import csv
from datetime import datetime
import os
from typing import Optional
import gradio as gr

#from convert import convert
from huggingface_hub import HfApi, Repository


# DATASET_REPO_URL = "https://huggingface.co/datasets/safetensors/conversions"
# DATA_FILENAME = "data.csv"
# DATA_FILE = os.path.join("data", DATA_FILENAME)

# HF_TOKEN = os.environ.get("HF_TOKEN")

# repo: Optional[Repository] = None
# # TODO
# if False and HF_TOKEN:
#     repo = Repository(local_dir="data", clone_from=DATASET_REPO_URL, token=HF_TOKEN)


def run(model_id: str, token: Optional[str] = None) -> str:
    print(model_id + ' ' + token)
    return model_id + ' ' + token


DESCRIPTION = """
The steps are the following:

- Paste a read-access token from hf.co/settings/tokens. Read access is enough given that we will open a PR against the source repo.
- Input a model id from the Hub
- Click "Submit"
- That's it! You'll get feedback if it works or not, and if it worked, you'll get the URL of the opened PR 🔥

⚠️ For now only `pytorch_model.bin` files are supported but we'll extend in the future.
"""

title="Convert any model to Safetensors and open a PR"
allow_flagging="never"

with gr.Blocks(title=title) as demo:
    description = gr.Markdown(f"""# {title}""")
    description = gr.Markdown(DESCRIPTION)

    with gr.Row() as r:
        with gr.Column() as c:
            model_id = gr.Text(max_lines=1, label="model_id")
            token = gr.Text(max_lines=1, label="your_hf_token")
            with gr.Row() as c:
                clean = gr.ClearButton()
                submit = gr.Button("Submit", variant="primary")

        with gr.Column() as d:
            output = gr.Markdown()

    submit.click(run, inputs=[model_id, token], outputs=output, concurrency_limit=1)





demo.queue(max_size=10).launch(show_api=True)