mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
e1c2cd7a28
- **Description:** Tool now supports querying over 200 million scientific articles, vastly expanding its reach beyond the 2 million articles accessible through Arxiv. This update significantly broadens access to the entire scope of scientific literature. - **Dependencies:** semantischolar https://github.com/danielnsilva/semanticscholar - **Twitter handle:** @shauryr --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
"""Tool for the SemanticScholar API."""
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from typing import Optional, Type
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from langchain_core.callbacks import CallbackManagerForToolRun
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from langchain_core.pydantic_v1 import BaseModel, Field
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from langchain_core.tools import BaseTool
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from langchain_community.utilities.semanticscholar import SemanticScholarAPIWrapper
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class SemantscholarInput(BaseModel):
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"""Input for the SemanticScholar tool."""
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query: str = Field(description="search query to look up")
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class SemanticScholarQueryRun(BaseTool):
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"""Tool that searches the semanticscholar API."""
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name: str = "semanticscholar"
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description: str = (
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"A wrapper around semantischolar.org "
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"Useful for when you need to answer to questions"
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"from research papers."
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"Input should be a search query."
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)
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api_wrapper: SemanticScholarAPIWrapper = Field(
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default_factory=SemanticScholarAPIWrapper
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)
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args_schema: Type[BaseModel] = SemantscholarInput
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def _run(
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self,
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query: str,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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) -> str:
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"""Use the Semantic Scholar tool."""
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return self.api_wrapper.run(query)
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