Added a Jupyter notebook to test own videos

notesbooks/videorag.ipynb

@@ -0,0 +1,115 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c1e12bf6-a8ae-4fec-9fbd-99ea74bcc563",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import logging\n",
+    "import warnings\n",
+    "import multiprocessing\n",
+    "import nest_asyncio\n",
+    "    \n",
+    "nest_asyncio.apply()\n",
+    "\n",
+    "warnings.filterwarnings(\"ignore\")\n",
+    "logging.getLogger(\"httpx\").setLevel(logging.WARNING)\n",
+    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = '0'\n",
+    "\n",
+    "from videorag._llm import *\n",
+    "from videorag import VideoRAG, QueryParam\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f04cee24-fd8e-41dc-93ea-888229d2a9af",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "video_paths = [\n",
+    "        '/mnt/data3/AI/software/VideoRAG/Lexington/GMT20241112-164602_Recording_gallery_1280x720.mp4',\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1a8b5f05-12e8-4b53-b84c-e4555fc99022",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "multiprocessing.set_start_method('spawn')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7539e57b-11c2-42a9-b8f1-2363e0f561df",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "videorag = VideoRAG(cheap_model_func=ollama_mini_complete, best_model_func=ollama_complete, working_dir=f\"./videorag-workdir/lexington\")\n",
+    "videorag.insert_video(video_path_list=video_paths)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6a938da7-5c33-44a3-a66e-a2e07636ce70",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "videorag.load_caption_model(debug=False)\n",
+    "param = QueryParam(mode=\"videorag\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "15d51fb9-06e9-44e0-83ef-f3269c50480f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query = \"Can you summarize this video?\"\n",
+    "param.wo_reference = False\n",
+    "response = videorag.query(query=query, param=param)\n",
+    "print(response)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4d517d22-a482-47a1-a4ac-89d0042b016f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:videorag]",
+   "language": "python",
+   "name": "conda-env-videorag-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}