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)

Return type

List[Dict]

async alist_as_str() → str[source]

Same as list, but returns a stringified version of the JSON for insertting back into an LLM.

Return type

str

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.

Parameters

  • action_id (str) –

  • instructions (str) –

  • params (Optional[Dict]) –

Return type

Dict

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.

Return type

str

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.

Parameters

  • action_id (str) –

  • instructions (str) –

  • params (Optional[Dict]) –

Return type

Dict

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.

Return type

str

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

Parameters

  • _fields_set (Optional[SetStr]) –

  • values (Any) –

Return type

Model

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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include

  • update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model

  • self (Model) –

Returns

new model instance

Return type

Model

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.

Parameters

  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • by_alias (bool) –

  • skip_defaults (Optional[bool]) –

  • exclude_unset (bool) –

  • exclude_defaults (bool) –

  • exclude_none (bool) –

Return type

DictStrAny

classmethod from_orm(obj: Any) → Model
Parameters

obj (Any) –

Return type

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().

Parameters

  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • by_alias (bool) –

  • skip_defaults (Optional[bool]) –

  • exclude_unset (bool) –

  • exclude_defaults (bool) –

  • exclude_none (bool) –

  • encoder (Optional[Callable[[Any], Any]]) –

  • models_as_dict (bool) –

  • dumps_kwargs (Any) –

Return type

unicode

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)

Return type

List[Dict]

list_as_str() → str[source]

Same as list, but returns a stringified version of the JSON for insertting back into an LLM.

Return type

str

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
Parameters

  • path (Union[str, Path]) –

  • content_type (unicode) –

  • encoding (unicode) –

  • proto (Protocol) –

  • allow_pickle (bool) –

Return type

Model

classmethod parse_obj(obj: Any) → Model
Parameters

obj (Any) –

Return type

Model

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
Parameters

  • b (Union[str, bytes]) –

  • content_type (unicode) –

  • encoding (unicode) –

  • proto (Protocol) –

  • allow_pickle (bool) –

Return type

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.

Parameters

  • action_id (str) –

  • instructions (str) –

  • params (Optional[Dict]) –

Return type

Dict

preview_as_str(*args, **kwargs) → str[source]

Same as preview, but returns a stringified version of the JSON for insertting back into an LLM.

Return type

str

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.

Parameters

  • action_id (str) –

  • instructions (str) –

  • params (Optional[Dict]) –

Return type

Dict

run_as_str(*args, **kwargs) → str[source]

Same as run, but returns a stringified version of the JSON for insertting back into an LLM.

Return type

str

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny
Parameters

  • by_alias (bool) –

  • ref_template (unicode) –

Return type

DictStrAny

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode
Parameters

  • by_alias (bool) –

  • ref_template (unicode) –

  • dumps_kwargs (Any) –

Return type

unicode

classmethod update_forward_refs(**localns: Any) → None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

Parameters

localns (Any) –

Return type

None

classmethod validate(value: Any) → Model
Parameters

value (Any) –

Return type

Model

Examples using ZapierNLAWrapper