unsloth/studio/backend/tests/test_diffusion_routes.py
Daniel Han-Chen f06895b73e Fix/adjust diffusion: round 5 lifecycle + validation hardening for PR #5754
Round 5 reviewer findings, mostly symmetric-lifecycle and input
validation gaps the earlier rounds left open.

Backend lifecycle (P1)
  * routes/training.py: training start now also unloads the GGUF
    llama-server subprocess; was previously only unloading the
    safetensors backend, so starting training while a GGUF chat
    model was loaded kept the subprocess pinned to VRAM.
  * routes/inference.py: new _raise_if_training_active helper. Both
    GGUF and standard chat loads, plus /api/inference/images/load,
    now refuse with HTTP 409 when training is active instead of
    silently stopping training to free VRAM.
  * core/inference/diffusion.py: _release_other_gpu_owners_for_
    diffusion no longer stops active training. The route layer
    refuses the request first, so reaching the helper with training
    live would only happen from programmatic backend calls; better
    to surface OOM than terminate a long training run.
  * core/inference/diffusion.py: BF16 dtype is now gated on
    torch.cuda.is_bf16_supported. Pascal/Turing GPUs report
    is_available()=True but lack BF16 ALUs; FLUX kernels then fail
    inside from_pretrained. Falls back to FP16 instead of refusing.
  * core/inference/diffusion.py: GGUF transformer allocation and
    pipeline allocation now run AFTER releasing chat/export GPU
    owners; previously from_single_file ran first and could OOM
    before the intended VRAM handoff happened.
  * routes/models.py: /delete-cached now also blocks delete when
    diffusion is_loading=True (not just is_loaded); concurrent
    delete during hf_hub_download / from_single_file would have
    raced the rmtree.
  * routes/models.py: /delete-finetuned now also checks the
    diffusion backend before unlinking a Studio outputs/exports
    path. A user who exported a FLUX LoRA locally and loaded it via
    /images/load could previously rmtree the directory the
    diffusion backend was reading from.

Backend correctness / safety (P2)
  * core/inference/diffusion.py: _FAMILY_EXCLUDE for qwen-image now
    also covers qwen_image_edit / qwenimageedit underscore spellings
    so '...qwen_image_edit-GGUF' no longer misdetects as Qwen-Image.
  * core/inference/diffusion.py: detect_family now scans
    _FULL_REPO_FAMILIES in addition to _FAMILIES, so SDXL repos
    (stabilityai/stable-diffusion-xl-base-1.0) are auto-detected
    instead of failing with 'Could not infer a diffusion family'.
  * core/inference/diffusion.py: generate_image now uses a separate
    _generate_lock for the pipeline forward instead of holding
    _lock for the whole call. status() polls and concurrent unload
    requests no longer block for the full minutes-long generation.
  * routes/models.py: diffusion delete guard now uses exact repo-id
    match instead of prefix match; previously loading 'org/model-v2'
    would block deleting unrelated cached 'org/model'.
  * models/inference.py: DiffusionLoadRequest now rejects ASCII
    control characters in repo_id / gguf_filename / base_repo /
    family via field_validator (closes log-injection surface from
    authenticated callers). Also caps lengths at 256 chars.
  * models/inference.py: DiffusionGenerateRequest seed is now
    bounded to the int64/uint64 range; previously a huge seed
    (e.g. 2**100) passed Pydantic then crashed inside
    torch.Generator.manual_seed with 'Overflow when unpacking long
    long'.

Frontend (P2)
  * features/images/images-page.tsx: Custom HF repo panel now
    exposes a Pipeline family override dropdown; previously the
    backend supported it via DiffusionLoadRequest.family but the UI
    had no way to send it, so custom repos whose names did not
    contain a hard-coded substring failed to load.
  * features/images/images-page.tsx: handleLoad now re-fetches
    status on error. The backend clears its old pipeline before
    allocating the replacement; a failed swap previously left the
    UI showing 'Loaded:' with Generate enabled until manual
    refresh.

