mirror of
https://github.com/hwchase17/langchain
synced 2024-11-04 06:00:26 +00:00
ed58eeb9c5
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
216 lines
7.5 KiB
Python
216 lines
7.5 KiB
Python
"""[DEPRECATED]
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## Zapier Natural Language Actions API
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\
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Full docs here: https://nla.zapier.com/start/
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**Zapier Natural Language Actions** gives you access to the 5k+ apps, 20k+ actions
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on Zapier's platform through a natural language API interface.
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NLA supports apps like Gmail, Salesforce, Trello, Slack, Asana, HubSpot, Google Sheets,
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Microsoft Teams, and thousands more apps: https://zapier.com/apps
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Zapier NLA handles ALL the underlying API auth and translation from
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natural language --> underlying API call --> return simplified output for LLMs
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The key idea is you, or your users, expose a set of actions via an oauth-like setup
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window, which you can then query and execute via a REST API.
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NLA offers both API Key and OAuth for signing NLA API requests.
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1. Server-side (API Key): for quickly getting started, testing, and production scenarios
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where LangChain will only use actions exposed in the developer's Zapier account
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(and will use the developer's connected accounts on Zapier.com)
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2. User-facing (Oauth): for production scenarios where you are deploying an end-user
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facing application and LangChain needs access to end-user's exposed actions and
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connected accounts on Zapier.com
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This quick start will focus on the server-side use case for brevity.
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Review [full docs](https://nla.zapier.com/start/) for user-facing oauth developer
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support.
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Typically, you'd use SequentialChain, here's a basic example:
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1. Use NLA to find an email in Gmail
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2. Use LLMChain to generate a draft reply to (1)
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3. Use NLA to send the draft reply (2) to someone in Slack via direct message
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In code, below:
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```python
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import os
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# get from https://platform.openai.com/
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os.environ["OPENAI_API_KEY"] = os.environ.get("OPENAI_API_KEY", "")
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# get from https://nla.zapier.com/docs/authentication/
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os.environ["ZAPIER_NLA_API_KEY"] = os.environ.get("ZAPIER_NLA_API_KEY", "")
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from langchain_community.agent_toolkits import ZapierToolkit
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from langchain_community.utilities.zapier import ZapierNLAWrapper
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## step 0. expose gmail 'find email' and slack 'send channel message' actions
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# first go here, log in, expose (enable) the two actions:
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# https://nla.zapier.com/demo/start
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# -- for this example, can leave all fields "Have AI guess"
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# in an oauth scenario, you'd get your own <provider> id (instead of 'demo')
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# which you route your users through first
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zapier = ZapierNLAWrapper()
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## To leverage OAuth you may pass the value `nla_oauth_access_token` to
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## the ZapierNLAWrapper. If you do this there is no need to initialize
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## the ZAPIER_NLA_API_KEY env variable
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# zapier = ZapierNLAWrapper(zapier_nla_oauth_access_token="TOKEN_HERE")
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toolkit = ZapierToolkit.from_zapier_nla_wrapper(zapier)
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```
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"""
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from typing import Any, Dict, Optional
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from langchain_core._api import warn_deprecated
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from langchain_core.callbacks import (
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AsyncCallbackManagerForToolRun,
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CallbackManagerForToolRun,
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)
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from langchain_core.pydantic_v1 import Field, root_validator
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from langchain_core.tools import BaseTool
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from langchain_community.tools.zapier.prompt import BASE_ZAPIER_TOOL_PROMPT
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from langchain_community.utilities.zapier import ZapierNLAWrapper
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class ZapierNLARunAction(BaseTool):
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"""
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Args:
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action_id: a specific action ID (from list actions) of the action to execute
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(the set api_key must be associated with the action owner)
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instructions: a natural language instruction string for using the action
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(eg. "get the latest email from Mike Knoop" for "Gmail: find email" action)
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params: a dict, optional. Any params provided will *override* AI guesses
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from `instructions` (see "understanding the AI guessing flow" here:
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https://nla.zapier.com/docs/using-the-api#ai-guessing)
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"""
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api_wrapper: ZapierNLAWrapper = Field(default_factory=ZapierNLAWrapper)
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action_id: str
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params: Optional[dict] = None
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base_prompt: str = BASE_ZAPIER_TOOL_PROMPT
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zapier_description: str
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params_schema: Dict[str, str] = Field(default_factory=dict)
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name: str = ""
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description: str = ""
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@root_validator
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def set_name_description(cls, values: Dict[str, Any]) -> Dict[str, Any]:
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zapier_description = values["zapier_description"]
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params_schema = values["params_schema"]
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if "instructions" in params_schema:
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del params_schema["instructions"]
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# Ensure base prompt (if overridden) contains necessary input fields
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necessary_fields = {"{zapier_description}", "{params}"}
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if not all(field in values["base_prompt"] for field in necessary_fields):
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raise ValueError(
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"Your custom base Zapier prompt must contain input fields for "
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"{zapier_description} and {params}."
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)
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values["name"] = zapier_description
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values["description"] = values["base_prompt"].format(
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zapier_description=zapier_description,
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params=str(list(params_schema.keys())),
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)
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return values
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def _run(
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self, instructions: str, run_manager: Optional[CallbackManagerForToolRun] = None
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) -> str:
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"""Use the Zapier NLA tool to return a list of all exposed user actions."""
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warn_deprecated(
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since="0.0.319",
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message=(
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"This tool will be deprecated on 2023-11-17. See "
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"https://nla.zapier.com/sunset/ for details"
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),
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)
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return self.api_wrapper.run_as_str(self.action_id, instructions, self.params)
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async def _arun(
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self,
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instructions: str,
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run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
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) -> str:
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"""Use the Zapier NLA tool to return a list of all exposed user actions."""
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warn_deprecated(
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since="0.0.319",
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message=(
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"This tool will be deprecated on 2023-11-17. See "
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"https://nla.zapier.com/sunset/ for details"
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),
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)
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return await self.api_wrapper.arun_as_str(
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self.action_id,
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instructions,
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self.params,
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)
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ZapierNLARunAction.__doc__ = (
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ZapierNLAWrapper.run.__doc__ + ZapierNLARunAction.__doc__ # type: ignore
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)
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# other useful actions
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class ZapierNLAListActions(BaseTool):
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"""
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Args:
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None
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"""
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name: str = "ZapierNLA_list_actions"
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description: str = BASE_ZAPIER_TOOL_PROMPT + (
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"This tool returns a list of the user's exposed actions."
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)
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api_wrapper: ZapierNLAWrapper = Field(default_factory=ZapierNLAWrapper)
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def _run(
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self,
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_: str = "",
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run_manager: Optional[CallbackManagerForToolRun] = None,
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) -> str:
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"""Use the Zapier NLA tool to return a list of all exposed user actions."""
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warn_deprecated(
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since="0.0.319",
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message=(
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"This tool will be deprecated on 2023-11-17. See "
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"https://nla.zapier.com/sunset/ for details"
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),
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)
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return self.api_wrapper.list_as_str()
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async def _arun(
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self,
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_: str = "",
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run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
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) -> str:
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"""Use the Zapier NLA tool to return a list of all exposed user actions."""
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warn_deprecated(
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since="0.0.319",
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message=(
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"This tool will be deprecated on 2023-11-17. See "
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"https://nla.zapier.com/sunset/ for details"
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),
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)
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return await self.api_wrapper.alist_as_str()
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ZapierNLAListActions.__doc__ = (
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ZapierNLAWrapper.list.__doc__ + ZapierNLAListActions.__doc__ # type: ignore
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)
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