* Studio: persistent per-user trust_remote_code approval cache The consent gate pins each approval to a content fingerprint (sha256 over every repo .py), but nothing was persisted, so the dialog reappeared on every fresh load of the same unchanged repo. This adds an on-disk, per-user approval cache that lets the gate skip the dialog when the same user reloads the same code, while keeping the safety guarantees intact. Two-tier validation, both must hold or the user is re-prompted: - Commit SHA (cheap, one HfApi.model_info().sha, no download): a match means a byte-identical tree to the approved revision, so the scan/download is skipped. - Content fingerprint (authoritative): used whenever the SHA is unavailable (local path / offline) and always recomputed on a SHA miss. A new or edited .py changes both the SHA and the fingerprint, so it is caught in every mode. Safety: - Keyed per subject; one user's approval never auto-runs code for another. - CRITICAL is never stored or honored (guarded on both write and read), so a hand-edited store cannot smuggle in an auto-approval. - The malware (HF unsafe-file) gate stays unconditional. - Fail-safe: a corrupt store, an unresolvable SHA, or any error degrades to "ask again", never to "auto-approve". UNSLOTH_TRC_APPROVAL_CACHE_DISABLE=1 turns the cache off entirely. New module utils/security/remote_code_approvals.py holds the store (studio_root()/security/remote_code_approvals.json, atomic write, 0600, RLock) plus the SHA resolvers. Recording happens at the single gate chokepoint when the caller supplies the matching fingerprint, so subject is just threaded through inference/training/export (orchestrators, routes, workers). The scan endpoint returns already_approved so the frontend can skip the dialog on a cache hit. Tests: new tests/test_trc_approval_cache.py covers cache miss, SHA-match skip, SHA-moved re-scan, new-file re-consent, CRITICAL never cached (write + forged read), disable flag, subject isolation, combined adapter+base key, corrupt store, and no-subject bypass. Full security suite: 101 passed. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Address review: make the approval cache skip only the prompt, never the scan Codex found that the SHA "no-scan" fast path could run untrusted code without re-consent. Removed it; the gate now always re-scans and the cache only seeds the authoritative fingerprint check, so it can skip the dialog but never the scan. - CRITICAL is hard-blocked on every load (the scan always runs), so a hand-edited store that downgrades a CRITICAL repo's severity can no longer auto-run it (P2: do not trust editable severity for SHA approvals). - The fingerprint covers external auto_map repos, so changed third-party code always re-prompts even when the primary commit SHA is unchanged; there is no longer a SHA path that bypasses the fingerprint (P1: external auto_map repos). - resolve_commit_sha is resolved fresh on every call (no memoization), so a repo whose default branch moves after approval re-prompts instead of reusing a stale cached SHA (P1: revalidate mutable Hub SHAs). The SHA is now only a conservative secondary gate: a fresh resolvable SHA must match the approved revision, else the seed is withheld; a None (local/offline) falls back to the fingerprint. - Approvals record the scanner ruleset version (SCAN_RULES_VERSION); the gate ignores approvals from an older ruleset so reclassified bytes are re-scanned and re-shown instead of silently auto-approved (P2: invalidate on scan-policy change). Tests: test_trc_approval_cache.py rewritten around the prompt-skip semantics (unchanged repo still scans; SHA move / changed code / scanner-version bump / disable flag all re-prompt; forged downgraded severity still blocks CRITICAL). 105 passed with test_consent_gate.py. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Trim comments to be more succinct * Keep run-owner subject out of persisted config; serialize approval writes Threading subject (the run owner's username / API-key id) into the training config meant _sanitize_db_config persisted it into config_json, which training-history GET returns to any authenticated user, leaking who started a run in multi-user installs. Filter subject alongside the token fields; the worker still receives it from the live config. The approval store's RLock only guards one process, but approvals are recorded from separate inference/export/training subprocesses, so concurrent writers could clobber each other on os.replace and drop an approval (re-prompt). Hold a best-effort cross-process file lock around the read-modify-write. * Fail safe on a malformed approval store A store with the right version but a non-dict shape (e.g. a hand-edited "subjects": []) passed _load()'s check, then lookup chained .get() on a list and raised, breaking every remote-code load until the file was removed. Validate that subjects is a dict in _load(), and tolerate a non-dict per-subject entry in lookup/record/forget, so a corrupt store fails safe (re-prompt) instead. * Keep subject out of the MLX W&B run config _run_mlx_training uploads the whole training config to W&B minus a sensitive set that only listed hf_token/wandb_token/s3_config, so the authenticated subject (username / API-key id) was sent to W&B as run config even though DB history already strips it. Add subject to the W&B-sensitive filter, mirroring training._sanitize_db_config. * Tighten the W&B subject-filter comment --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
549 lines
20 KiB
Python
549 lines
20 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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"""Export API routes: checkpoint discovery and model export operations."""
