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from dataclasses import dataclass, make_dataclass | |
from src.benchmarks import BenchmarksQA, BenchmarksLongDoc | |
def fields(raw_class): | |
return [v for k, v in raw_class.__dict__.items() if k[:2] != "__" and k[-2:] != "__"] | |
# These classes are for user facing column names, | |
# to avoid having to change them all around the code | |
# when a modification is needed | |
class ColumnContent: | |
name: str | |
type: str | |
displayed_by_default: bool | |
hidden: bool = False | |
never_hidden: bool = False | |
COL_NAME_AVG = "Average ⬆️" | |
COL_NAME_RETRIEVAL_MODEL = "Retrieval Model" | |
COL_NAME_RERANKING_MODEL = "Reranking Model" | |
COL_NAME_RETRIEVAL_MODEL_LINK = "Retrieval Model LINK" | |
COL_NAME_RERANKING_MODEL_LINK = "Reranking Model LINK" | |
COL_NAME_RANK = "Rank 🏆" | |
COL_NAME_REVISION = "Revision" | |
COL_NAME_TIMESTAMP = "Submission Date" | |
def get_default_auto_eval_column_dict(): | |
auto_eval_column_dict = [] | |
# Init | |
auto_eval_column_dict.append( | |
["rank", ColumnContent, ColumnContent(COL_NAME_RANK, "number", True)] | |
) | |
auto_eval_column_dict.append( | |
["retrieval_model", ColumnContent, ColumnContent(COL_NAME_RETRIEVAL_MODEL, "markdown", True, hidden=False, never_hidden=True)] | |
) | |
auto_eval_column_dict.append( | |
["reranking_model", ColumnContent, ColumnContent(COL_NAME_RERANKING_MODEL, "markdown", True, hidden=False, never_hidden=True)] | |
) | |
auto_eval_column_dict.append( | |
["revision", ColumnContent, ColumnContent(COL_NAME_REVISION, "markdown", True, never_hidden=True)] | |
) | |
auto_eval_column_dict.append( | |
["timestamp", ColumnContent, ColumnContent(COL_NAME_TIMESTAMP, "date", True, never_hidden=True)] | |
) | |
auto_eval_column_dict.append( | |
["average", ColumnContent, ColumnContent(COL_NAME_AVG, "number", True)] | |
) | |
auto_eval_column_dict.append( | |
["retrieval_model_link", ColumnContent, ColumnContent(COL_NAME_RETRIEVAL_MODEL, "markdown", False, hidden=True, never_hidden=False)] | |
) | |
auto_eval_column_dict.append( | |
["reranking_model_link", ColumnContent, ColumnContent(COL_NAME_RERANKING_MODEL, "markdown", False, hidden=True, never_hidden=False)] | |
) | |
return auto_eval_column_dict | |
def make_autoevalcolumn(cls_name="BenchmarksQA", benchmarks=BenchmarksQA): | |
auto_eval_column_dict = get_default_auto_eval_column_dict() | |
## Leaderboard columns | |
for benchmark in benchmarks: | |
auto_eval_column_dict.append( | |
[benchmark.name, ColumnContent, ColumnContent(benchmark.value.col_name, "number", True)] | |
) | |
# We use make dataclass to dynamically fill the scores from Tasks | |
return make_dataclass(cls_name, auto_eval_column_dict, frozen=True) | |
AutoEvalColumnQA = make_autoevalcolumn( | |
"AutoEvalColumnQA", BenchmarksQA) | |
AutoEvalColumnLongDoc = make_autoevalcolumn( | |
"AutoEvalColumnLongDoc", BenchmarksLongDoc) | |
# Column selection | |
COLS_QA = [c.name for c in fields(AutoEvalColumnQA) if not c.hidden] | |
COLS_LONG_DOC = [c.name for c in fields(AutoEvalColumnLongDoc) if not c.hidden] | |
TYPES_QA = [c.type for c in fields(AutoEvalColumnQA) if not c.hidden] | |
TYPES_LONG_DOC = [c.type for c in fields(AutoEvalColumnLongDoc) if not c.hidden] | |
COLS_LITE = [c.name for c in fields(AutoEvalColumnQA) if c.displayed_by_default and not c.hidden] | |
QA_BENCHMARK_COLS = [t.value.col_name for t in BenchmarksQA] | |
LONG_DOC_BENCHMARK_COLS = [t.value.col_name for t in BenchmarksLongDoc] |