SearchApi
这份笔记展示了如何使用 SearchApi 来搜索网络。请访问 https://www.searchapi.io/ 注册一个免费账户并获取 API 密钥。
import os
os.environ["SEARCHAPI_API_KEY"] = ""
from langchain_community.utilities import SearchApiAPIWrapper
search = SearchApiAPIWrapper()
search.run("奥巴马的名字是什么？")
'巴拉克·侯赛因·奥巴马二世'
作为自问自答链的一部分使用
os.environ["OPENAI_API_KEY"] = ""
from langchain.agents import AgentType, initialize_agent
from langchain_community.utilities import SearchApiAPIWrapper
from langchain_core.tools import Tool
from langchain_openai import OpenAI
llm = OpenAI(temperature=0)
search = SearchApiAPIWrapper()
tools = [
Tool(
name="Intermediate Answer",
func=search.run,
description="useful for when you need to ask with search",
)
]
self_ask_with_search = initialize_agent(
tools, llm, agent=AgentType.SELF_ASK_WITH_SEARCH, verbose=True
)
self_ask_with_search.run("柏拉图、苏格拉底或亚里士多德中谁活得更久？")
> 进入新的 AgentExecutor 链...
是的。
后续问题：柏拉图去世时多大年纪？
中间答案：八十
后续问题：苏格拉底去世时多大年纪？
中间答案：苏格拉底
出生：约公元前470年 雅典阿洛佩克区
去世：公元前399年（约71岁） 雅典
死因：被迫自杀服毒
配偶：克西安蒂佩，米尔托
后续问题：亚里士多德去世时多大年纪？
中间答案：62岁
所以最终答案是：柏拉图
> 链结束。
'柏拉图'
自定义参数
SearchApi 包装器可以定制使用不同的引擎，比如 Google News、Google Jobs、Google Scholar，或者其他引擎，这些都可以在 SearchApi 文档中找到。在执行查询时可以传递 SearchApi 支持的所有参数。
search = SearchApiAPIWrapper(engine="google_jobs")
search.run("AI 工程师", location="葡萄牙", gl="pt")[0:500]
'Azure AI Engineer Be an XpanderCandidatar-meCandidatar-meCandidatar-me\n\nShare:\n\nAzure AI Engineer\n\nA área Digital Xperience da Xpand IT é uma equipa tecnológica de rápido crescimento que se concentra em tecnologias Microsoft e Mobile. A sua principal missão é fornecer soluções de software de alta qualidade que atendam às necessidades do utilizador final, num mundo tecnológico continuamente exigente e em ritmo acelerado, proporcionando a melhor experiência em termos de personalização, performance'
获取带有元数据的结果
import pprint
search = SearchApiAPIWrapper(engine="google_scholar")
results = search.results("Large Language Models")
pprint.pp(results)
{'search_metadata': {'id': 'search_qVdXG2jzvrlqTzayeYoaOb8A',
'status': 'Success',
'created_at': '2023-09-25T15:22:30Z',
'request_time_taken': 3.21,
'parsing_time_taken': 0.03,
'total_time_taken': 3.24,
'request_url': 'https://scholar.google.com/scholar?q=Large+Language+Models&hl=en',
'html_url': 'https://www.searchapi.io/api/v1/searches/search_qVdXG2jzvrlqTzayeYoaOb8A.html',
'json_url': 'https://www.searchapi.io/api/v1/searches/search_qVdXG2jzvrlqTzayeYoaOb8A'},
'search_parameters': {'engine': 'google_scholar',
'q': 'Large Language Models',
'hl': 'en'},
'search_information': {'query_displayed': 'Large Language Models',
'total_results': 6420000,
'page': 1,
'time_taken_displayed': 0.06},
'organic_results': [{'position': 1,
'title': 'ChatGPT for good? On opportunities and '
'challenges of large language models for '
'education',
'data_cid': 'uthwmf2nU3EJ',
'link': 'https://www.sciencedirect.com/science/article/pii/S1041608023000195',
'publication': 'E Kasneci, K Seßler, S Küchemann, M '
'Bannert… - Learning and individual …, '
'2023 - Elsevier',
'snippet': '… state of large language models and their '
'applications. We then highlight how these '
'models can be … With regard to challenges, '
'we argue that large language models in '
'education require …',
'inline_links': {'cited_by': {'cites_id': '8166055256995715258',
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'link': 'https://scholar.google.com/scholar?cites=8166055256995715258&as_sdt=5,33&sciodt=0,33&hl=en'},
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'resource': {'name': 'edarxiv.org',
