Source code for langchain_community.utilities.semanticscholar

"""Utils for interacting with the Semantic Scholar API."""
import logging
from typing import Any, Dict, Optional

from langchain_core.pydantic_v1 import BaseModel, root_validator

logger = logging.getLogger(__name__)

[docs]class SemanticScholarAPIWrapper(BaseModel): """Wrapper around API. 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 )"biases in large language models") """ semanticscholar_search: Any #: :meta private: top_k_results: int = 5 S2_MAX_QUERY_LENGTH: int = 300 load_max_docs: int = 100 doc_content_chars_max: Optional[int] = 4000 returned_fields = [ "title", "abstract", "venue", "year", "paperId", "citationCount", "openAccessPdf", "authors", "externalIds", ] @root_validator() def validate_environment(cls, values: Dict) -> Dict: """Validate that the python package exists in environment.""" try: from semanticscholar import SemanticScholar sch = SemanticScholar() values["semanticscholar_search"] = sch.search_paper except ImportError: raise ImportError( "Could not import Semanticscholar python package. " "Please install it with `pip install semanticscholar`." ) return values
[docs] def run(self, query: str) -> str: """Run the Semantic Scholar API.""" results = self.semanticscholar_search( query, limit=self.load_max_docs, fields=self.returned_fields ) documents = [] for item in results[: self.top_k_results]: authors = ", ".join( author["name"] for author in getattr(item, "authors", []) ) documents.append( f"Published year: {getattr(item, 'year', None)}\n" f"Title: {getattr(item, 'title', None)}\n" f"Authors: {authors}\n" f"Astract: {getattr(item, 'abstract', None)}\n" ) if documents: return "\n\n".join(documents)[: self.doc_content_chars_max] else: return "No results found."