langchain_community.utilities.zapier
.ZapierNLAWrapper¶
- class langchain_community.utilities.zapier.ZapierNLAWrapper[source]¶
Bases:
BaseModel
Wrapper for Zapier NLA.
Full docs here: https://nla.zapier.com/start/
This wrapper supports both API Key and OAuth Credential auth methods. API Key is the fastest way to get started using this wrapper.
Call this wrapper with either zapier_nla_api_key or zapier_nla_oauth_access_token arguments, or set the ZAPIER_NLA_API_KEY environment variable. If both arguments are set, the Access Token will take precedence.
For use-cases where LangChain + Zapier NLA is powering a user-facing application, and LangChain needs access to the end-user’s connected accounts on Zapier.com, you’ll need to use OAuth. Review the full docs above to learn how to create your own provider and generate credentials.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- param zapier_nla_api_base: str = 'https://nla.zapier.com/api/v1/'¶
- param zapier_nla_api_key: str [Required]¶
- param zapier_nla_oauth_access_token: str [Required]¶
- async alist() List[Dict] [source]¶
Returns a list of all exposed (enabled) actions associated with current user (associated with the set api_key). Change your exposed actions here: https://nla.zapier.com/demo/start/
The return list can be empty if no actions exposed. Else will contain a list of action objects:
- [{
“id”: str, “description”: str, “params”: Dict[str, str]
}]
params will always contain an instructions key, the only required param. All others optional and if provided will override any AI guesses (see “understanding the AI guessing flow” here: https://nla.zapier.com/api/v1/docs)
- async alist_as_str() str [source]¶
Same as list, but returns a stringified version of the JSON for insertting back into an LLM.
- async apreview(action_id: str, instructions: str, params: Optional[Dict] = None) Dict [source]¶
Same as run, but instead of actually executing the action, will instead return a preview of params that have been guessed by the AI in case you need to explicitly review before executing.
- async apreview_as_str(*args, **kwargs) str [source]¶
Same as preview, but returns a stringified version of the JSON for insertting back into an LLM.
- async arun(action_id: str, instructions: str, params: Optional[Dict] = None) Dict [source]¶
Executes an action that is identified by action_id, must be exposed (enabled) by the current user (associated with the set api_key). Change your exposed actions here: https://nla.zapier.com/demo/start/
The return JSON is guaranteed to be less than ~500 words (350 tokens) making it safe to inject into the prompt of another LLM call.
- async arun_as_str(*args, **kwargs) str [source]¶
Same as run, but returns a stringified version of the JSON for insertting back into an LLM.
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model ¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model ¶
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny ¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- classmethod from_orm(obj: Any) Model ¶
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode ¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- list() List[Dict] [source]¶
Returns a list of all exposed (enabled) actions associated with current user (associated with the set api_key). Change your exposed actions here: https://nla.zapier.com/demo/start/
The return list can be empty if no actions exposed. Else will contain a list of action objects:
- [{
“id”: str, “description”: str, “params”: Dict[str, str]
}]
params will always contain an instructions key, the only required param. All others optional and if provided will override any AI guesses (see “understanding the AI guessing flow” here: https://nla.zapier.com/docs/using-the-api#ai-guessing)
- list_as_str() str [source]¶
Same as list, but returns a stringified version of the JSON for insertting back into an LLM.
- classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ¶
- classmethod parse_obj(obj: Any) Model ¶
- classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ¶
- preview(action_id: str, instructions: str, params: Optional[Dict] = None) Dict [source]¶
Same as run, but instead of actually executing the action, will instead return a preview of params that have been guessed by the AI in case you need to explicitly review before executing.
- preview_as_str(*args, **kwargs) str [source]¶
Same as preview, but returns a stringified version of the JSON for insertting back into an LLM.
- run(action_id: str, instructions: str, params: Optional[Dict] = None) Dict [source]¶
Executes an action that is identified by action_id, must be exposed (enabled) by the current user (associated with the set api_key). Change your exposed actions here: https://nla.zapier.com/demo/start/
The return JSON is guaranteed to be less than ~500 words (350 tokens) making it safe to inject into the prompt of another LLM call.
- run_as_str(*args, **kwargs) str [source]¶
Same as run, but returns a stringified version of the JSON for insertting back into an LLM.
- classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny ¶
- classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode ¶
- classmethod update_forward_refs(**localns: Any) None ¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- classmethod validate(value: Any) Model ¶