SemanticScholarAPIWrapper#
- class langchain_community.utilities.semanticscholar.SemanticScholarAPIWrapper[source]#
Bases:
BaseModelWrapper around semanticscholar.org API. danielnsilva/semanticscholar
You should have this library installed.
pip install semanticscholar
Semantic Scholar API can conduct searches and fetch document metadata like title, abstract, authors, etc.
Attributes: top_k_results: number of the top-scored document used for the Semantic Scholar tool load_max_docs: a limit to the number of loaded documents
Example: .. code-block:: python
from langchain_community.utilities.semanticscholar import SemanticScholarAPIWrapper ss = SemanticScholarAPIWrapper(
top_k_results = 3, load_max_docs = 3
) ss.run(“biases in large language models”)
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
- param S2_MAX_QUERY_LENGTH: int = 300#
- param doc_content_chars_max: int | None = 4000#
- param load_max_docs: int = 100#
- param returned_fields: List[str] = ['title', 'abstract', 'venue', 'year', 'paperId', 'citationCount', 'openAccessPdf', 'authors', 'externalIds']#
- param top_k_results: int = 5#