import csv
import os
from datetime import datetime
from typing import Optional, Union
import gradio as gr
from huggingface_hub import HfApi, Repository
from export import convert
from gradio_huggingfacehub_search import HuggingfaceHubSearch


DATASET_REPO_URL = "https://huggingface.co/datasets/optimum/exporters"
DATA_FILENAME = "data.csv"
DATA_FILE = os.path.join("openvino", DATA_FILENAME)
HF_TOKEN = os.environ.get("HF_WRITE_TOKEN")
DATA_DIR = "exporters_data"

repo = None
if HF_TOKEN:
    repo = Repository(local_dir=DATA_DIR, clone_from=DATASET_REPO_URL, token=HF_TOKEN)


def export(model_id: str, task: str, oauth_token: gr.OAuthToken) -> str:

    if oauth_token.token is None:
        raise ValueError("You must be logged in to use this space")
    token = oauth_token.token

    if model_id == "" or token == "":
        return """
        ### Invalid input 🐞
        Please fill a token and model name.
        """
    try:
        api = HfApi(token=token)

        error, commit_info = convert(api=api, model_id=model_id, task=task, force=False)
        if error != "0":
            return error

        print("[commit_info]", commit_info)

        # save in a private dataset
        if repo is not None:
            repo.git_pull(rebase=True)
            with open(os.path.join(DATA_DIR, DATA_FILE), "a") as csvfile:
                writer = csv.DictWriter(csvfile, fieldnames=["model_id", "pr_url", "time"])
                writer.writerow(
                    {
                        "model_id": model_id,
                        "pr_url": commit_info.pr_url,
                        "time": str(datetime.now()),
                    }
                )
            commit_url = repo.push_to_hub()
            print("[dataset]", commit_url)

        return f"#### Success 🔥 Yay! This model was successfully exported and a PR was open using your token, here: [{commit_info.pr_url}]({commit_info.pr_url})"
    except Exception as e:
        return f"#### Error: {e}"


TTILE_IMAGE = """
<div
    style="
        display: block;
        margin-left: auto;
        margin-right: auto;
        width: 50%;
    "
>
<img src="https://huggingface.co/spaces/echarlaix/openvino-export/resolve/main/header.png"/>
</div>
"""

TITLE = """
<div
    style="
        display: inline-flex;
        align-items: center;
        text-align: center;
        max-width: 1400px;
        gap: 0.8rem;
        font-size: 2.2rem;
    "
>
<h1 style="text-align:center; font-weight: 1200">
    Export your model to OpenVINO
</h1>
</div>
"""

DESCRIPTION = """
This Space uses [Optimum Intel](https://huggingface.co/docs/optimum/intel/inference) to automatically export your model to the OpenVINO format.

After the model conversion, we will open a PR against the source repo to add the resulting model.

To export your model you need:
- A Model ID from the Hub

That's it ! 🔥
"""



model_id = HuggingfaceHubSearch(
    label="Hub Model ID",
    placeholder="Search for model id on the hub",
    search_type="model",
)
task = gr.Textbox(
    value="auto",
    label="Task : can be left to auto, will be automatically inferred",
)
interface = gr.Interface(
    fn=export,
    inputs=[
        model_id,
        task,
    ],
    outputs=[
        gr.Markdown(label="output"),
    ],
    title=TITLE,
    description=DESCRIPTION,
    api_name=False,
)

with gr.Blocks() as demo:
    gr.Markdown("You must be logged in to use this space")
    gr.LoginButton(min_width=250)
    interface.render()

demo.launch()