from dataclasses import dataclass, make_dataclass from enum import Enum import pandas as pd from src.about import Tasks 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 modif is needed @dataclass class ColumnContent: name: str type: str displayed_by_default: bool hidden: bool = False never_hidden: bool = False ## Leaderboard columns auto_eval_column_dict = [] # Init auto_eval_column_dict.append(["library_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)]) auto_eval_column_dict.append(["library", ColumnContent, ColumnContent("Library", "markdown", True, never_hidden=True)]) #Scores auto_eval_column_dict.append(["overall_risk", ColumnContent, ColumnContent("Overall Risk ⬇️", "number", True)]) for task in Tasks: auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "number", True)]) # Library information auto_eval_column_dict.append(["library_type", ColumnContent, ColumnContent("Type", "str", False)]) auto_eval_column_dict.append(["framework", ColumnContent, ColumnContent("Framework", "str", False)]) auto_eval_column_dict.append(["version", ColumnContent, ColumnContent("Version", "str", False, False)]) auto_eval_column_dict.append(["language", ColumnContent, ColumnContent("Language", "str", False)]) auto_eval_column_dict.append(["license_name", ColumnContent, ColumnContent("License", "str", True)]) auto_eval_column_dict.append(["stars", ColumnContent, ColumnContent("GitHub ⭐", "number", False)]) auto_eval_column_dict.append(["last_update", ColumnContent, ColumnContent("Last Updated", "str", False)]) auto_eval_column_dict.append(["verified", ColumnContent, ColumnContent("Independently Verified", "bool", False)]) auto_eval_column_dict.append(["availability", ColumnContent, ColumnContent("Active Maintenance", "bool", True)]) auto_eval_column_dict.append(["report_url", ColumnContent, ColumnContent("Report", "html", True)]) # We use make dataclass to dynamically fill the scores from Tasks AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True) ## For the queue columns in the submission tab @dataclass(frozen=True) class EvalQueueColumn: # Queue column library = ColumnContent("library", "markdown", True) version = ColumnContent("version", "str", True) language = ColumnContent("language", "str", True) framework = ColumnContent("framework", "str", True) library_type = ColumnContent("library_type", "str", True) status = ColumnContent("status", "str", True) ## All the library information that we might need @dataclass class LibraryDetails: name: str display_name: str = "" symbol: str = "" # emoji class LibraryType(Enum): ML = LibraryDetails(name="machine learning", symbol="🟢") LLM = LibraryDetails(name="llm framework", symbol="🔶") AGENT = LibraryDetails(name="agent framework", symbol="⭕") VIS = LibraryDetails(name="visualization", symbol="🟦") GENERAL = LibraryDetails(name="general ai", symbol="🟣") Unknown = LibraryDetails(name="", symbol="?") def to_str(self, separator=" "): return f"{self.value.symbol}{separator}{self.value.name}" @staticmethod def from_str(type): if "machine learning" in type or "🟢" in type: return LibraryType.ML if "llm framework" in type or "🔶" in type: return LibraryType.LLM if "agent framework" in type or "⭕" in type: return LibraryType.AGENT if "visualization" in type or "🟦" in type: return LibraryType.VIS if "general ai" in type or "🟣" in type: return LibraryType.GENERAL return LibraryType.Unknown class Language(Enum): Python = LibraryDetails("Python") JavaScript = LibraryDetails("JavaScript") TypeScript = LibraryDetails("TypeScript") Java = LibraryDetails("Java") CPP = LibraryDetails("C++") Other = LibraryDetails("Other") class AssessmentStatus(Enum): Verified = LibraryDetails("Verified") Unverified = LibraryDetails("Unverified") Disputed = LibraryDetails("Disputed") # Column selection COLS = [c.name for c in fields(AutoEvalColumn) if not c.hidden] EVAL_COLS = [c.name for c in fields(EvalQueueColumn)] EVAL_TYPES = [c.type for c in fields(EvalQueueColumn)] # Task columns for benchmarking - use the display column names from the Tasks enum BENCHMARK_COLS = [task.value.col_name for task in Tasks]