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>
120 lines
2.6 KiB
Python
120 lines
2.6 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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"""
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Pydantic models for API request/response schemas
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"""
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from .training import (
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TrainingStartRequest,
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TrainingJobResponse,
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TrainingStatus,
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TrainingProgress,
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)
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from .models import (
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CheckpointInfo,
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ModelCheckpoints,
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CheckpointListResponse,
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ModelDetails,
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LocalModelInfo,
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LocalModelListResponse,
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LoRAInfo,
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LoRAScanResponse,
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ModelListResponse,
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)
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from .auth import (
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AuthSetupRequest,
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AuthLoginRequest,
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RefreshTokenRequest,
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AuthStatusResponse,
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)
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from .export import (
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LoadCheckpointRequest,
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ExportStatusResponse,
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ExportOperationResponse,
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ExportMergedModelRequest,
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ExportBaseModelRequest,
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ExportGGUFRequest,
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ExportLoRAAdapterRequest,
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)
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from .users import Token
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from .datasets import (
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CheckFormatRequest,
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CheckFormatResponse,
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)
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from .inference import (
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LoadRequest,
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UnloadRequest,
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GenerateRequest,
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LoadResponse,
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UnloadResponse,
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InferenceStatusResponse,
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)
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from .responses import (
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TrainingStopResponse,
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TrainingMetricsResponse,
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LoRABaseModelResponse,
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VisionCheckResponse,
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EmbeddingCheckResponse,
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)
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from .data_recipe import (
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RecipePayload,
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PreviewResponse,
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ValidateError,
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ValidateResponse,
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JobCreateResponse,
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)
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__all__ = [
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# Training schemas
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"TrainingStartRequest",
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"TrainingJobResponse",
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"TrainingStatus",
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"TrainingProgress",
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# Model management schemas
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"ModelDetails",
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"LocalModelInfo",
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"LocalModelListResponse",
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"LoRAInfo",
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"LoRAScanResponse",
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"ModelListResponse",
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# Auth schemas
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"AuthSetupRequest",
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"AuthLoginRequest",
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"RefreshTokenRequest",
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"AuthStatusResponse",
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# Export schemas
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"CheckpointInfo",
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"ModelCheckpoints",
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"CheckpointListResponse",
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"LoadCheckpointRequest",
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"ExportStatusResponse",
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"ExportOperationResponse",
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"ExportMergedModelRequest",
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"ExportBaseModelRequest",
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"ExportGGUFRequest",
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"ExportLoRAAdapterRequest",
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"Token",
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# Dataset schemas
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"CheckFormatRequest",
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"CheckFormatResponse",
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# Inference schemas
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"LoadRequest",
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"UnloadRequest",
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"GenerateRequest",
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"LoadResponse",
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"UnloadResponse",
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"InferenceStatusResponse",
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# Response schemas
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"TrainingStopResponse",
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"TrainingMetricsResponse",
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"LoRABaseModelResponse",
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"VisionCheckResponse",
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"EmbeddingCheckResponse",
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# Data recipe
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"RecipePayload",
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"PreviewResponse",
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"ValidateError",
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"ValidateResponse",
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"JobCreateResponse",
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]
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