import json
import os
import uuid
from datetime import datetime, timezone

import gradio as gr
import spaces
from huggingface_hub import HfApi


DATASET_ID = os.environ["DATASET_ID"]
DATASET_TOKEN = os.environ["DATASET_TOKEN"]

api = HfApi(token=DATASET_TOKEN)


# ZeroGPU requires at least one @spaces.GPU function.
# This function is never called, so it does not consume GPU time.
@spaces.GPU
def zerogpu_probe():
    return None


def save_feedback(data: dict) -> dict:
    """Receives feedback data and stores it in the private HF dataset."""

    if not isinstance(data, dict):
        raise ValueError("data must be a JSON object")

    record = {
        "id": str(uuid.uuid4()),
        "timestamp": datetime.now(timezone.utc).isoformat(),
        **data,
    }

    content = json.dumps(record, ensure_ascii=False) + "\n"

    filename = f"incoming/{record['id']}.jsonl"

    api.upload_file(
        path_or_fileobj=content.encode("utf-8"),
        path_in_repo=filename,
        repo_id=DATASET_ID,
        repo_type="dataset",
        token=DATASET_TOKEN,
        commit_message="Add feedback record",
    )

    return {
        "success": True,
        "id": record["id"],
    }


demo = gr.Interface(
    fn=save_feedback,
    inputs=gr.JSON(label="Feedback"),
    outputs=gr.JSON(label="Result"),
    api_name="save_feedback",
    title="Zayit Feedback API",
)


if __name__ == "__main__":
    demo.launch()