'format': 'PDF',
'link': 'https://edarxiv.org/5er8f/download?format=pdf'},
'authors': [{'name': 'E Kasneci',
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'link': 'https://scholar.google.com/citations?user=bZVkVvoAAAAJ&hl=en&oi=sra'},
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'link': 'https://scholar.google.com/citations?user=MbMBoN4AAAAJ&hl=en&oi=sra'},
{'name': 'S Küchemann',
'id': 'g1jX5QUAAAAJ',
'link': 'https://scholar.google.com/citations?user=g1jX5QUAAAAJ&hl=en&oi=sra'},
{'name': 'M Bannert',
'id': 'TjfQ8QkAAAAJ',
'link': 'https://scholar.google.com/citations?user=TjfQ8QkAAAAJ&hl=en&oi=sra'}]},
{'position': 2,
'title': 'Large language models in medicine',
'data_cid': 'Ph9AwHTmhzAJ',
'link': 'https://www.nature.com/articles/s41591-023-02448-8',
'publication': 'AJ Thirunavukarasu, DSJ Ting, K '
'Elangovan… - Nature medicine, 2023 - '
'nature.com',
'snippet': '… HuggingChat offers a free-to-access '
'chatbot with a similar interface to ChatGPT '
'but uses Large Language Model Meta AI '
'(LLaMA) as its backend model 30 . Finally, '
'cheap imitations of …',
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'authors': [{'name': 'AJ Thirunavukarasu',
'id': '3qb1AYwAAAAJ',
'link': 'https://scholar.google.com/citations?user=3qb1AYwAAAAJ&hl=en&oi=sra'},
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'link': 'https://scholar.google.com/citations?user=KbrpC8cAAAAJ&hl=en&oi=sra'},
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'link': 'https://scholar.google.com/citations?user=BE_lVTQAAAAJ&hl=en&oi=sra'}]},
{'position': 3,
'title': 'Extracting training data from large language '
'models',
'data_cid': 'mEYsWK6bWKoJ',
'link': 'https://www.usenix.org/conference/usenixsecurity21/presentation/carlini-extracting',
'publication': 'N Carlini, F Tramer, E Wallace, M '
'Jagielski… - 30th USENIX Security …, '
'2021 - usenix.org',
'snippet': '… language model trained on scrapes of the '
'public Internet, and are able to extract '
'hundreds of verbatim text sequences from the '
'model’… models are more vulnerable than '
'smaller models. …',
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'link': 'https://scholar.google.com/citations?user=ijH0-a8AAAAJ&hl=en&oi=sra'},
{'name': 'E Wallace',
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'link': 'https://scholar.google.com/citations?user=SgST3LkAAAAJ&hl=en&oi=sra'},
{'name': 'M Jagielski',
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'link': 'https://scholar.google.com/citations?user=_8rw_GMAAAAJ&hl=en&oi=sra'}]},
{'position': 4,
'title': 'Emergent abilities of large language models',
'data_cid': 'hG0iVOrOguoJ',
'link': 'https://arxiv.org/abs/2206.07682',
'publication': 'J Wei, Y Tay, R Bommasani, C Raffel, B '
'Zoph… - arXiv preprint arXiv …, 2022 - '
'arxiv.org',
'snippet': 'Scaling up language models has been shown to '
'predictably improve performance and sample '
'efficiency on a wide range of downstream '
'tasks. This paper instead discusses an …',
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'authors': [{'name': 'J Wei',
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'link': 'https://scholar.google.com/citations?user=wA5TK_0AAAAJ&hl=en&oi=sra'},
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'link': 'https://scholar.google.com/citations?user=VBclY_cAAAAJ&hl=en&oi=sra'},
{'name': 'R Bommasani',
'id': 'WMBXw1EAAAAJ',
'link': 'https://scholar.google.com/citations?user=WMBXw1EAAAAJ&hl=en&oi=sra'},
{'name': 'C Raffel',
