Zapier自然语言操作

已弃用 此API将在2023-11-17停止服务: https://nla.zapier.com/start/

Zapier自然语言操作通过自然语言API接口为您提供对Zapier平台上5000多个应用和20000多个操作的访问。

NLA支持的应用包括Gmail、Salesforce、Trello、Slack、Asana、HubSpot、Google Sheets、Microsoft Teams以及成千上万的其他应用: https://zapier.com/apps Zapier NLA处理所有底层API认证和从自然语言到底层API调用的转换，并返回简化的LLMs输出。关键思想是您或您的用户通过类似oauth的设置窗口暴露一组操作，然后可以通过REST API查询和执行这些操作。

NLA同时提供API密钥和OAuth用于签署NLA API请求。

服务器端（API密钥）：用于快速入门、测试和生产场景，在这些场景中LangChain将仅使用开发者在Zapier账户中暴露的操作（并将使用开发者在Zapier.com上的连接账户）
面向用户（Oauth）：用于生产场景，在这些场景中您正在部署面向最终用户的应用程序，LangChain需要访问最终用户在Zapier.com上暴露的操作和连接账户

此快速入门主要集中在服务器端用例以简洁为主。跳转到使用OAuth访问令牌的示例以查看如何为面向用户的情况设置Zapier的简短示例。查看完整文档以获取完整的面向用户的oauth开发者支持。

本示例介绍了如何使用Zapier集成与SimpleSequentialChain，然后是Agent。代码如下：

import os

# get from https://platform.openai.com/
os.environ["OPENAI_API_KEY"] = os.environ.get("OPENAI_API_KEY", "")

# get from https://nla.zapier.com/docs/authentication/ after logging in):
os.environ["ZAPIER_NLA_API_KEY"] = os.environ.get("ZAPIER_NLA_API_KEY", "")

代理示例

Zapier 工具可以与代理一起使用。请参见下面的示例。

<!--IMPORTS:[{"imported": "AgentType", "source": "langchain.agents", "docs": "https://python.langchain.com/api_reference/langchain/agents/langchain.agents.agent_types.AgentType.html", "title": "Zapier Natural Language Actions"}, {"imported": "initialize_agent", "source": "langchain.agents", "docs": "https://python.langchain.com/api_reference/langchain/agents/langchain.agents.initialize.initialize_agent.html", "title": "Zapier Natural Language Actions"}, {"imported": "ZapierToolkit", "source": "langchain_community.agent_toolkits", "docs": "https://python.langchain.com/api_reference/community/agent_toolkits/langchain_community.agent_toolkits.zapier.toolkit.ZapierToolkit.html", "title": "Zapier Natural Language Actions"}, {"imported": "ZapierNLAWrapper", "source": "langchain_community.utilities.zapier", "docs": "https://python.langchain.com/api_reference/community/utilities/langchain_community.utilities.zapier.ZapierNLAWrapper.html", "title": "Zapier Natural Language Actions"}, {"imported": "OpenAI", "source": "langchain_openai", "docs": "https://python.langchain.com/api_reference/openai/llms/langchain_openai.llms.base.OpenAI.html", "title": "Zapier Natural Language Actions"}]-->
from langchain.agents import AgentType, initialize_agent
from langchain_community.agent_toolkits import ZapierToolkit
from langchain_community.utilities.zapier import ZapierNLAWrapper
from langchain_openai import OpenAI

## step 0. expose gmail 'find email' and slack 'send channel message' actions

# first go here, log in, expose (enable) the two actions: https://nla.zapier.com/demo/start -- for this example, can leave all fields "Have AI guess"
# in an oauth scenario, you'd get your own <provider> id (instead of 'demo') which you route your users through first

llm = OpenAI(temperature=0)
zapier = ZapierNLAWrapper()
toolkit = ZapierToolkit.from_zapier_nla_wrapper(zapier)
agent = initialize_agent(
    toolkit.get_tools(), llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)

agent.run(
    "Summarize the last email I received regarding Silicon Valley Bank. Send the summary to the #test-zapier channel in slack."
)