Tests (10 new)
  * underscore qwen-image-edit exclusion + SDXL full-repo detection
  * BF16 fallback when is_bf16_supported() returns False
  * status() does not block while generate_image holds _generate_lock
  * route layer rejects control chars in repo_id
  * route layer rejects 2**100 seeds (uint64-max boundary accepted)
  * route layer happy-path with negative-prompt true_cfg_scale
    forwarding (Qwen/Flux) and skip-when-no-neg (distilled CFG)
2026-05-25 01:05:27 +00:00

241 lines
7.4 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
"""Route-level tests for ``/api/inference/images/*``.
Mounts the actual ``inference_router`` on a fresh FastAPI app with the
auth dependency replaced by a stub so we exercise the same FastAPI
handlers Studio ships in production. The diffusion backend is replaced
with an in-memory stub so we don't need diffusers / GPUs to run these.
"""
from __future__ import annotations
import sys
from pathlib import Path
import pytest
from fastapi import FastAPI
from fastapi.testclient import TestClient
from PIL import Image
_BACKEND_ROOT = Path(__file__).resolve().parents[1]
if str(_BACKEND_ROOT) not in sys.path:
sys.path.insert(0, str(_BACKEND_ROOT))
class _FakeBackend:
def __init__(self) -> None:
self._loaded = False
self._repo: str | None = None
self.calls: list[dict] = []
@property
def is_loaded(self) -> bool:
return self._loaded
def status(self) -> dict:
return {
"is_loaded": self._loaded,
"is_loading": False,
"repo_id": self._repo,
"family": "flux.2-klein" if self._loaded else None,
"pipeline_class": "Flux2KleinPipeline" if self._loaded else None,
"base_repo": "black-forest-labs/FLUX.2-klein" if self._loaded else None,
"gguf_filename": None,
"device": "cpu",
"dtype": "torch.bfloat16",
"loaded_at": 0,
"last_error": None,
"supported_families": [],
}
def load_model(self, repo_id, **kw):
self.calls.append({"op": "load", "repo_id": repo_id, **kw})
self._loaded = True
self._repo = repo_id
return self.status()
def unload_model(self) -> dict:
self._loaded = False
self._repo = None
return {"is_loaded": False}
def generate_image(self, **kw):
self.calls.append({"op": "generate", **kw})
return Image.new("RGB", (kw["width"], kw["height"]), color = (123, 45, 67))
@pytest.fixture
def app_with_stub(monkeypatch):
"""Build a FastAPI app that mounts the real inference router with
auth disabled and the diffusion backend swapped for a stub."""
from routes import inference as inf
import core.inference.diffusion as d
stub = _FakeBackend()
# Override the singleton accessor the route uses.
monkeypatch.setattr(d, "get_diffusion_backend", lambda: stub)
monkeypatch.setattr(inf, "_get_diffusion_backend", lambda: stub)
app = FastAPI()
app.include_router(inf.router, prefix = "/api/inference")
# Bypass auth by overriding the dependency.
from auth.authentication import get_current_subject
app.dependency_overrides[get_current_subject] = lambda: "test-user"
return app, stub
def test_status_when_unloaded(app_with_stub):
app, _ = app_with_stub
c = TestClient(app)
r = c.get("/api/inference/images/status")
assert r.status_code == 200
body = r.json()
assert body["is_loaded"] is False
assert body["repo_id"] is None
def test_generate_without_load_returns_400(app_with_stub):
app, _ = app_with_stub
c = TestClient(app)
r = c.post(
"/api/inference/images/generate",
json = {"prompt": "a red sphere"},
)
assert r.status_code == 400
assert "No diffusion model" in r.json()["detail"]
def test_load_then_generate_round_trip(app_with_stub):
