from dataclasses import dataclass
from enum import Enum

@dataclass
class Task:
    benchmark: str
    metric: str
    col_name: str


# Select your tasks here
# ---------------------------------------------------
class Tasks(Enum):
    # task_key in the json file, metric_key in the json file, name to display in the leaderboard 
    task0 = Task("blimp", "acc", "BLiMP")
    task1 = Task("blimp_supplement", "acc", "BLiMP Supplement")
    task2 = Task("glue", "acc", "(Super)GLUE")
    task3 = Task("ewok", "acc", "EWoK")

class TasksMultimodal(Enum):
    task0 = Task("blimp", "acc", "BLiMP")
    task1 = Task("blimp_supplement", "acc", "BLiMP Supplement")
    task2 = Task("glue", "acc", "(Super)GLUE")
    task3 = Task("ewok", "acc", "EWoK")
    task4 = Task("vqa", "acc", "VQA")
    task5 = Task("winoground", "acc", "Winoground")
    task6 = Task("devbench", "acc", "DevBench")

NUM_FEWSHOT = 0 # Change with your few shot
# ---------------------------------------------------



# Your leaderboard name
TITLE = """<h1 align="center" id="space-title">BabyLM 2024 Leaderboards</h1>"""

# What does your leaderboard evaluate?
INTRODUCTION_TEXT = """
The leaderboards for each track of the 2024 BabyLM Challenge.
"""

# Which evaluations are you running? how can people reproduce what you have?
LLM_BENCHMARKS_TEXT = f"""
## How it works
This leaderboard accepts predictions files as input, and uploads the results to the leaderboard. The logic is the same as in the `score_predictions.py` script from the BabyLM 2024 evaluation pipeline repository.
"""

EVALUATION_QUEUE_TEXT = """
## Some good practices before submitting a model

### 1) Make sure you can get scores from your prediction using the `score_predictions.py` script.
```bash
git clone https://github.com/babylm/evaluation-pipeline-2024/
cd evaluation-pipeline-2024
python score_predictions.py path/to/your/predictions.json.gz
```
If this step fails, follow the error messages to debug your model before submitting it. It's likely that either (i) some results are missing, or (ii) the results are incorrectly formatted.

### 3) Make sure your model has an open license!
This is a leaderboard that is meant to advance research on language modeling, and we'd love for as many people as possible to know they can use your model!

### 4) Fill up your model card
When we add extra information about models to the leaderboard, it will be automatically taken from the model card.
"""

CITATION_BUTTON_LABEL = "If you would like to cite these results, please cite the 2024 BabyLM Findings paper, as well as the authors of the model(s) whose results you cite!"
CITATION_BUTTON_TEXT = r"""
"""