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'link': 'https://scholar.google.com/citations?user=I66ZBYwAAAAJ&hl=en&oi=sra'},
{'name': 'B Zoph',
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'link': 'https://scholar.google.com/citations?user=NL_7iTwAAAAJ&hl=en&oi=sra'}]},
{'position': 5,
'title': 'A survey on evaluation of large language '
'models',
'data_cid': 'ZYohnzOz-XgJ',
'link': 'https://arxiv.org/abs/2307.03109',
'publication': 'Y Chang, X Wang, J Wang, Y Wu, K Zhu… - '
'arXiv preprint arXiv …, 2023 - arxiv.org',
'snippet': '… 3.1 Natural Language Processing Tasks … '
'the development of language models, '
'particularly large language models, was to '
'enhance performance on natural language '
'processing tasks, …',
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'link': 'https://arxiv.org/pdf/2307.03109'},
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{'position': 6,
'title': 'Evaluating large language models trained on '
'code',
'data_cid': '3tNvW3l5nU4J',
'link': 'https://arxiv.org/abs/2107.03374',
'publication': 'M Chen, J Tworek, H Jun, Q Yuan, HPO '
'Pinto… - arXiv preprint arXiv …, 2021 - '
'arxiv.org',
'snippet': '… We introduce Codex, a GPT language model '
'finetuned on publicly available code from '
'GitHub, and study its Python code-writing '
'capabilities. A distinct production version '
'of Codex …',
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{'position': 7,
'title': 'Large language models in machine translation',
'data_cid': 'sY5m_Y3-0Y4J',
'link': 'http://research.google/pubs/pub33278.pdf',
'publication': 'T Brants, AC Popat, P Xu, FJ Och, J Dean '
'- 2007 - research.google',
'snippet': '… the benefits of largescale statistical '
'language modeling in ma… trillion tokens, '
'resulting in language models having up to '
'300 … is inexpensive to train on large data '
'sets and approaches the …',
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{'position': 8,
'title': 'A watermark for large language models',
'data_cid': 'BlSyLHT4iiEJ',
'link': 'https://arxiv.org/abs/2301.10226',
'publication': 'J Kirchenbauer, J Geiping, Y Wen, J '
'Katz… - arXiv preprint arXiv …, 2023 - '
'arxiv.org',
'snippet': '… To derive this watermark, we examine what '
'happens in the language model just before it '
'produces a probability vector. The last '
'layer of the language model outputs a vector '
'of logits l(t). …',
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{'position': 9,
'title': 'ChatGPT and other large language models are '
'double-edged swords',
'data_cid': 'So0q8TRvxhYJ',
'link': 'https://pubs.rsna.org/doi/full/10.1148/radiol.230163',
'publication': 'Y Shen, L Heacock, J Elias, KD Hentel, B '
'Reig, G Shih… - Radiology, 2023 - '
'pubs.rsna.org',
'snippet': '… Large Language Models (LLMs) are deep '
'learning models trained to understand and '
'generate natural language. Recent studies '
'demonstrated that LLMs achieve great success '
'in a …',
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{'position': 10,
'title': 'Pythia: A suite for analyzing large language '
'models across training and scaling',
'data_cid': 'aaIDvsMAD8QJ',
'link': 'https://proceedings.mlr.press/v202/biderman23a.html',
'publication': 'S Biderman, H Schoelkopf… - '
'International …, 2023 - '
'proceedings.mlr.press',
'snippet': '… large language models, we prioritize '
'consistency in model … out the most '
'performance from each model. For example, we '
'… models, as it is becoming widely used for '
'the largest models, …',
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