[1m> Entering new AgentExecutor chain...[0m
[32;1m[1;3m I need to find the email and summarize it.
Action: Gmail: Find Email
Action Input: Find the latest email from Silicon Valley Bank[0m
Observation: [31;1m[1;3m{"from__name": "Silicon Valley Bridge Bank, N.A.", "from__email": "sreply@svb.com", "body_plain": "Dear Clients, After chaotic, tumultuous & stressful days, we have clarity on path for SVB, FDIC is fully insuring all deposits & have an ask for clients & partners as we rebuild. Tim Mayopoulos <https://eml.svb.com/NjEwLUtBSy0yNjYAAAGKgoxUeBCLAyF_NxON97X4rKEaNBLG", "reply_to__email": "sreply@svb.com", "subject": "Meet the new CEO Tim Mayopoulos", "date": "Tue, 14 Mar 2023 23:42:29 -0500 (CDT)", "message_url": "https://mail.google.com/mail/u/0/#inbox/186e393b13cfdf0a", "attachment_count": "0", "to__emails": "ankush@langchain.dev", "message_id": "186e393b13cfdf0a", "labels": "IMPORTANT, CATEGORY_UPDATES, INBOX"}[0m
Thought:[32;1m[1;3m I need to summarize the email and send it to the #test-zapier channel in Slack.
Action: Slack: Send Channel Message
Action Input: Send a slack message to the #test-zapier channel with the text "Silicon Valley Bank has announced that Tim Mayopoulos is the new CEO. FDIC is fully insuring all deposits and they have an ask for clients and partners as they rebuild."[0m
Observation: [36;1m[1;3m{"message__text": "Silicon Valley Bank has announced that Tim Mayopoulos is the new CEO. FDIC is fully insuring all deposits and they have an ask for clients and partners as they rebuild.", "message__permalink": "https://langchain.slack.com/archives/C04TSGU0RA7/p1678859932375259", "channel": "C04TSGU0RA7", "message__bot_profile__name": "Zapier", "message__team": "T04F8K3FZB5", "message__bot_id": "B04TRV4R74K", "message__bot_profile__deleted": "false", "message__bot_profile__app_id": "A024R9PQM", "ts_time": "2023-03-15T05:58:52Z", "message__bot_profile__icons__image_36": "https://avatars.slack-edge.com/2022-08-02/3888649620612_f864dc1bb794cf7d82b0_36.png", "message__blocks[]block_id": "kdZZ", "message__blocks[]elements[]type": "['rich_text_section']"}[0m
Thought:[32;1m[1;3m I now know the final answer.
Final Answer: I have sent a summary of the last email from Silicon Valley Bank to the #test-zapier channel in Slack.[0m

[1m> Finished chain.[0m

'I have sent a summary of the last email from Silicon Valley Bank to the #test-zapier channel in Slack.'

