langchain.utilities.google_scholar.GoogleScholarAPIWrapper

class langchain.utilities.google_scholar.GoogleScholarAPIWrapper[source]

Bases: BaseModel

Wrapper for Google Scholar API

You can create serpapi key by signing up at: https://serpapi.com/users/sign_up.

The wrapper uses the serpapi python package: https://serpapi.com/integrations/python#search-google-scholar

To use, you should have the environment variable SERP_API_KEY set with your API key, or pass serp_api_key as a named parameter to the constructor.

top_k_results

number of results to return from google-scholar query search. By default it returns top 10 results.

hl

attribute defines the language to use for the Google Scholar search. It’s a two-letter language code. (e.g., en for English, es for Spanish, or fr for French). Head to the Google languages page for a full list of supported Google languages: https://serpapi.com/google-languages

lr

attribute defines one or multiple languages to limit the search to. It uses lang_{two-letter language code} to specify languages and | as a delimiter. (e.g., lang_fr|lang_de will only search French and German pages). Head to the Google lr languages for a full list of supported languages: https://serpapi.com/google-lr-languages

Example:

from langchain.utilities import GoogleScholarAPIWrapper google_scholar = GoogleScholarAPIWrapper() google_scholar.run(‘langchain’)

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 hl: str = 'en'
param lr: str = 'lang_en'
param serp_api_key: Optional[str] = None
param top_k_results: int = 10
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().

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
run(query: str) str[source]

Run query through GoogleSearchScholar and parse result

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