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import asyncio
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import json
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import os
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import sys
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import time
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from pathlib import Path
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from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple
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from fastapi import APIRouter, Depends, HTTPException, Query, Request
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from fastapi.responses import StreamingResponse
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import structlog
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from loggers import get_logger
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backend_path = Path(__file__).parent.parent.parent
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if str(backend_path) not in sys.path:
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sys.path.insert(0, str(backend_path))
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from auth.authentication import get_current_subject
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from utils.utils import safe_error_detail
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try:
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from core.export import get_export_backend
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except ImportError:
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parent_backend = backend_path.parent / "backend"
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if str(parent_backend) not in sys.path:
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sys.path.insert(0, str(parent_backend))
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from core.export import get_export_backend
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from models 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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router = APIRouter()
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logger = get_logger(__name__)
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@router.post("/load-checkpoint", response_model = ExportOperationResponse)
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async def load_checkpoint(
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request: LoadCheckpointRequest, current_subject: str = Depends(get_current_subject)
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):
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"""Load a checkpoint into the export backend (ExportBackend.load_checkpoint).
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Export runs in its own subprocess and is allowed to run in parallel with
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training and inference. We deliberately do NOT stop training or unload the
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chat model here -- if the GPU runs out of memory the load/export fails with
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a clear error instead of tearing down the user's other running workloads.
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"""
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try:
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backend = get_export_backend()
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# Run in a worker thread (spawns and waits on a subprocess, can take
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# minutes) so the event loop stays free to serve the live log SSE stream.
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success, message = await asyncio.to_thread(
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backend.load_checkpoint,
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checkpoint_path = request.checkpoint_path,
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max_seq_length = request.max_seq_length,
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load_in_4bit = request.load_in_4bit,
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trust_remote_code = request.trust_remote_code,
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approved_remote_code_fingerprint = request.approved_remote_code_fingerprint,
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hf_token = request.hf_token,
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subject = current_subject,
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)
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if not success:
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raise HTTPException(status_code = 400, detail = message)
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return ExportOperationResponse(success = True, message = message)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error loading checkpoint: {e}", exc_info = True)
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raise HTTPException(
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status_code = 500,
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detail = "Failed to load checkpoint",
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)
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@router.post("/cleanup", response_model = ExportOperationResponse)
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async def cleanup_export_memory(current_subject: str = Depends(get_current_subject)):
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"""Cleanup export-related models from memory (ExportBackend.cleanup_memory)."""
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try:
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backend = get_export_backend()
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success = await asyncio.to_thread(backend.cleanup_memory)
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if not success:
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raise HTTPException(
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status_code = 500,
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detail = "Memory cleanup failed. See server logs for details.",
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)
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return ExportOperationResponse(
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success = True,
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message = "Memory cleanup completed successfully",
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error during export memory cleanup: {e}", exc_info = True)
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raise HTTPException(
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status_code = 500,
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detail = "Failed to cleanup export memory",
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)
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@router.post("/cancel", response_model = ExportOperationResponse)
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async def cancel_export(current_subject: str = Depends(get_current_subject)):
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"""Cancel the in-flight export by terminating its worker subprocess.
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Only the export subprocess is killed; training and inference run in their
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own subprocesses and keep going.
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"""
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try:
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backend = get_export_backend()
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cancelled = await asyncio.to_thread(backend.cancel_export)
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return ExportOperationResponse(
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success = True,
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message = "Export cancelled" if cancelled else "No active export to cancel",
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)
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except Exception as e:
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logger.error(f"Error cancelling export: {e}", exc_info = True)
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raise HTTPException(
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status_code = 500,
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detail = "Failed to cancel export",
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)
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@router.get("/status", response_model = ExportStatusResponse)
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async def get_export_status(current_subject: str = Depends(get_current_subject)):
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"""Get export backend status (loaded checkpoint, model type, PEFT flag)."""
