Zapier Natural Language Actions

Deprecated This API will be sunset on 2023-11-17: https://nla.zapier.com/start/

Zapier Natural Language Actions gives you access to the 5k+ apps, 20k+ actions on Zapier's platform through a natural language API interface.

NLA supports apps like Gmail, Salesforce, Trello, Slack, Asana, HubSpot, Google Sheets, Microsoft Teams, and thousands more apps: https://zapier.com/apps Zapier NLA handles ALL the underlying API auth and translation from natural language --> underlying API call --> return simplified output for LLMs. The key idea is you, or your users, expose a set of actions via an oauth-like setup window, which you can then query and execute via a REST API.

NLA offers both API Key and OAuth for signing NLA API requests.

Server-side (API Key): for quickly getting started, testing, and production scenarios where LangChain will only use actions exposed in the developer's Zapier account (and will use the developer's connected accounts on Zapier.com)
User-facing (Oauth): for production scenarios where you are deploying an end-user facing application and LangChain needs access to end-user's exposed actions and connected accounts on Zapier.com

This quick start focus mostly on the server-side use case for brevity. Jump to Example Using OAuth Access Token to see a short example how to set up Zapier for user-facing situations. Review full docs for full user-facing oauth developer support.

This example goes over how to use the Zapier integration with a SimpleSequentialChain, then an Agent. In code, below:

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", "")

Example with Agent

Zapier tools can be used with an agent. See the example below.

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

API Reference:AgentType | initialize_agent | ZapierToolkit | ZapierNLAWrapper | 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.'

Example with SimpleSequentialChain

If you need more explicit control, use a chain, like below.

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\']"}'

Example Using OAuth Access Token

The below snippet shows how to initialize the wrapper with a procured OAuth access token. Note the argument being passed in as opposed to setting an environment variable. Review the authentication docs for full user-facing oauth developer support.

The developer is tasked with handling the OAuth handshaking to procure and refresh the access token.

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."
)

Tool conceptual guide
Tool how-to guides

Example with Agent​

Example with SimpleSequentialChain​

Example Using OAuth Access Token​

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Example with Agent

Example with SimpleSequentialChain

Example Using OAuth Access Token

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