def lindorm_retrieve_from_index()

in src/lindorm_mcp_server/server.py [0:0]

• 7 lines of code
• 2 McCabe index (conditional complexity)

def lindorm_retrieve_from_index(index_name: str, query: str,  content_field: str, vector_field: str,
                                top_k: int = 5, ctx: Context = None) -> str:
    """
    Retrieve from an existing indexes(or knowledgebase) using both full-text search and vector search, and return the aggregated results
    :param index_name: the index name, or known as knowledgebase name
    :param query: the query that you want to search in knowledgebase
    :param content_field: the text field that store the content text. You can get it from the index structure by lindorm_get_index_mappings tool
    :param vector_field: the vector field that store the vector index. You can get it from the index structure by lindorm_get_index_mappings tool
    :param top_k: the result number that you want to return
    :return: the most relevant content stored in the knowledgebase.
    """
    lindorm_search_client = ctx.request_context.lifespan_context.lindorm_search_client
    contents = lindorm_search_client.rrf_search(index_name, query, top_k, content_field, vector_field)
    output = f"The retrieving results for query {query} in knowledgebase {index_name} is\n"
    output += "\n".join(f"{i + 1}. {content}" for i, content in enumerate(contents))
    return output