{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "efb41c9e450b5a29",
   "metadata": {},
   "source": [
    "# Cognee GraphRAG Simple Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "982b897a29a26f7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install cognee==0.1.39"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f51e92e9fdcf77b7",
   "metadata": {},
   "source": [
    " By default cognee uses OpenAI's gpt-4o-mini LLM model.\n",
    "\n",
    " Provide your OpenAI LLM API KEY in the step bellow. Here's a guide on how to get your [OpenAI API key](https://help.openai.com/en/articles/4936850-where-do-i-find-my-openai-api-key)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "initial_id",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "os.environ[\"LLM_API_KEY\"] = \"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1fec64bc573bb",
   "metadata": {},
   "source": [
    "In this step we'll get the location of the file to store and process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5805c346f03d8070",
   "metadata": {},
   "outputs": [],
   "source": [
    "current_directory = os.getcwd()\n",
    "file_path = os.path.join(current_directory, \"data\", \"alice_in_wonderland.txt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2826a80ca1ad0438",
   "metadata": {},
   "source": [
    "Give the file location to cognee to save it and process its contents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "875763366723ee48",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cognee\n",
    "await cognee.add(file_path)\n",
    "await cognee.cognify()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4944567387ec5821",
   "metadata": {},
   "source": [
    "Your data is ready to be queried:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29b3a1e3279100d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "await cognee.search(\"List me all the influential characters in Alice in Wonderland.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "883ce50d2d9dc584",
   "metadata": {},
   "outputs": [],
   "source": [
    "await cognee.search(\"How did Alice end up in Wonderland?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "677e1bc52aa078b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "await cognee.search(\"Tell me about Alice's personality.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd521e182fb66d49",
   "metadata": {},
   "source": [
    "Bonus: See your processed data visualized in a knowledge graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6effdae590b795d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import webbrowser\n",
    "import os\n",
    "from cognee.api.v1.visualize.visualize import visualize_graph\n",
    "html = await visualize_graph()\n",
    "home_dir = os.path.expanduser(\"~\")\n",
    "html_file = os.path.join(home_dir, \"graph_visualization.html\")\n",
    "display(html_file)\n",
    "webbrowser.open(f\"file://{html_file}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0945d6f1d962ab",
   "metadata": {},
   "source": [
    "For more examples and information on how Cognee GraphRAG works checkout our other more detailed notebooks."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Cognee Env",
   "language": "python",
   "name": "venv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.8"
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 },
 "nbformat": 4,
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}