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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]
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