5f6b1d251f
Change-detectors, tautologies, source-reading tests, redundant duplicates, mock-echo tests and dead/unrunnable tests. Per-test rationale in the lane ledger (category + reason for every removal).
635 lines
26 KiB
Python
635 lines
26 KiB
Python
"""Tests for tools/image_generation_tool.py — FAL multi-model support.
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Covers the pure logic of the new wrapper: catalog integrity, the three size
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families (image_size_preset / aspect_ratio / gpt_literal), the supports
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whitelist, default merging, GPT quality override, and model resolution
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fallback. Does NOT exercise fal_client submission — that's covered by
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tests/tools/test_managed_media_gateways.py.
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"""
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from __future__ import annotations
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from unittest.mock import patch
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import pytest
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# ---------------------------------------------------------------------------
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# Fixtures
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# ---------------------------------------------------------------------------
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@pytest.fixture
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def image_tool():
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"""Fresh import of tools.image_generation_tool per test."""
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import importlib
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import tools.image_generation_tool as mod
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return importlib.reload(mod)
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# ---------------------------------------------------------------------------
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# Catalog integrity
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# ---------------------------------------------------------------------------
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@pytest.mark.parametrize("variant", ["flare", "sunburst"])
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@pytest.mark.parametrize("aspect,size", [
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("landscape", "landscape_4_3"), ("square", "square_hd"), ("portrait", "portrait_4_3"),
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])
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def test_image_25_selection_routes_generation_and_edits(image_tool, monkeypatch, variant, aspect, size):
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model = f"openai/gpt-image-2.5/{variant}/text-to-image"
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monkeypatch.setenv("FAL_IMAGE_MODEL", model)
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monkeypatch.setenv("FAL_KEY", "test-key")
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selected, meta = image_tool._resolve_fal_model()
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assert selected == model
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refs = [f"https://example.com/{i}.png" for i in range(17)]
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for sources, endpoint in (([], model), (refs, f"openai/gpt-image-2.5/{variant}/edit")):
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actual, payload = image_tool._prepare_fal_request(
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selected, meta, "a cup", aspect, 42, {"guidance_scale": 9}, sources,
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)
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assert actual == endpoint
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assert payload["quality"] == "medium"
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assert payload["image_size"] == size
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assert "seed" not in payload and "guidance_scale" not in payload
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assert payload.get("image_urls", []) == sources[:16]
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assert meta["upscale"] is False
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class TestFalCatalog:
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"""Every FAL_MODELS entry must have a consistent shape."""
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def test_all_entries_have_required_keys(self, image_tool):
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required = {
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"display", "speed", "strengths", "price",
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"size_style", "sizes", "defaults", "supports", "upscale",
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}
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for mid, meta in image_tool.FAL_MODELS.items():
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missing = required - set(meta.keys())
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assert not missing, f"{mid} missing required keys: {missing}"
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def test_edit_capable_entries_declare_a_full_edit_contract(self, image_tool):
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"""An `edit_endpoint` is useless without the whitelist and the
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reference-image cap that `_build_fal_edit_payload` reads."""
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for mid, meta in image_tool.FAL_MODELS.items():
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if "edit_endpoint" not in meta:
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continue
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assert meta.get("edit_supports"), f"{mid} has edit_endpoint but no edit_supports"
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# Most edit endpoints take an `image_urls` list; entries with a
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# singular image key (Kling Image v3) declare edit_image_param.
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image_param = meta.get("edit_image_param") or "image_urls"
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assert image_param in meta["edit_supports"], \
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f"{mid} edit_supports must allow {image_param}"
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cap = meta.get("max_reference_images")
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assert isinstance(cap, int) and cap > 0, \
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f"{mid} needs a positive max_reference_images"
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# ---------------------------------------------------------------------------
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# Payload building — three size families
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# ---------------------------------------------------------------------------
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class TestImageSizePresetFamily:
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"""Flux, z-image, qwen, recraft, ideogram all use preset enum sizes."""
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def test_klein_landscape_uses_preset(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/flux-2/klein/9b", "hello", "landscape")
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assert p["image_size"] == "landscape_16_9"
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assert "aspect_ratio" not in p
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class TestAspectRatioFamily:
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"""Nano-banana uses aspect_ratio enum, NOT image_size."""
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def test_nano_banana_landscape_uses_aspect_ratio(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/nano-banana-pro", "hello", "landscape")
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assert p["aspect_ratio"] == "16:9"
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assert "image_size" not in p
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class TestGptLiteralFamily:
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"""GPT-Image 1.5 uses literal size strings."""
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def test_gpt_landscape_is_literal(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/gpt-image-1.5", "hello", "landscape")
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assert p["image_size"] == "1536x1024"
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class TestGptImage2Presets:
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"""GPT Image 2 uses preset enum sizes (not literal strings like 1.5).
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Mapped to 4:3 variants so we stay above the 655,360 min-pixel floor
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(16:9 presets at 1024x576 = 589,824 would be rejected)."""
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def test_gpt2_landscape_uses_4_3_preset(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/gpt-image-2", "hello", "landscape")
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assert p["image_size"] == "landscape_4_3"
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def test_gpt2_strips_byok_and_unsupported_overrides(self, image_tool):
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"""openai_api_key (BYOK) is deliberately not in supports — all users
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route through shared FAL billing. guidance_scale/num_inference_steps
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aren't in the model's API surface either."""
