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	updating the documentation to be consistent for Golden query tool and have a better introduction to the tool
		
			
				
	
	
		
			160 lines
		
	
	
		
			5.7 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
			
		
		
	
	
			160 lines
		
	
	
		
			5.7 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
{
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  "cells": [
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    {
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      "cell_type": "markdown",
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      "id": "245a954a",
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      "metadata": {
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        "id": "245a954a"
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      },
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      "source": [
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        "# Golden Query\n",
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        "\n",
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        ">[Golden](https://golden.com) provides a set of natural language APIs for querying and enrichment using the Golden Knowledge Graph e.g. queries such as: `Products from OpenAI`, `Generative ai companies with series a funding`, and `rappers who invest` can be used to retrieve structured data about relevant entities.\n",
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        ">\n",
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        ">The `golden-query` langchain tool is a wrapper on top of the [Golden Query API](https://docs.golden.com/reference/query-api) which enables programmatic access to these results.\n",
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        ">See the [Golden Query API docs](https://docs.golden.com/reference/query-api) for more information.\n",
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        "\n",
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        "\n",
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        "This notebook goes over how to use the `golden-query` tool.\n",
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        "\n",
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        "- Go to the [Golden API docs](https://docs.golden.com/) to get an overview about the Golden API.\n",
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        "- Get your API key from the [Golden API Settings](https://golden.com/settings/api) page.\n",
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        "- Save your API key into GOLDEN_API_KEY env variable"
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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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      "id": "34bb5968",
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      "metadata": {
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        "id": "34bb5968"
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      },
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      "outputs": [],
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      "source": [
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        "import os\n",
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        "\n",
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        "os.environ[\"GOLDEN_API_KEY\"] = \"\""
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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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      "id": "ac4910f8",
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      "metadata": {
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        "id": "ac4910f8"
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      },
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      "outputs": [],
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      "source": [
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        "from langchain.utilities.golden_query import GoldenQueryAPIWrapper"
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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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      "id": "84b8f773",
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      "metadata": {
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        "id": "84b8f773"
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      },
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      "outputs": [],
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      "source": [
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        "golden_query = GoldenQueryAPIWrapper()"
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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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      "id": "068991a6",
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      "metadata": {
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        "id": "068991a6",
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        "outputId": "c5cdc6ec-03cf-4084-cc6f-6ae792d91d39"
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      },
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      "outputs": [
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        {
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          "data": {
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            "text/plain": [
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              "{'results': [{'id': 4673886,\n",
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              "   'latestVersionId': 60276991,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'Samsung', 'citations': []}]}]},\n",
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              "  {'id': 7008,\n",
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              "   'latestVersionId': 61087416,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'Intel', 'citations': []}]}]},\n",
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              "  {'id': 24193,\n",
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              "   'latestVersionId': 60274482,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'Texas Instruments', 'citations': []}]}]},\n",
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              "  {'id': 1142,\n",
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              "   'latestVersionId': 61406205,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'Advanced Micro Devices', 'citations': []}]}]},\n",
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              "  {'id': 193948,\n",
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              "   'latestVersionId': 58326582,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'Freescale Semiconductor', 'citations': []}]}]},\n",
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              "  {'id': 91316,\n",
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              "   'latestVersionId': 60387380,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'Agilent Technologies', 'citations': []}]}]},\n",
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              "  {'id': 90014,\n",
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              "   'latestVersionId': 60388078,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'Novartis', 'citations': []}]}]},\n",
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              "  {'id': 237458,\n",
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              "   'latestVersionId': 61406160,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'Analog Devices', 'citations': []}]}]},\n",
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              "  {'id': 3941943,\n",
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              "   'latestVersionId': 60382250,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'AbbVie Inc.', 'citations': []}]}]},\n",
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              "  {'id': 4178762,\n",
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              "   'latestVersionId': 60542667,\n",
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              "   'properties': [{'predicateId': 'name',\n",
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              "     'instances': [{'value': 'IBM', 'citations': []}]}]}],\n",
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              " 'next': 'https://golden.com/api/v2/public/queries/59044/results/?cursor=eyJwb3NpdGlvbiI6IFsxNzYxNiwgIklCTS04M1lQM1oiXX0%3D&pageSize=10',\n",
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              " 'previous': None}"
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            ]
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          },
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          "execution_count": 9,
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          "metadata": {},
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          "output_type": "execute_result"
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        }
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      ],
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      "source": [
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        "import json\n",
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        "\n",
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        "json.loads(golden_query.run(\"companies in nanotech\"))"
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      ]
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    }
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  ],
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