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("anli_r1", "acc", "ANLI")
    task1 = Task("logiqa", "acc_norm", "LogiQA")

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



# Your leaderboard name
TITLE = """
<div align="center">
    <h1>🪷 LOTUS: Detailed LVLM Evaluation from Quality to Societal Bias</h1>
</div>
"""

# What does your leaderboard evaluate?
INTRODUCTION_TEXT = """

We introduce **LOTUS**, a leaderboard for evaluating detailed captions, addressing three main gaps in existing evaluations: lack of **standardized** criteria, **bias-aware** assessments, and **user preference** considerations. 
LOTUS comprehensively evaluates various aspects, including caption quality (e.g., alignment, descriptiveness), risks (e.g., hallucination), and societal biases (e.g., gender bias) while enabling preference-oriented evaluations by tailoring criteria to diverse user preferences.

"""

# Which evaluations are you running? how can people reproduce what you have?
LLM_BENCHMARKS_TEXT = """
Details about the LLM benchmarks will go here.
"""

EVALUATION_QUEUE_TEXT = """
## Evaluation Queue and Submission

Models are evaluated on the private test set of COCO Captions, and results are protected from misuse.

**To submit your model for evaluation, please follow these steps:**

1. **Prepare your model's predictions**: Ensure your model's predictions are in the same format as the COCO Captions [dataset](https://cocodataset.org/#format-data).
2. **Submit via our form**: Fill out the [submission form](https://forms.gle/your_form_link_here) with your model details and prediction file.
3. **Wait for results**: The evaluation may take some time. Results will be updated on the leaderboard.

For any issues or questions, please open an issue on our [GitHub repository](https://github.com/lotus-benchmark/lotus).
"""

CITATION_BUTTON_LABEL = "BibTeX" # Keep this label or change if needed

CITATION_BUTTON_TEXT = """
@inproceedings{hirota2025lotus,
  author    = {Yusuke Hirota and Boyi Li and Ryo Hachiuma and Yueh-Hua Wu and Boris Ivanovic and Yuta Nakashima and Marco Pavone and Yejin Choi and Yu-Chiang Frank Wang and Huck Yang},
  title     = {LOTUS: {A} Leaderboard for Detailed Image Captioning from Quality to Societal Bias and User Preferences},
  booktitle = {Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL)},
  year      = {2025}
}
"""