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try:
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backend = get_export_backend()
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last_op = backend.get_last_op()
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# Relativise the recovered output path the same way the per-op POST response
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# does, so the success banner shows an identical path on either route.
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last_op_output_path = None
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if last_op and last_op.get("output_path"):
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details = _export_details(last_op["output_path"])
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last_op_output_path = (details or {}).get("output_path")
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return ExportStatusResponse(
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current_checkpoint = backend.current_checkpoint,
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is_vision = bool(getattr(backend, "is_vision", False)),
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is_peft = bool(getattr(backend, "is_peft", False)),
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is_export_active = bool(backend.is_export_active()),
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active_op_kind = backend.get_active_op_kind(),
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last_op_seq = int(last_op["seq"]) if last_op else 0,
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last_op_kind = last_op.get("kind") if last_op else None,
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last_op_status = last_op.get("status") if last_op else None,
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last_op_output_path = last_op_output_path,
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last_op_error = last_op.get("error") if last_op else None,
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)
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except Exception as e:
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logger.error(f"Error getting export status: {e}", exc_info = True)
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raise HTTPException(
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status_code = 500,
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detail = "Failed to get export status",
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)
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@router.get("/logs")
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async def get_export_logs(
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since: Optional[int] = Query(
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None,
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description = "Return log entries with seq strictly greater than this cursor.",
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),
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current_subject: str = Depends(get_current_subject),
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):
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"""Tunnel-safe JSON fallback for the live export log stream.
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The SSE endpoint (`/logs/stream`) is the low-latency path, but some reverse
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proxies -- notably Cloudflare quick tunnels (`*.trycloudflare.com`) used by
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`--secure` mode -- buffer `text/event-stream` responses and only flush when
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the stream closes, so over the tunnel the browser sees nothing for the whole
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export ("connecting..." with no logs). This endpoint returns the same
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ring-buffer lines as a short, complete JSON response that no proxy buffers,
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so the frontend can poll it and still show logs in near real time.
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Shares the orchestrator's monotonic `seq` cursor with the SSE stream, so the
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two transports can run together and the client de-dupes by seq.
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"""
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try:
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backend = get_export_backend()
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# No cursor on the first poll of a run: start from the run-start snapshot
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# so the client gets every line since the run began (matches the SSE
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# default), not the entire historical ring buffer.
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if since is None:
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cursor = backend.get_run_start_seq()
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else:
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cursor = max(0, int(since))
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entries, new_cursor = backend.get_logs_since(cursor)
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return {
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"entries": [
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{
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"seq": int(entry.get("seq", 0)),
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"stream": entry.get("stream", "stdout"),
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"line": entry.get("line", ""),
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"ts": entry.get("ts"),
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}
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for entry in entries
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],
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"cursor": new_cursor,
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"active": bool(backend.is_export_active()),
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}
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except Exception as e:
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logger.error(f"Error getting export logs: {e}", exc_info = True)
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raise HTTPException(
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status_code = 500,
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detail = "Failed to get export logs",
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)
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def _try_register_external_export(path: Path) -> tuple[bool, Optional[str]]:
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"""Best-effort registration so absolute exports show up in local scans."""
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try:
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from storage.studio_db import add_scan_folder
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folder = add_scan_folder(str(path))
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return True, str(folder.get("path") or path)
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except Exception as exc:
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logger.warning("Could not register export scan folder %s: %s", path, exc)
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return False, None
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def _export_details(output_path: Optional[str]) -> Optional[Dict[str, Any]]:
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"""Return relative export paths, keeping external absolute paths visible."""
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if not output_path:
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return None
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try:
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from utils.paths.storage_roots import exports_root
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path = Path(output_path)
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# If it's outside exports_root, return the full absolute path
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# so users can find their files on a different drive.
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if path.is_absolute():
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try:
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path.resolve().relative_to(exports_root().resolve())
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except ValueError:
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registered, registered_path = _try_register_external_export(path)
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return {
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"output_path": str(path),
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"scan_folder_registered": registered,
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"scan_folder_path": registered_path,
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}
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rel = os.path.relpath(output_path, exports_root())
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return {"output_path": rel}
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except Exception:
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return {"output_path": output_path}
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@router.post("/export/merged", response_model = ExportOperationResponse)
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async def export_merged_model(
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request: ExportMergedModelRequest, current_subject: str = Depends(get_current_subject)
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):
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"""Export a merged PEFT model (16-bit or 4-bit), optionally pushing to Hub.
