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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."
)
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