"""
PMC_search_papers
Search for full-text biomedical literature using the PMC (PubMed Central) API. PMC is the free fu...
"""
from typing import Any, Optional, Callable
from ._shared_client import get_shared_client
[docs]
def PMC_search_papers(
query: str,
limit: Optional[int] = 10,
retmax: Optional[int] = None,
date_from: Optional[str] = None,
date_to: Optional[str] = None,
article_type: Optional[str] = None,
include_abstract: Optional[bool] = False,
*,
stream_callback: Optional[Callable[[str], None]] = None,
use_cache: bool = False,
validate: bool = True,
) -> list[Any]:
"""
Search for full-text biomedical literature using the PMC (PubMed Central) API. PMC is the free fu...
Parameters
----------
query : str
Search query for PMC papers. Use keywords separated by spaces to refine your ...
limit : int
Maximum number of papers to return. This sets the maximum number of papers re...
retmax : int
Alias for limit (NCBI eutils naming). If both retmax and limit are provided, ...
date_from : str
Start date for publication date filter (YYYY/MM/DD format). Optional paramete...
date_to : str
End date for publication date filter (YYYY/MM/DD format). Optional parameter ...
article_type : str
Article type filter (e.g., 'research-article', 'review', 'case-report'). Opti...
include_abstract : bool
If true, attempts to enrich results with an abstract (best-effort) by fetchin...
stream_callback : Callable, optional
Callback for streaming output
use_cache : bool, default False
Enable caching
validate : bool, default True
Validate parameters
Returns
-------
list[Any]
"""
# Handle mutable defaults to avoid B006 linting error
return get_shared_client().run_one_function(
{
"name": "PMC_search_papers",
"arguments": {
"query": query,
"limit": limit,
"retmax": retmax,
"date_from": date_from,
"date_to": date_to,
"article_type": article_type,
"include_abstract": include_abstract,
},
},
stream_callback=stream_callback,
use_cache=use_cache,
validate=validate,
)
__all__ = ["PMC_search_papers"]
