f08aef1804
* Rebuild Studio branch on top of main * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix security and code quality issues for Studio PR #4237 - Validate models_dir query param against allowed directory roots to prevent path traversal in /api/models/local endpoint - Replace string startswith() with Path.is_relative_to() for frontend path traversal check in serve_frontend - Sanitize SSE error messages to not leak exception details to clients (4 locations in inference.py) - Bind port-discovery socket to 127.0.0.1 instead of all interfaces in llama_cpp backend - Import datasets_root and resolve_output_dir in embedding training function to fix NameError and use managed output directory - Remove stale .gitignore entries for package-lock.json and test directories so tests can be tracked in version control - Add venv-reexecution logic to ui CLI command matching the studio command behavior * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Move models_dir path validation before try/except block The HTTPException(403) was inside the try/except Exception handler, so it would be caught and re-raised as a 500. Moving the validation before the try block ensures the 403 is returned directly and also makes the control flow clearer for static analysis (path is validated before any filesystem operations). * Use os.path.realpath + startswith for models_dir validation CodeQL py/path-injection does not recognize Path.is_relative_to() as a sanitizer. Switched to os.path.realpath + str.startswith which is a recognized sanitizer pattern in CodeQL's taint analysis. The startswith check uses root_str + os.sep to prevent prefix collisions (e.g. /app/models_evil matching /app/models). * Never pass user input to Path constructor in models_dir validation CodeQL traces taint through Path(resolved) even after a startswith barrier guard. Fix: the user-supplied models_dir is only used as a string for comparison against allowed roots. The Path object passed to _scan_models_dir comes from the trusted allowed_roots list, not from user input. This fully breaks the taint chain. --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
76 lines
2.9 KiB
Python
76 lines
2.9 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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"""Logging configuration for structured logging with structlog.
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This module provides centralized logging configuration with environment-specific
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formats and processors. Supports both development and production environments
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with consistent structured logging.
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Key Features:
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- Environment-specific formatting (JSON for production, console for development)
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- Timestamp standardization (ISO format)
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- Context variable integration
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- Log level filtering
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- Logger caching for performance
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"""
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import logging
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import os
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import sys
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from typing import Optional
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import structlog
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class LogConfig:
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"""Structured logging configuration for the application.
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Provides static method to configure structlog with environment-specific
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formatting and processors for consistent structured logging.
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"""
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@staticmethod
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def setup_logging(
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service_name: str = "unsloth-studio-backend", env: Optional[str] = None
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) -> structlog.BoundLogger:
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"""Configure structured logging for the application.
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Args:
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service_name: Name of the service for logging identification
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env: Environment (development/production), affects logging format
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"""
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# Determine log level from environment
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log_level_name = os.getenv("LOG_LEVEL", "INFO").upper()
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# Fallback to INFO if an invalid level is provided
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log_level = getattr(logging, log_level_name, logging.INFO)
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structlog.configure(
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processors = [
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# Reorder processors to control field order
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structlog.processors.TimeStamper(fmt = "iso"), # timestamp first
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structlog.processors.add_log_level, # level second
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structlog.contextvars.merge_contextvars,
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# Custom processor to flatten the extra field
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lambda logger, method_name, event_dict: {
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"timestamp": event_dict.get("timestamp"),
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"level": event_dict.get("level"),
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"event": event_dict.get("event"),
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**(event_dict.get("extra", {})), # Flatten extra into main dict
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**{
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k: v
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for k, v in event_dict.items()
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if k not in ["timestamp", "level", "event", "extra"]
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},
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},
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(
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structlog.processors.JSONRenderer(sort_keys = False) # Preserve order
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if env == "production"
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else structlog.dev.ConsoleRenderer()
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),
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],
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wrapper_class = structlog.make_filtering_bound_logger(log_level),
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logger_factory = structlog.PrintLoggerFactory(file = sys.stdout),
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cache_logger_on_first_use = True,
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)
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return structlog.get_logger(service_name)
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