简单顺序链示例

如果您需要更明确的控制，请使用链，如下所示。

<!--IMPORTS:[{"imported": "LLMChain", "source": "langchain.chains", "docs": "https://python.langchain.com/api_reference/langchain/chains/langchain.chains.llm.LLMChain.html", "title": "Zapier Natural Language Actions"}, {"imported": "SimpleSequentialChain", "source": "langchain.chains", "docs": "https://python.langchain.com/api_reference/langchain/chains/langchain.chains.sequential.SimpleSequentialChain.html", "title": "Zapier Natural Language Actions"}, {"imported": "TransformChain", "source": "langchain.chains", "docs": "https://python.langchain.com/api_reference/langchain/chains/langchain.chains.transform.TransformChain.html", "title": "Zapier Natural Language Actions"}, {"imported": "ZapierNLARunAction", "source": "langchain_community.tools.zapier.tool", "docs": "https://python.langchain.com/api_reference/community/tools/langchain_community.tools.zapier.tool.ZapierNLARunAction.html", "title": "Zapier Natural Language Actions"}, {"imported": "ZapierNLAWrapper", "source": "langchain_community.utilities.zapier", "docs": "https://python.langchain.com/api_reference/community/utilities/langchain_community.utilities.zapier.ZapierNLAWrapper.html", "title": "Zapier Natural Language Actions"}, {"imported": "PromptTemplate", "source": "langchain_core.prompts", "docs": "https://python.langchain.com/api_reference/core/prompts/langchain_core.prompts.prompt.PromptTemplate.html", "title": "Zapier Natural Language Actions"}, {"imported": "OpenAI", "source": "langchain_openai", "docs": "https://python.langchain.com/api_reference/openai/llms/langchain_openai.llms.base.OpenAI.html", "title": "Zapier Natural Language Actions"}]-->
from langchain.chains import LLMChain, SimpleSequentialChain, TransformChain
from langchain_community.tools.zapier.tool import ZapierNLARunAction
from langchain_community.utilities.zapier import ZapierNLAWrapper
from langchain_core.prompts import PromptTemplate
from langchain_openai import OpenAI

## step 0. expose gmail 'find email' and slack 'send direct message' actions

# first go here, log in, expose (enable) the two actions: https://nla.zapier.com/demo/start -- for this example, can leave all fields "Have AI guess"
# in an oauth scenario, you'd get your own <provider> id (instead of 'demo') which you route your users through first

actions = ZapierNLAWrapper().list()

## step 1. gmail find email

GMAIL_SEARCH_INSTRUCTIONS = "Grab the latest email from Silicon Valley Bank"


def nla_gmail(inputs):
    action = next(
        (a for a in actions if a["description"].startswith("Gmail: Find Email")), None
    )
    return {
        "email_data": ZapierNLARunAction(
            action_id=action["id"],
            zapier_description=action["description"],
            params_schema=action["params"],
        ).run(inputs["instructions"])
    }


gmail_chain = TransformChain(
    input_variables=["instructions"],
    output_variables=["email_data"],
    transform=nla_gmail,
)

## step 2. generate draft reply

template = """You are an assisstant who drafts replies to an incoming email. Output draft reply in plain text (not JSON).

Incoming email:
{email_data}

Draft email reply:"""

prompt_template = PromptTemplate(input_variables=["email_data"], template=template)
reply_chain = LLMChain(llm=OpenAI(temperature=0.7), prompt=prompt_template)

## step 3. send draft reply via a slack direct message

SLACK_HANDLE = "@Ankush Gola"


def nla_slack(inputs):
    action = next(
        (
            a
            for a in actions
            if a["description"].startswith("Slack: Send Direct Message")
        ),
        None,
    )
    instructions = f'Send this to {SLACK_HANDLE} in Slack: {inputs["draft_reply"]}'
    return {
        "slack_data": ZapierNLARunAction(
            action_id=action["id"],
            zapier_description=action["description"],
            params_schema=action["params"],
        ).run(instructions)
    }


slack_chain = TransformChain(
    input_variables=["draft_reply"],
    output_variables=["slack_data"],
    transform=nla_slack,
)

## finally, execute

overall_chain = SimpleSequentialChain(
    chains=[gmail_chain, reply_chain, slack_chain], verbose=True
)
overall_chain.run(GMAIL_SEARCH_INSTRUCTIONS)