app, stub = app_with_stub
c = TestClient(app)
r = c.post(
"/api/inference/images/load",
json = {
"repo_id": "unsloth/FLUX.2-klein-4B-GGUF",
"gguf_filename": "flux-2-klein-4b-Q4_K_S.gguf",
},
)
assert r.status_code == 200, r.text
assert r.json()["is_loaded"] is True
r = c.post(
"/api/inference/images/generate",
json = {
"prompt": "a tiny synth-pop album cover",
"width": 256,
"height": 256,
"num_inference_steps": 4,
"seed": 7,
},
)
assert r.status_code == 200, r.text
body = r.json()
assert body["image_b64"]
assert body["image_mime"] == "image/png"
assert body["width"] == 256
assert body["height"] == 256
assert body["seed"] == 7
assert body["duration_ms"] >= 0
# Round-trip the base64 -> PIL to confirm it is a real PNG of the
# right size and not, say, an empty string.
import base64
import io
raw = base64.b64decode(body["image_b64"])
decoded = Image.open(io.BytesIO(raw))
assert decoded.format == "PNG"
assert decoded.size == (256, 256)
# Backend stub should have recorded both calls.
ops = [c["op"] for c in stub.calls]
assert ops == ["load", "generate"]
def test_generate_rejects_off_grid_size(app_with_stub):
app, stub = app_with_stub
c = TestClient(app)
c.post(
"/api/inference/images/load",
json = {
"repo_id": "unsloth/FLUX.2-klein-4B-GGUF",
"gguf_filename": "x.gguf",
},
)
r = c.post(
"/api/inference/images/generate",
json = {"prompt": "x", "width": 513, "height": 512},
)
# Pydantic v2 wraps validator errors in 422 by default.
assert r.status_code in (400, 422), r.text
def test_unload_clears_state(app_with_stub):
app, _ = app_with_stub
c = TestClient(app)
c.post(
"/api/inference/images/load",
json = {"repo_id": "unsloth/FLUX.2-klein-4B-GGUF", "gguf_filename": "x.gguf"},
)
r = c.post("/api/inference/images/unload")
assert r.status_code == 200
assert r.json()["is_loaded"] is False
r = c.get("/api/inference/images/status")
assert r.json()["is_loaded"] is False
def test_load_rejects_control_chars_in_repo_id(app_with_stub):
"""Newline-laden repo ids must be rejected by Pydantic BEFORE the
log line that echoes them. Catches log-injection from authenticated
callers (issues a 422 instead of forging a fake log line)."""
app, _ = app_with_stub
c = TestClient(app)
r = c.post(
"/api/inference/images/load",
json = {"repo_id": "owner/model\nFAKE_LOG_LINE"},
)
assert r.status_code == 422, r.text
body = r.json()
text = repr(body).lower()
assert "control" in text or "repo_id" in text
def test_generate_rejects_oversize_seed(app_with_stub):
"""Huge seeds raise inside torch.Generator.manual_seed; Pydantic
must clamp first with a 422 instead of a 500 traceback."""
app, _ = app_with_stub
c = TestClient(app)
c.post(
"/api/inference/images/load",
json = {"repo_id": "unsloth/FLUX.2-klein-4B-GGUF", "gguf_filename": "x.gguf"},
)
r = c.post(
"/api/inference/images/generate",
json = {"prompt": "x", "seed": 2 ** 100},
)
assert r.status_code == 422, r.text
def test_generate_accepts_uint64_max_seed(app_with_stub):
"""Boundary value: 2**64 - 1 (uint64 max) is the largest seed
torch.Generator on CPU accepts; reject would frustrate users
who paste large seeds from other tooling."""
app, _ = app_with_stub
c = TestClient(app)
c.post(
"/api/inference/images/load",
json = {"repo_id": "unsloth/FLUX.2-klein-4B-GGUF", "gguf_filename": "x.gguf"},
)
r = c.post(
"/api/inference/images/generate",
json = {"prompt": "x", "seed": (2 ** 64) - 1},
)
# The fake backend returns 200 on success; we only care that the
# request did NOT 422 on seed bounds.
assert r.status_code != 422, r.text