mirror of
https://github.com/hwchase17/langchain
synced 2024-11-18 09:25:54 +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
298 lines
11 KiB
Python
298 lines
11 KiB
Python
"""Util that can interact with Zapier NLA.
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Full docs here: https://nla.zapier.com/start/
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Note: this wrapper currently only implemented the `api_key` auth method for testing
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and server-side production use cases (using the developer's connected accounts on
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Zapier.com)
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For use-cases where LangChain + Zapier NLA is powering a user-facing application, and
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LangChain needs access to the end-user's connected accounts on Zapier.com, you'll need
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to use oauth. Review the full docs above and reach out to nla@zapier.com for
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developer support.
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"""
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import json
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from typing import Any, Dict, List, Optional
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import aiohttp
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import requests
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from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
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from langchain_core.utils import get_from_dict_or_env
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from requests import Request, Session
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class ZapierNLAWrapper(BaseModel):
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"""Wrapper for Zapier NLA.
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Full docs here: https://nla.zapier.com/start/
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This wrapper supports both API Key and OAuth Credential auth methods. API Key
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is the fastest way to get started using this wrapper.
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Call this wrapper with either `zapier_nla_api_key` or
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`zapier_nla_oauth_access_token` arguments, or set the `ZAPIER_NLA_API_KEY`
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environment variable. If both arguments are set, the Access Token will take
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precedence.
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For use-cases where LangChain + Zapier NLA is powering a user-facing application,
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and LangChain needs access to the end-user's connected accounts on Zapier.com,
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you'll need to use OAuth. Review the full docs above to learn how to create
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your own provider and generate credentials.
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"""
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zapier_nla_api_key: str
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zapier_nla_oauth_access_token: str
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zapier_nla_api_base: str = "https://nla.zapier.com/api/v1/"
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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def _format_headers(self) -> Dict[str, str]:
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"""Format headers for requests."""
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headers = {
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"Accept": "application/json",
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"Content-Type": "application/json",
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}
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if self.zapier_nla_oauth_access_token:
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headers.update(
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{"Authorization": f"Bearer {self.zapier_nla_oauth_access_token}"}
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)
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else:
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headers.update({"X-API-Key": self.zapier_nla_api_key})
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return headers
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def _get_session(self) -> Session:
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session = requests.Session()
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session.headers.update(self._format_headers())
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return session
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async def _arequest(self, method: str, url: str, **kwargs: Any) -> Dict[str, Any]:
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"""Make an async request."""
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async with aiohttp.ClientSession(headers=self._format_headers()) as session:
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async with session.request(method, url, **kwargs) as response:
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response.raise_for_status()
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return await response.json()
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def _create_action_payload( # type: ignore[no-untyped-def]
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self, instructions: str, params: Optional[Dict] = None, preview_only=False
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) -> Dict:
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"""Create a payload for an action."""
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data = params if params else {}
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data.update(
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{
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"instructions": instructions,
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}
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)
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if preview_only:
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data.update({"preview_only": True})
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return data
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def _create_action_url(self, action_id: str) -> str:
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"""Create a url for an action."""
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return self.zapier_nla_api_base + f"exposed/{action_id}/execute/"
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def _create_action_request( # type: ignore[no-untyped-def]
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self,
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action_id: str,
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instructions: str,
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params: Optional[Dict] = None,
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preview_only=False,
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) -> Request:
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data = self._create_action_payload(instructions, params, preview_only)
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return Request(
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"POST",
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self._create_action_url(action_id),
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json=data,
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)
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@root_validator(pre=True)
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key exists in environment."""
