import json
import os
from datetime import datetime, timezone

from src.display.formatting import styled_error, styled_message
from src.envs import API, EVAL_REQUESTS_PATH, QUEUE_REPO


def add_new_eval(model: str, weight_type: str, gguf_filename=None):
    user_name = ""
    model_path = model
    if "/" in model:
        user_name = model.split("/")[0]
        model_path = model.split("/")[1]

    current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")

    # Is the model info correctly filled?
    try:
        model_info = API.model_info(repo_id=model, revision='main')
    except Exception:
        return styled_error("Could not get your model information.")
    
    if weight_type=="safetensors":
        if len(gguf_filename)!=0:
            return styled_error("GGUF filename should be empty when using safetensors.")

    # Seems good, creating the eval
    print("Adding new eval")

    eval_entry = {
        "model": model,
        "weight_type": weight_type,
        "gguf_filename": gguf_filename,
        "status": "PENDING",
        "submitted_time": current_time,
    }

    print("Creating eval file")
    OUT_DIR = f"{EVAL_REQUESTS_PATH}/{user_name}"
    os.makedirs(OUT_DIR, exist_ok=True)
    out_path = f"{OUT_DIR}/{model_path}_eval_request_{current_time}.json"

    with open(out_path, "w") as f:
        f.write(json.dumps(eval_entry))

    print("Uploading eval file")
    API.upload_file(
        path_or_fileobj=out_path,
        path_in_repo=out_path.split("eval-queue/")[1],
        repo_id=QUEUE_REPO,
        repo_type="dataset",
        commit_message=f"Add {model} to eval queue",
    )

    # Remove the local file
    os.remove(out_path)

    return styled_message(
        "Your request has been submitted to the evaluation queue!\nPlease wait for up to five minutes for the model to show in the PENDING list."
    )