from groundx import AsyncGroundX
from typing import List, Optional, Dict, Any
async def search_documents_in_Groundx(
groundx_api_key: str,
document_ids: List[str],
query: str,
n: Optional[int] = None,
next_token: Optional[str] = None,
verbosity: Optional[int] = None,
filter: Optional[Dict[str, Any]] = None,
relevanced: Optional[float] = None
) -> dict:
"""
Search documents on GroundX for the most relevant information to a given query by documentId(s).
See: https://docs.eyelevel.ai/reference/api-reference/search/documents
Args:
groundx_api_key (str): The API key for GroundX.
document_ids (List[str]): An array of unique documentIds to be searched.
query (str): The search query to be used to find relevant documentation.
n (int, optional): The maximum number of returned search results. Accepts 1-100 with a default of 20.
next_token (str, optional): A token for pagination. If the number of search results for a given query is larger than n, the response will include a "nextToken" value. That token can be included in this field to retrieve the next batch of n search results.
verbosity (int, optional): The amount of data returned with each search result. 0 == no search results, only the recommended context. 1 == search results but no searchData. 2 == search results and searchData.
filter (dict, optional): A dictionary of key-value pairs that can be used to pre-filter documents prior to a search.
relevanced (float, optional): The minimum search relevance score required to include the result. Defaults to 10.0.
"""
client = AsyncGroundX(api_key=groundx_api_key)
try:
params = {"document_ids": document_ids, "query": query}
if n is not None:
params["n"] = n
if next_token is not None:
params["next_token"] = next_token
if verbosity is not None:
params["verbosity"] = verbosity
if filter is not None:
params["filter"] = filter
if relevanced is not None:
params["relevanced"] = relevanced
response = await client.search.documents(**params)
return response
except Exception as e:
return {"error": f"Failed to search documents: {str(e)}"}
