mirror of
				https://github.com/hwchase17/langchain.git
				synced 2025-11-04 10:10:09 +00:00 
			
		
		
		
	Huge thanks to @leo-gan for improving the document loaders notebooks --------- Co-authored-by: Leonid Ganeline <leo.gan.57@gmail.com>
		
			
				
	
	
		
			197 lines
		
	
	
		
			3.8 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
			
		
		
	
	
			197 lines
		
	
	
		
			3.8 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
{
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 "cells": [
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  {
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   "cell_type": "markdown",
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   "metadata": {},
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   "source": [
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    "# DuckDB\n",
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    "\n",
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    ">[DuckDB](https://duckdb.org/) is an in-process SQL OLAP database management system.\n",
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    "\n",
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    "Load a `DuckDB` query with one document per row."
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {
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    "tags": []
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   },
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   "outputs": [],
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   "source": [
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    "#!pip install duckdb"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 2,
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   "metadata": {
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    "tags": []
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   },
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   "outputs": [],
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   "source": [
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    "from langchain.document_loaders import DuckDBLoader"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 3,
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   "metadata": {
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    "tags": []
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   },
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   "outputs": [
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    {
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     "name": "stdout",
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     "output_type": "stream",
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     "text": [
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      "Writing example.csv\n"
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     ]
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    }
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   ],
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   "source": [
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    "%%file example.csv\n",
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    "Team,Payroll\n",
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    "Nationals,81.34\n",
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    "Reds,82.20"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 4,
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   "metadata": {
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    "tags": []
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   },
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   "outputs": [],
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   "source": [
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    "loader = DuckDBLoader(\"SELECT * FROM read_csv_auto('example.csv')\")\n",
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    "\n",
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    "data = loader.load()"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 5,
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   "metadata": {
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    "tags": []
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   },
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   "outputs": [
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    {
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     "name": "stdout",
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     "output_type": "stream",
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     "text": [
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      "[Document(page_content='Team: Nationals\\nPayroll: 81.34', metadata={}), Document(page_content='Team: Reds\\nPayroll: 82.2', metadata={})]\n"
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     ]
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    }
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   ],
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   "source": [
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    "print(data)"
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   ]
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  },
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  {
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   "cell_type": "markdown",
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   "metadata": {},
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   "source": [
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    "## Specifying Which Columns are Content vs Metadata"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 5,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "loader = DuckDBLoader(\n",
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    "    \"SELECT * FROM read_csv_auto('example.csv')\",\n",
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    "    page_content_columns=[\"Team\"],\n",
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    "    metadata_columns=[\"Payroll\"]\n",
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    ")\n",
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    "\n",
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    "data = loader.load()"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 6,
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   "metadata": {},
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   "outputs": [
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    {
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     "name": "stdout",
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     "output_type": "stream",
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     "text": [
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      "[Document(page_content='Team: Nationals', metadata={'Payroll': 81.34}), Document(page_content='Team: Reds', metadata={'Payroll': 82.2})]\n"
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     ]
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    }
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   ],
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   "source": [
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    "print(data)"
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   ]
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  },
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  {
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   "cell_type": "markdown",
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   "metadata": {},
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   "source": [
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    "## Adding Source to Metadata"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 7,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "loader = DuckDBLoader(\n",
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    "    \"SELECT Team, Payroll, Team As source FROM read_csv_auto('example.csv')\",\n",
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    "    metadata_columns=[\"source\"]\n",
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    ")\n",
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    "\n",
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    "data = loader.load()"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 8,
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   "metadata": {},
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   "outputs": [
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    {
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     "name": "stdout",
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     "output_type": "stream",
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     "text": [
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      "[Document(page_content='Team: Nationals\\nPayroll: 81.34\\nsource: Nationals', metadata={'source': 'Nationals'}), Document(page_content='Team: Reds\\nPayroll: 82.2\\nsource: Reds', metadata={'source': 'Reds'})]\n"
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     ]
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    }
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   ],
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   "source": [
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    "print(data)"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": []
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  }
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 ],
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 "metadata": {
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  "kernelspec": {
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   "display_name": "Python 3 (ipykernel)",
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   "language": "python",
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   "name": "python3"
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  },
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  "language_info": {
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   "codemirror_mode": {
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    "name": "ipython",
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    "version": 3
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   },
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   "file_extension": ".py",
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   "mimetype": "text/x-python",
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   "name": "python",
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   "nbconvert_exporter": "python",
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   "pygments_lexer": "ipython3",
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   "version": "3.10.6"
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  }
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 },
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 "nbformat": 4,
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 "nbformat_minor": 4
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}
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