跳到主要内容
已弃用 该 API 将于 2023-11-17 停止服务：nla.zapier.com/start/
Zapier 自然语言操作 (NLA) 允许您通过自然语言 API 接口访问 Zapier 平台上的 5000 多个应用程序和 20000 多个操作。 NLA 支持 Gmail、Salesforce、Trello、Slack、Asana、HubSpot、Google Sheets、Microsoft Teams 等数千个应用程序：zapier.com/apps。Zapier NLA 处理所有底层的 API 身份验证以及从自然语言 -> 底层 API 调用 -> 返回 LLM 的简化输出的转换。关键思想是您或您的用户通过类似 OAuth 的设置窗口公开一组操作，然后可以通过 REST API 查询和执行这些操作。
NLA 提供 API 密钥和 OAuth 两种方式来签署 NLA API 请求。
  1. 服务器端（API 密钥）：用于快速入门、测试以及 LangChain 只使用开发者 Zapier 账户中公开的操作（并使用开发者在 Zapier.com 上连接的账户）的生产场景。
  2. 用户端（OAuth）：用于部署面向最终用户的应用程序，并且 LangChain 需要访问最终用户在 Zapier.com 上公开的操作和连接的账户的生产场景。
为简洁起见，本快速入门主要关注服务器端用例。跳至使用 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。 本示例将介绍如何将 Zapier 集成与 SimpleSequentialChain 和 Agent 结合使用。请参见下面的代码：
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", "")

​
使用 Agent 的示例

Zapier 工具可以与 Agent 结合使用。请参见下面的示例。 
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."
)

> Entering new AgentExecutor chain...
 I need to find the email and summarize it.
Action: Gmail: Find Email
Action Input: Find the latest email from Silicon Valley Bank
Observation: {"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"}
Thought: 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."
Observation: {"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']"}
Thought: 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.

> Finished chain.

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

​
使用 SimpleSequentialChain 的示例

如果您需要更明确的控制，请使用链，如下所示。 
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)

> Entering new SimpleSequentialChain chain...
{"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"}

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]
{"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']"}

> Finished chain.

'{"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得的 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。查看身份验证文档以获取完整的面向用户的 OAuth 开发者支持。 开发者需要负责处理 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."
)
在 GitHub 上编辑此页面源文件。
以编程方式连接这些文档到 Claude、VSCode 等，通过 MCP 获取实时答案。
© . This site is unofficial and not affiliated with LangChain, Inc.