"""
Access and manage a feature-based learning-to-rank (Ltr) reranker.
"""

# Copyright (c) 2025, Carnegie Mellon University.  All Rights Reserved.

import PyLu				# Used to access RankLib
import Util				# Used to read and write files

from QryParser import QryParser		# Parse queries

class RerankWithLtr:
    """
    Access and manage a feature-based learning-to-rank (Ltr) reranker.
    """

    # -------------- Methods (alphabetical) ---------------- #

    def __init__(self, parameters):

        # Store the parameters for the LTR reranker

        # Initialization is a good time to create the model that will
        # be used for reranking. Cleaner code probably does this in a
        # separate function.
        # - Get training data from .trainQry and .trainQrels files
        # - Generate feature vectors for each (qid, docid) tuple
        # - Possibly normalize vectors
        # - Write vectors to file
        # - Call the toolkit to train a model
        pass
        

    def rerank(self, batch):
        """
        Update the results for a set of queries with new scores.

        batch: A dict of {qid: {'qstring': qstring,
                                'ranking': [(score, externalId) ...]}
                          ... }
        """

        # Generate feature vectors for each (qid, docid) tuple

        # Possibly normalize vectors

        # Write vectors to file

        # Call the toolkit to generate new scores

        # Use the new scores to update results

        return(results)