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