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Wraps ExportBackend.export_merged_model.
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"""
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try:
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backend = get_export_backend()
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success, message, output_path = await asyncio.to_thread(
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backend.export_merged_model,
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save_directory = request.save_directory,
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format_type = request.format_type,
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push_to_hub = request.push_to_hub,
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repo_id = request.repo_id,
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hf_token = request.hf_token,
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private = request.private,
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)
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if not success:
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raise HTTPException(status_code = 400, detail = message)
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return ExportOperationResponse(
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success = True,
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message = message,
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details = _export_details(output_path),
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error exporting merged model: {e}", exc_info = True)
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raise HTTPException(
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status_code = 500,
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detail = "Failed to export merged model",
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)
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@router.post("/export/base", response_model = ExportOperationResponse)
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async def export_base_model(
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request: ExportBaseModelRequest, current_subject: str = Depends(get_current_subject)
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):
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"""Export a non-PEFT base model, optionally pushing to Hub.
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Wraps ExportBackend.export_base_model.
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"""
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try:
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backend = get_export_backend()
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success, message, output_path = await asyncio.to_thread(
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backend.export_base_model,
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save_directory = request.save_directory,
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push_to_hub = request.push_to_hub,
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repo_id = request.repo_id,
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hf_token = request.hf_token,
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private = request.private,
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base_model_id = request.base_model_id,
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)
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if not success:
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raise HTTPException(status_code = 400, detail = message)
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return ExportOperationResponse(
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success = True,
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message = message,
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details = _export_details(output_path),
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error exporting base model: {e}", exc_info = True)
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raise HTTPException(
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status_code = 500,
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detail = "Failed to export base model",
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)
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@router.post("/export/gguf", response_model = ExportOperationResponse)
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async def export_gguf(
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request: ExportGGUFRequest, current_subject: str = Depends(get_current_subject)
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):
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"""Export the current model to GGUF format, optionally pushing to Hub.
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Wraps ExportBackend.export_gguf.
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"""
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try:
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backend = get_export_backend()
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success, message, output_path = await asyncio.to_thread(
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backend.export_gguf,
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save_directory = request.save_directory,
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quantization_method = request.quantization_method,
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push_to_hub = request.push_to_hub,
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repo_id = request.repo_id,
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hf_token = request.hf_token,
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)
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if not success:
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raise HTTPException(status_code = 400, detail = message)
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return ExportOperationResponse(
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success = True,
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message = message,
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details = _export_details(output_path),
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error exporting GGUF model: {e}", exc_info = True)
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raise HTTPException(
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status_code = 500,
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detail = "Failed to export GGUF model",
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)
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@router.post("/export/lora", response_model = ExportOperationResponse)
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async def export_lora_adapter(
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request: ExportLoRAAdapterRequest, current_subject: str = Depends(get_current_subject)
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):
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"""Export only the LoRA adapter (if the loaded model is PEFT).
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Wraps ExportBackend.export_lora_adapter.
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"""
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try:
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backend = get_export_backend()
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success, message, output_path = await asyncio.to_thread(
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backend.export_lora_adapter,
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save_directory = request.save_directory,
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push_to_hub = request.push_to_hub,
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repo_id = request.repo_id,
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hf_token = request.hf_token,
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private = request.private,
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)
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if not success:
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raise HTTPException(status_code = 400, detail = message)
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return ExportOperationResponse(
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success = True,
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message = message,
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details = _export_details(output_path),
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error exporting LoRA adapter: {e}", exc_info = True)
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raise HTTPException(
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status_code = 500,
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detail = "Failed to export LoRA adapter",
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)
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# Live export log stream (Server-Sent Events).
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#
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# The export worker's stdout/stderr is piped to the orchestrator as log
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# entries (core/export/worker.py, orchestrator.py); this endpoint streams
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# them to the browser for a live terminal panel during export operations.
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#
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# Shape follows routes/training.py::stream_training_progress: each event
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# carries id/event/data, the stream starts with a `retry:` directive, and
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# `Last-Event-ID` is honored on reconnect.
