langchain/docs/extras/integrations/document_loaders/wikipedia.ipynb

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    "# Wikipedia\n",
    "\n",
    ">[Wikipedia](https://wikipedia.org/) is a multilingual free online encyclopedia written and maintained by a community of volunteers, known as Wikipedians, through open collaboration and using a wiki-based editing system called MediaWiki. `Wikipedia` is the largest and most-read reference work in history.\n",
    "\n",
    "This notebook shows how to load wiki pages from `wikipedia.org` into the Document format that we use downstream."
   ]
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   "source": [
    "## Installation"
   ]
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   "source": [
    "First, you need to install `wikipedia` python package."
   ]
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   "source": [
    "#!pip install wikipedia"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## Examples"
   ]
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   "source": [
    "`WikipediaLoader` has these arguments:\n",
    "- `query`: free text which used to find documents in Wikipedia\n",
    "- optional `lang`: default=\"en\". Use it to search in a specific language part of Wikipedia\n",
    "- optional `load_max_docs`: default=100. Use it to limit number of downloaded documents. It takes time to download all 100 documents, so use a small number for experiments. There is a hard limit of 300 for now.\n",
    "- optional `load_all_available_meta`: default=False. By default only the most important fields downloaded: `Published` (date when document was published/last updated), `title`, `Summary`. If True, other fields also downloaded."
   ]
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  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9bfd5e46",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.document_loaders import WikipediaLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "700e4ef2",
   "metadata": {},
   "outputs": [],
   "source": [
    "docs = WikipediaLoader(query=\"HUNTER X HUNTER\", load_max_docs=2).load()\n",
    "len(docs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8977bac0-0042-4f23-9754-247dbd32439b",
   "metadata": {
    "tags": []
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   "outputs": [],
   "source": [
    "docs[0].metadata  # meta-information of the Document"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46969806-45a9-4c4d-a61b-cfb9658fc9de",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "docs[0].page_content[:400]  # a content of the Document"
   ]
  }
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