{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "69050aa19c302b38e5698575eaa553bf137b0cd391c976a74c6767f6c46ced66\n"
     ]
    }
   ],
   "source": [
    "!docker run -p \"6333:6333\" -p \"6334:6334\" --name \"rag-traversaal-qdrant\" --rm -d qdrant/qdrant:latest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CollectionsResponse(collections=[])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import qdrant_client\n",
    "\n",
    "client = qdrant_client.QdrantClient(host=\"localhost\", port=6333, grpc_port=6333)\n",
    "client.get_collections()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"summ_texts.txt\", \"r\", encoding=\"utf-8\") as file:\n",
    "    document = file.readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " '1a8282698e7346e5a9a81f381e496b08']"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client.add(\n",
    "    collection_name=\"knowledge-base\",\n",
    "    documents=document\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
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}