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chore: import upstream snapshot with attribution
2026-07-13 12:59:56 +08:00

164 lines
5.4 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""Shared backend utilities."""
import os
import structlog
from loggers import get_logger
from contextlib import contextmanager
from pathlib import Path
import shutil
import tempfile
logger = get_logger(__name__)
# ── Client-safe error helpers ───────────────────────────────────
# Never return raw exception text to clients; log server-side, return generic.
def safe_error_detail(error: Exception, fallback: str = "An internal error occurred") -> str:
"""Map an exception to a generic, client-safe message (never raw
``str(error)``, which can leak paths). Log the real exception server-side.
"""
text = str(error).lower()
if (
isinstance(error, (ConnectionError, TimeoutError))
or "connection" in text
or "timed out" in text
or "timeout" in text
):
return "Could not reach an upstream service. Please try again."
if "out of memory" in text or "cuda error" in text:
return "Ran out of memory. Try a smaller model or shorter input."
return fallback
def safe_curated_detail(error: Exception, fallback: str = "An internal error occurred") -> str:
"""Client-safe text for curated domain/validation exceptions.
Keeps the message (paths stripped) instead of a generic fallback; for known
exception types only (use ``safe_error_detail`` for generic ``Exception``).
"""
from utils.native_path_leases import redact_native_paths
msg = redact_native_paths(str(error)).strip()
return msg or fallback
def log_and_http_error(
error: Exception,
status_code: int,
public_message: str,
*,
event: str = "request_failed",
log = None,
):
"""Log ``error`` in full server-side and return an ``HTTPException`` whose
``detail`` is only ``public_message`` -- never the raw exception text.
Usage: raise log_and_http_error(e, 500, "Failed to start training")
"""
from fastapi import HTTPException
# exc_info=error works for both structlog and stdlib loggers.
(log or logger).error(f"{event}: {error}", exc_info = error)
return HTTPException(status_code = status_code, detail = public_message)
@contextmanager
def without_hf_auth():
"""
Temporarily disable HuggingFace authentication.
Usage:
with without_hf_auth():
# Code that should run without cached tokens
model_info(model_name, token=None)
"""
saved_env = {}
env_vars = ["HF_TOKEN", "HUGGINGFACE_HUB_TOKEN", "HF_HOME"]
for var in env_vars:
if var in os.environ:
saved_env[var] = os.environ[var]
del os.environ[var]
saved_disable = os.environ.get("HF_HUB_DISABLE_IMPLICIT_TOKEN")
os.environ["HF_HUB_DISABLE_IMPLICIT_TOKEN"] = "1"
# Move token files aside temporarily
token_files = []
token_locations = [
Path.home() / ".cache" / "huggingface" / "token",
Path.home() / ".huggingface" / "token",
]
for token_loc in token_locations:
if token_loc.exists():
temp = tempfile.NamedTemporaryFile(delete = False)
temp.close()
shutil.move(str(token_loc), temp.name)
token_files.append((token_loc, temp.name))
try:
yield
finally:
# Restore tokens
for original, temp in token_files:
try:
original.parent.mkdir(parents = True, exist_ok = True)
shutil.move(temp, str(original))
except Exception as e:
logger.error(f"Failed to restore token {original}: {e}")
# Restore env
for var, value in saved_env.items():
os.environ[var] = value
if saved_disable is not None:
os.environ["HF_HUB_DISABLE_IMPLICIT_TOKEN"] = saved_disable
else:
os.environ.pop("HF_HUB_DISABLE_IMPLICIT_TOKEN", None)
def format_error_message(error: Exception, model_name: str) -> str:
"""
Format a user-friendly error message for common load issues.
Args:
error: The exception that occurred
model_name: Name of the model being loaded
"""
error_str = str(error).lower()
model_short = model_name.split("/")[-1] if "/" in model_name else model_name
if "repository not found" in error_str or "404" in error_str:
return f"Model '{model_short}' not found. Check the model name."
if "401" in error_str or "unauthorized" in error_str:
return f"Authentication failed for '{model_short}'. Please provide a valid HF token."
if "gated" in error_str or "access to model" in error_str:
return f"Model '{model_short}' requires authentication. Please provide a valid HF token."
if "invalid user token" in error_str:
return "Invalid HF token. Please check your token and try again."
if (
"memory" in error_str
or "cuda" in error_str
or "mlx" in error_str
or "out of memory" in error_str
):
from utils.hardware import get_device
device = get_device()
device_label = {"cuda": "GPU", "mlx": "Apple Silicon GPU", "cpu": "system"}.get(
device.value, "GPU"
)
return f"Not enough {device_label} memory to load '{model_short}'. Try a smaller model or free memory."
return str(error)