[1m> Entering new SimpleSequentialChain chain...[0m
[36;1m[1;3m{"from__name": "Silicon Valley Bridge Bank, N.A.", "from__email": "sreply@svb.com", "body_plain": "Dear Clients, After chaotic, tumultuous & stressful days, we have clarity on path for SVB, FDIC is fully insuring all deposits & have an ask for clients & partners as we rebuild. Tim Mayopoulos <https://eml.svb.com/NjEwLUtBSy0yNjYAAAGKgoxUeBCLAyF_NxON97X4rKEaNBLG", "reply_to__email": "sreply@svb.com", "subject": "Meet the new CEO Tim Mayopoulos", "date": "Tue, 14 Mar 2023 23:42:29 -0500 (CDT)", "message_url": "https://mail.google.com/mail/u/0/#inbox/186e393b13cfdf0a", "attachment_count": "0", "to__emails": "ankush@langchain.dev", "message_id": "186e393b13cfdf0a", "labels": "IMPORTANT, CATEGORY_UPDATES, INBOX"}[0m
[33;1m[1;3m
Dear Silicon Valley Bridge Bank, 

Thank you for your email and the update regarding your new CEO Tim Mayopoulos. We appreciate your dedication to keeping your clients and partners informed and we look forward to continuing our relationship with you. 

Best regards, 
[Your Name][0m
[38;5;200m[1;3m{"message__text": "Dear Silicon Valley Bridge Bank, \n\nThank you for your email and the update regarding your new CEO Tim Mayopoulos. We appreciate your dedication to keeping your clients and partners informed and we look forward to continuing our relationship with you. \n\nBest regards, \n[Your Name]", "message__permalink": "https://langchain.slack.com/archives/D04TKF5BBHU/p1678859968241629", "channel": "D04TKF5BBHU", "message__bot_profile__name": "Zapier", "message__team": "T04F8K3FZB5", "message__bot_id": "B04TRV4R74K", "message__bot_profile__deleted": "false", "message__bot_profile__app_id": "A024R9PQM", "ts_time": "2023-03-15T05:59:28Z", "message__blocks[]block_id": "p7i", "message__blocks[]elements[]elements[]type": "[['text']]", "message__blocks[]elements[]type": "['rich_text_section']"}[0m

[1m> Finished chain.[0m

'{"message__text": "Dear Silicon Valley Bridge Bank, \\n\\nThank you for your email and the update regarding your new CEO Tim Mayopoulos. We appreciate your dedication to keeping your clients and partners informed and we look forward to continuing our relationship with you. \\n\\nBest regards, \\n[Your Name]", "message__permalink": "https://langchain.slack.com/archives/D04TKF5BBHU/p1678859968241629", "channel": "D04TKF5BBHU", "message__bot_profile__name": "Zapier", "message__team": "T04F8K3FZB5", "message__bot_id": "B04TRV4R74K", "message__bot_profile__deleted": "false", "message__bot_profile__app_id": "A024R9PQM", "ts_time": "2023-03-15T05:59:28Z", "message__blocks[]block_id": "p7i", "message__blocks[]elements[]elements[]type": "[[\'text\']]", "message__blocks[]elements[]type": "[\'rich_text_section\']"}'

使用 OAuth 访问令牌的示例

下面的代码片段展示了如何使用获取的 OAuth 访问令牌初始化包装器。请注意传入的参数，而不是设置环境变量。请查看认证文档以获取完整的用户面 OAuth 开发者支持。

开发者负责处理 OAuth 握手以获取和刷新访问令牌。

llm = OpenAI(temperature=0)
zapier = ZapierNLAWrapper(zapier_nla_oauth_access_token="<fill in access token here>")
toolkit = ZapierToolkit.from_zapier_nla_wrapper(zapier)
agent = initialize_agent(
    toolkit.get_tools(), llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)

agent.run(
    "Summarize the last email I received regarding Silicon Valley Bank. Send the summary to the #test-zapier channel in slack."
)

Zapier自然语言操作

代理示例

简单顺序链示例

使用 OAuth 访问令牌的示例

相关

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代理示例​

简单顺序链示例​

使用 OAuth 访问令牌的示例​

相关​

Was this page helpful?

You can also leave detailed feedback on GitHub.

代理示例

简单顺序链示例

使用 OAuth 访问令牌的示例

相关