from huggingface_hub import CommitOperationAdd, create_commit, HfApi, HfFileSystem, login
from huggingface_hub.utils import RepositoryNotFoundError as deneme
from openllm import *
import gradio as gr
import requests
import pandas as pd

api = HfApi()
fs = HfFileSystem()

data = get_json_format_data()
finished_models = get_datas(data)
df = pd.DataFrame(finished_models)


def search(df, value):
    result_df = df[df["Model"] == value]
    return result_df.iloc[0].to_dict() if not result_df.empty else None


def get_details_url(repo):
   author, model = repo.split("/")
   return f"https://huggingface.co/datasets/open-llm-leaderboard/details_{author}__{model}"


def get_eval_results(repo):
  results = search(df, repo)

  text = f"""
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here]({get_details_url(repo)})

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | {results['Average ⬆️']}   |
| ARC (25-shot)         | {results['ARC']}          |
| HellaSwag (10-shot)   | {results['HellaSwag']}    |
| MMLU (5-shot)         | {results['MMLU']}         |
| TruthfulQA (0-shot)   | {results['TruthfulQA']}   |
| Winogrande (5-shot)   | {results['Winogrande']}   |
| GSM8K (5-shot)        | {results['GSM8K']}        |
| DROP (3-shot)         | {results['DROP']}         |
"""
  return text


desc = """
This is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr

The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.

If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions
"""


def commit(hf_token, repo):
  login(hf_token)
  try:
    try: # check if there is a readme already
      readme_text = fs.read_text(f"{repo}/README.md") + get_eval_results(repo)
    except:
      readme_text = get_eval_results(repo)

    liste = [CommitOperationAdd(path_in_repo="README.md", path_or_fileobj=readme_text.encode())]
    commit = (create_commit(repo_id=repo, operations=liste, commit_message=f"Adding Evaluation Results", commit_description=desc, repo_type="model", create_pr=True).__dict__['pr_url'])
    return commit
  except Exception as e: # unexpected error
    return e


demo = gr.Interface(fn=commit, inputs=["text", "text"], outputs="text")

demo.launch()