compute_ndcg:v0
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import weave
from typing import List
from typing import Dict
from typing import Any
import numpy as np
@weave.op()
def compute_ndcg(
model_output: List[Dict[str, Any]], contexts: List[Dict[str, Any]]
) -> float:
"""
Calculate the Normalized Discounted Cumulative Gain (NDCG) for a single query.
Args:
model_output (List[Dict[str, Any]]): The list of retrieved documents from the model.
Each dictionary contains:
- 'source': A unique identifier for the document.
contexts (List[Dict[str, Any]]): A list of dictionaries representing the relevant contexts.
Each dictionary contains:
- 'source': A unique identifier for the relevant document.
- 'relevance': The relevance score of the document (0, 1, or 2).
Returns:
float: The NDCG score for the given query.
"""
relevance_map = {context["source"]: context["relevance"] for context in contexts}