prebuilt.systemic_review_of_scientific_articles.tools¶

Classes¶

AcademicPaperSearchTool

Base class for all LangChain tools.

Module Contents¶

class prebuilt.systemic_review_of_scientific_articles.tools.AcademicPaperSearchTool(name: str = 'academic_paper_search_tool', description: str = 'Queries an academic paper API to retrieve relevant articles based on a topic')¶

Bases: langchain_core.tools.BaseTool

Base class for all LangChain tools.

This abstract class defines the interface that all LangChain tools must implement. Tools are components that can be called by agents to perform specific actions.

query_academic_api(topic: str, max_results: int) → list[dict[str, Any]]¶

Query Academic Api.

Parameters:

  • topic – [TODO: Add description]

  • max_results – [TODO: Add description]

Returns:

Add return description]

Return type:

[TODO

args_schema: type¶

Pydantic model class to validate and parse the tool’s input arguments.

Args schema should be either:

  • A subclass of pydantic.BaseModel.

  • A subclass of pydantic.v1.BaseModel if accessing v1 namespace in pydantic 2

  • a JSON schema dict

description: str = None¶

Used to tell the model how/when/why to use the tool.

You can provide few-shot examples as a part of the description.

name: str = None¶

The unique name of the tool that clearly communicates its purpose.