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def _format_sse(
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data: str,
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event: str,
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event_id: Optional[int] = None,
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) -> str:
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"""Format a single SSE message with id/event/data fields."""
|
|
lines = []
|
|
if event_id is not None:
|
|
lines.append(f"id: {event_id}")
|
|
lines.append(f"event: {event}")
|
|
lines.append(f"data: {data}")
|
|
lines.append("")
|
|
lines.append("")
|
|
return "\n".join(lines)
|
|
|
|
|
|
@router.get("/logs/stream")
|
|
async def stream_export_logs(
|
|
request: Request,
|
|
since: Optional[int] = Query(
|
|
None,
|
|
description = "Return log entries with seq strictly greater than this cursor.",
|
|
),
|
|
current_subject: str = Depends(get_current_subject),
|
|
):
|
|
"""
|
|
Stream live stdout/stderr from the export worker subprocess as
|
|
Server-Sent Events.
|
|
|
|
Events:
|
|
- `log` : a single log line (data: {"stream","line","ts"})
|
|
- `heartbeat`: periodic keepalive when no new lines are available
|
|
- `complete` : once the worker is idle and no new lines arrived for
|
|
~1 second. Clients should close.
|
|
- `error` : unrecoverable server-side error
|
|
|
|
Each event's `id:` field is the log entry's monotonic seq number so the
|
|
browser can resume via `Last-Event-ID` on reconnect.
|
|
"""
|
|
backend = get_export_backend()
|
|
|
|
# Starting cursor: explicit `since` wins, then Last-Event-ID on reconnect,
|
|
# else the run-start snapshot so the client sees every line since the run
|
|
# began even if the SSE connection opened after the export-kickoff POST.
|
|
last_event_id = request.headers.get("last-event-id")
|
|
if since is None and last_event_id is not None:
|
|
try:
|
|
since = int(last_event_id)
|
|
except ValueError:
|
|
pass
|
|
|
|
if since is None:
|
|
cursor = backend.get_run_start_seq()
|
|
else:
|
|
cursor = max(0, int(since))
|
|
|
|
async def event_generator() -> AsyncGenerator[str, None]:
|
|
nonlocal cursor
|
|
# Reconnect after 3 seconds if the connection drops mid-export.
|
|
yield "retry: 3000\n\n"
|
|
|
|
last_yield = time.monotonic()
|
|
idle_since: Optional[float] = None
|
|
try:
|
|
while True:
|
|
if await request.is_disconnected():
|
|
return
|
|
|
|
entries, new_cursor = backend.get_logs_since(cursor)
|
|
if entries:
|
|
for entry in entries:
|
|
payload = json.dumps(
|
|
{
|
|
"stream": entry.get("stream", "stdout"),
|
|
"line": entry.get("line", ""),
|
|
"ts": entry.get("ts"),
|
|
}
|
|
)
|
|
yield _format_sse(
|
|
payload,
|
|
event = "log",
|
|
event_id = int(entry.get("seq", 0)),
|
|
)
|
|
cursor = new_cursor
|
|
last_yield = time.monotonic()
|
|
idle_since = None
|
|
else:
|
|
now = time.monotonic()
|
|
if now - last_yield > 10.0:
|
|
yield _format_sse("{}", event = "heartbeat")
|
|
last_yield = now
|
|
if not backend.is_export_active():
|
|
# Let the reader thread drain trailing lines printed just
|
|
# before the worker signalled done.
|
|
if idle_since is None:
|
|
idle_since = now
|
|
elif now - idle_since > 1.0:
|
|
yield _format_sse(
|
|
"{}",
|
|
event = "complete",
|
|
event_id = cursor,
|
|
)
|
|
return
|
|
else:
|
|
idle_since = None
|
|
|
|
await asyncio.sleep(0.1)
|
|
except asyncio.CancelledError:
|
|
# Client disconnected mid-yield: end cleanly so StreamingResponse finalizes.
|
|
return
|
|
except Exception as exc:
|
|
logger.error("Export log stream failed: %s", exc, exc_info = True)
|
|
try:
|
|
yield _format_sse(
|
|
json.dumps({"error": safe_error_detail(exc)}),
|
|
event = "error",
|
|
)
|
|
except Exception:
|
|
pass
|
|
|
|
return StreamingResponse(
|
|
event_generator(),
|
|
media_type = "text/event-stream",
|
|
headers = {
|
|
"Cache-Control": "no-cache",
|
|
"Connection": "keep-alive",
|
|
"X-Accel-Buffering": "no",
|
|
},
|
|
)
|