mirror of https://github.com/hwchase17/langchain
Add Golden Query Tool (#7930)
**Description:** Golden Query is a wrapper on top of the [Golden Query API](https://docs.golden.com/reference/query-api) which enables programmatic access to query results on entities across Golden's Knowledge Base. For more information about Golden API, please see the [Golden API Getting Started](https://docs.golden.com/reference/getting-started) page. **Issue:** None **Dependencies:** requests(already present in project) **Tag maintainer:** @hinthornw Signed-off-by: Constantin Musca <constantin.musca@gmail.com>pull/8007/head
Constantin Musca
1 year ago
committed by
GitHub
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aea97efe8b
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# Golden Query
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>Golden Query is a wrapper on top of the [Golden Query API](https://docs.golden.com/reference/query-api) which enables programmatic access to query results on entities across Golden's Knowledge Base.
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>See the [Golden Query API docs](https://docs.golden.com/reference/query-api) for more information.
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This page covers how to use `Golden Query` within LangChain.
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## Installation and Setup
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- Go to the [Golden API docs](https://docs.golden.com/) to get an overview about the Golden API.
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- Create a Golden account if you don't have one on the [Golden Website](https://golden.com).
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- Get your API key from the [Golden API Settings](https://golden.com/settings/api) page.
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- Save your API key into GOLDEN_API_KEY env variable
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## Wrappers
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### Utility
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There exists a GoldenQueryAPIWrapper utility which wraps this API. To import this utility:
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```python
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from langchain.utilities.golden_query import GoldenQueryAPIWrapper
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```
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For a more detailed walkthrough of this wrapper, see [this notebook](/docs/modules/agents/tools/integrations/golden_query.html).
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### Tool
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You can also easily load this wrapper as a Tool (to use with an Agent).
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You can do this with:
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```python
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from langchain.agents import load_tools
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tools = load_tools(["golden-query"])
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```
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For more information on tools, see [this page](/docs/modules/agents/tools/).
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@ -0,0 +1,142 @@
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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "245a954a",
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"metadata": {},
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"source": [
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"# Golden Query\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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"- Create a Golden account if you don't have one on the [Golden Website](golden.com).\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": 5,
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"id": "34bb5968",
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"metadata": {},
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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": 6,
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"id": "ac4910f8",
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"metadata": {},
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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": 7,
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"id": "84b8f773",
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"metadata": {},
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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": 9,
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"id": "068991a6",
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"metadata": {},
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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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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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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": "3.9.13"
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},
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"vscode": {
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"interpreter": {
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"hash": "53f3bc57609c7a84333bb558594977aa5b4026b1d6070b93987956689e367341"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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"""Golden API toolkit."""
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from langchain.tools.golden_query.tool import GoldenQueryRun
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__all__ = [
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"GoldenQueryRun",
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]
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"""Tool for the Golden API."""
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from typing import Optional
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from langchain.callbacks.manager import (
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AsyncCallbackManagerForToolRun,
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CallbackManagerForToolRun,
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)
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from langchain.tools.base import BaseTool
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from langchain.utilities.golden_query import GoldenQueryAPIWrapper
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class GoldenQueryRun(BaseTool):
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"""Tool that adds the capability to query using the Golden API and get back JSON."""
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name = "Golden Query"
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description = (
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"A wrapper around Golden Query API."
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" Useful for getting entities that match"
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" a natural language query from Golden's Knowledge Base."
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"\nExample queries:"
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"\n- companies in nanotech"
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"\n- list of cloud providers starting in 2019"
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"\nInput should be the natural language query."
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"\nOutput is a paginated list of results or an error object"
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" in JSON format."
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)
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api_wrapper: GoldenQueryAPIWrapper
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def _run(
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self,
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query: str,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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) -> str:
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"""Use the Golden tool."""
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return self.api_wrapper.run(query)
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async def _arun(
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self,
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query: str,
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run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
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) -> str:
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"""Use the Golden tool asynchronously."""
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raise NotImplementedError("Golden does not support async")
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"""Util that calls Golden."""
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import json
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from typing import Dict, Optional
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import requests
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from pydantic import BaseModel, Extra, root_validator
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from langchain.utils import get_from_dict_or_env
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GOLDEN_BASE_URL = "https://golden.com"
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GOLDEN_TIMEOUT = 5000
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class GoldenQueryAPIWrapper(BaseModel):
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"""Wrapper for Golden.
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Docs for using:
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1. Go to https://golden.com and sign up for an account
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2. Get your API Key from https://golden.com/settings/api
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3. Save your API Key into GOLDEN_API_KEY env variable
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"""
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golden_api_key: Optional[str] = None
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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@root_validator()
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key and python package exists in environment."""
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golden_api_key = get_from_dict_or_env(
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values, "golden_api_key", "GOLDEN_API_KEY"
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)
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values["golden_api_key"] = golden_api_key
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return values
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def run(self, query: str) -> str:
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"""Run query through Golden Query API and return the JSON raw result."""
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headers = {"apikey": self.golden_api_key or ""}
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response = requests.post(
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f"{GOLDEN_BASE_URL}/api/v2/public/queries/",
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json={"prompt": query},
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headers=headers,
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timeout=GOLDEN_TIMEOUT,
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)
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if response.status_code != 201:
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return response.text
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content = json.loads(response.content)
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query_id = content["id"]
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response = requests.get(
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(
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f"{GOLDEN_BASE_URL}/api/v2/public/queries/{query_id}/results/"
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"?pageSize=10"
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),
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headers=headers,
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timeout=GOLDEN_TIMEOUT,
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)
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return response.text
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"""Integration test for Golden API Wrapper."""
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import json
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from langchain.utilities.golden_query import GoldenQueryAPIWrapper
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def test_call() -> None:
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"""Test that call gives the correct answer."""
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search = GoldenQueryAPIWrapper()
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output = json.loads(search.run("companies in nanotech"))
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assert len(output.get("results", [])) > 0
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