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zapier_nla_api_key_default = None
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# If there is a oauth_access_key passed in the values
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# we don't need a nla_api_key it can be blank
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if "zapier_nla_oauth_access_token" in values:
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zapier_nla_api_key_default = ""
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else:
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values["zapier_nla_oauth_access_token"] = ""
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# we require at least one API Key
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zapier_nla_api_key = get_from_dict_or_env(
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values,
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"zapier_nla_api_key",
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"ZAPIER_NLA_API_KEY",
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zapier_nla_api_key_default,
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)
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values["zapier_nla_api_key"] = zapier_nla_api_key
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return values
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async def alist(self) -> List[Dict]:
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"""Returns a list of all exposed (enabled) actions associated with
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current user (associated with the set api_key). Change your exposed
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actions here: https://nla.zapier.com/demo/start/
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The return list can be empty if no actions exposed. Else will contain
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a list of action objects:
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[{
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"id": str,
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"description": str,
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"params": Dict[str, str]
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}]
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`params` will always contain an `instructions` key, the only required
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param. All others optional and if provided will override any AI guesses
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(see "understanding the AI guessing flow" here:
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https://nla.zapier.com/api/v1/docs)
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"""
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response = await self._arequest("GET", self.zapier_nla_api_base + "exposed/")
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return response["results"]
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def list(self) -> List[Dict]:
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"""Returns a list of all exposed (enabled) actions associated with
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current user (associated with the set api_key). Change your exposed
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actions here: https://nla.zapier.com/demo/start/
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The return list can be empty if no actions exposed. Else will contain
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a list of action objects:
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[{
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"id": str,
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"description": str,
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"params": Dict[str, str]
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}]
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`params` will always contain an `instructions` key, the only required
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param. All others optional and if provided will override any AI guesses
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(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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session = self._get_session()
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try:
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response = session.get(self.zapier_nla_api_base + "exposed/")
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response.raise_for_status()
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except requests.HTTPError as http_err:
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if response.status_code == 401:
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if self.zapier_nla_oauth_access_token:
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raise requests.HTTPError(
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f"An unauthorized response occurred. Check that your "
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f"access token is correct and doesn't need to be "
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f"refreshed. Err: {http_err}",
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response=response,
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)
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raise requests.HTTPError(
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f"An unauthorized response occurred. Check that your api "
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f"key is correct. Err: {http_err}",
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response=response,
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)
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raise http_err
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return response.json()["results"]
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def run(
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self, action_id: str, instructions: str, params: Optional[Dict] = None
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) -> Dict:
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"""Executes an action that is identified by action_id, must be exposed
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(enabled) by the current user (associated with the set api_key). Change
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your exposed actions here: https://nla.zapier.com/demo/start/
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The return JSON is guaranteed to be less than ~500 words (350
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tokens) making it safe to inject into the prompt of another LLM
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call.
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"""
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session = self._get_session()
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request = self._create_action_request(action_id, instructions, params)
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response = session.send(session.prepare_request(request))
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response.raise_for_status()
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return response.json()["result"]
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async def arun(
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self, action_id: str, instructions: str, params: Optional[Dict] = None
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) -> Dict:
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"""Executes an action that is identified by action_id, must be exposed
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(enabled) by the current user (associated with the set api_key). Change
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your exposed actions here: https://nla.zapier.com/demo/start/
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The return JSON is guaranteed to be less than ~500 words (350
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tokens) making it safe to inject into the prompt of another LLM
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call.
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"""
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response = await self._arequest(
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"POST",
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self._create_action_url(action_id),
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json=self._create_action_payload(instructions, params),
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)
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return response["result"]
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def preview(
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self, action_id: str, instructions: str, params: Optional[Dict] = None
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) -> Dict:
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"""Same as run, but instead of actually executing the action, will
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instead return a preview of params that have been guessed by the AI in
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case you need to explicitly review before executing."""
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session = self._get_session()
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params = params if params else {}
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params.update({"preview_only": True})
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request = self._create_action_request(action_id, instructions, params, True)
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response = session.send(session.prepare_request(request))
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response.raise_for_status()
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return response.json()["input_params"]
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async def apreview(
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self, action_id: str, instructions: str, params: Optional[Dict] = None
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) -> Dict:
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"""Same as run, but instead of actually executing the action, will
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instead return a preview of params that have been guessed by the AI in
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case you need to explicitly review before executing."""
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response = await self._arequest(
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"POST",
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self._create_action_url(action_id),
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json=self._create_action_payload(instructions, params, preview_only=True),
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)
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return response["result"]
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def run_as_str(self, *args, **kwargs) -> str: # type: ignore[no-untyped-def]
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"""Same as run, but returns a stringified version of the JSON for
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insertting back into an LLM."""
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data = self.run(*args, **kwargs)
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return json.dumps(data)
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async def arun_as_str(self, *args, **kwargs) -> str: # type: ignore[no-untyped-def]
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"""Same as run, but returns a stringified version of the JSON for
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insertting back into an LLM."""
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data = await self.arun(*args, **kwargs)
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return json.dumps(data)
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def preview_as_str(self, *args, **kwargs) -> str: # type: ignore[no-untyped-def]
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"""Same as preview, but returns a stringified version of the JSON for
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insertting back into an LLM."""
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data = self.preview(*args, **kwargs)
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return json.dumps(data)
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async def apreview_as_str( # type: ignore[no-untyped-def]
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self, *args, **kwargs
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) -> str:
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"""Same as preview, but returns a stringified version of the JSON for
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insertting back into an LLM."""
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data = await self.apreview(*args, **kwargs)
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return json.dumps(data)
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def list_as_str(self) -> str: # type: ignore[no-untyped-def]
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"""Same as list, but returns a stringified version of the JSON for
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insertting back into an LLM."""
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actions = self.list()
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return json.dumps(actions)
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async def alist_as_str(self) -> str: # type: ignore[no-untyped-def]
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"""Same as list, but returns a stringified version of the JSON for
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insertting back into an LLM."""
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actions = await self.alist()
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return json.dumps(actions)
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