+    "save_locations = {\n",
+    "    'Checkpoint': '/content/Fooocus/models/checkpoints',\n",
+    "    'LORA': '/content/Fooocus/models/loras'\n",
+    "}\n",
+    "\n",
+    "parsed_url = urlparse(civitai_url)\n",
+    "\n",
+    "model_id = parsed_url.path.split('/')[parsed_url.path.split('/').index('models') + 1]\n",
+    "model_version_id = parse_qs(parsed_url.query).get('modelVersionId')\n",
+    "\n",
+    "url = \"https://civitai.com/api/v1/models/\" + model_id\n",
+    "response = requests.get(url)\n",
+    "\n",
+    "if response.status_code != 200:\n",
+    "  raise RuntimeError('model not found')\n",
+    "\n",
+    "data = response.json()\n",
+    "model_type = data.get('type')\n",
+    "\n",
+    "if model_type not in allowed_types:\n",
+    "  raise RuntimeError('model is not a checkpoint or LoRA')\n",
+    "\n",
+    "model_versions = data.get('modelVersions')\n",
+    "\n",
+    "selected_version = None\n",
+    "\n",
+    "if model_version_id:\n",
+    "  for model_version in model_versions:\n",
+    "    if str(model_version.get('id')) == model_version_id[0]:\n",
+    "      selected_version = model_version\n",
+    "else:\n",
+    "  selected_version = model_versions[0]\n",
+    "\n",
+    "if selected_version is None:\n",
+    "  raise RuntimeError(\"this version doesn't exist\")\n",
+    "\n",
+    "if \"SDXL\" not in selected_version.get('baseModel'):\n",
+    "  raise RuntimeError(\"this model is not SDXL\")\n",
+    "\n",
+    "files = selected_version.get('files')\n",
+    "primary_file = None\n",
+    "\n",
+    "for f in files:\n",
+    "  if f.get('primary'):\n",
+    "    primary_file = f\n",
+    "\n",
+    "download_url = primary_file.get('downloadUrl')\n",
+    "file_name = primary_file.get('name')\n",
+    "\n",
+    "LOCATION = save_locations[model_type]\n",
+    "%cd $LOCATION\n",
+    "\n",
+    "model_name = data.get('name')\n",
+    "selected_version_name = selected_version.get('name')\n",
+    "print(f'downloading {model_name} ({model_type} version {selected_version_name})')\n",
+    "\n",
+    "get_ipython().system(f'wget -O \"{file_name}\" \"{download_url}\"')"
+   ]
   }
  ],
  "metadata": {