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p = image_tool._build_fal_payload(
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"fal-ai/gpt-image-2", "hi", "square",
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overrides={
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"openai_api_key": "sk-...",
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"guidance_scale": 7.5,
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"num_inference_steps": 50,
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},
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)
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assert "openai_api_key" not in p
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assert "guidance_scale" not in p
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assert "num_inference_steps" not in p
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# ---------------------------------------------------------------------------
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# Supports whitelist — the main safety property
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# ---------------------------------------------------------------------------
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class TestSupportsFilter:
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"""No model should receive keys outside its `supports` set."""
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def test_payload_keys_are_subset_of_supports_for_all_models(self, image_tool):
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for mid, meta in image_tool.FAL_MODELS.items():
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payload = image_tool._build_fal_payload(mid, "test", "landscape", seed=42)
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unsupported = set(payload.keys()) - meta["supports"]
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assert not unsupported, \
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f"{mid} payload has unsupported keys: {unsupported}"
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# ---------------------------------------------------------------------------
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# Default merging
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# ---------------------------------------------------------------------------
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class TestDefaults:
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"""Model-level defaults should carry through unless overridden."""
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def test_none_override_does_not_replace_default(self, image_tool):
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"""None values from caller should be ignored (use default)."""
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p = image_tool._build_fal_payload(
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"fal-ai/flux-2-pro", "hi", "square",
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overrides={"num_inference_steps": None},
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)
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assert p["num_inference_steps"] == image_tool.FAL_MODELS["fal-ai/flux-2-pro"]["defaults"]["num_inference_steps"]
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# ---------------------------------------------------------------------------
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# GPT-Image quality is pinned to medium (not user-configurable)
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# ---------------------------------------------------------------------------
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# ---------------------------------------------------------------------------
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# Model resolution
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# ---------------------------------------------------------------------------
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class TestModelResolution:
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def test_no_config_falls_back_to_default(self, image_tool):
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with patch("hermes_cli.config.load_config", return_value={}):
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mid, meta = image_tool._resolve_fal_model()
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assert mid == image_tool.DEFAULT_MODEL
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def test_config_wins_over_env_var(self, image_tool, monkeypatch):
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monkeypatch.setenv("FAL_IMAGE_MODEL", "fal-ai/z-image/turbo")
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with patch("hermes_cli.config.load_config",
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return_value={"image_gen": {"model": "fal-ai/nano-banana-pro"}}):
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mid, _ = image_tool._resolve_fal_model()
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assert mid == "fal-ai/nano-banana-pro"
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# ---------------------------------------------------------------------------
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# Aspect ratio handling
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# ---------------------------------------------------------------------------
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class TestAspectRatioNormalization:
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def test_invalid_aspect_defaults_to_landscape(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/flux-2/klein/9b", "hi", "cinemascope")
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assert p["image_size"] == "landscape_16_9"
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# ---------------------------------------------------------------------------
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# Schema + registry integrity
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# ---------------------------------------------------------------------------
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# ---------------------------------------------------------------------------
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# Managed gateway 4xx translation
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# ---------------------------------------------------------------------------
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class _MockResponse:
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def __init__(self, status_code: int, payload=None):
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self.status_code = status_code
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self._payload = payload
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self.text = "" if payload is None else __import__("json").dumps(payload)
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def json(self):
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if self._payload is None:
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raise ValueError("not json")
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return self._payload
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class _MockHttpxError(Exception):
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"""Simulates httpx.HTTPStatusError which exposes .response.status_code."""
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def __init__(self, status_code: int, message: str = "Bad Request", payload=None):
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super().__init__(message)
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self.response = _MockResponse(status_code, payload)
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class TestExtractHttpStatus:
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"""Status-code extraction should work across exception shapes."""
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def test_extracts_from_response_attr(self, image_tool):
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exc = _MockHttpxError(403)
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assert image_tool._extract_http_status(exc) == 403
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def test_response_attr_without_status_code_returns_none(self, image_tool):
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class OddResponse:
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pass
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exc = Exception("weird")
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exc.response = OddResponse() # type: ignore[attr-defined]
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assert image_tool._extract_http_status(exc) is None
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class TestManagedGatewayErrorTranslation:
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"""4xx from the Nous managed gateway should be translated to a user-actionable message."""
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@pytest.fixture(autouse=True)
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def _fal_client_stub(self, image_tool, monkeypatch):
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# These tests drive a mocked managed client; the module-global loader
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# must not demand the optional fal extra (a version-pinned metadata
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# check under lazy installs) on the way there.
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monkeypatch.setattr(image_tool, "fal_client", object())
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def test_4xx_translates_to_value_error_with_remediation(self, image_tool, monkeypatch):
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"""403 from managed gateway → ValueError mentioning FAL_KEY + hermes tools."""
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from unittest.mock import MagicMock
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# Simulate: managed mode active, managed submit raises 4xx.
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managed_gateway = MagicMock()
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managed_gateway.gateway_origin = "https://fal-queue-gateway.example.com"
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managed_gateway.nous_user_token = "test-token"
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monkeypatch.setattr(image_tool, "_resolve_managed_fal_gateway",
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lambda: managed_gateway)
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bad_request = _MockHttpxError(403, "Forbidden")
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mock_managed_client = MagicMock()
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mock_managed_client.submit.side_effect = bad_request
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monkeypatch.setattr(image_tool, "_get_managed_fal_client",
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lambda gw: mock_managed_client)
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with pytest.raises(ValueError) as exc_info:
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image_tool._submit_fal_request("fal-ai/nano-banana-pro", {"prompt": "x"})
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msg = str(exc_info.value)
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assert "fal-ai/nano-banana-pro" in msg
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assert "403" in msg
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# Original exception chained for debugging
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assert exc_info.value.__cause__ is bad_request
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def test_billing_meter_error_is_preserved_instead_of_called_model_unavailable(
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self, image_tool, monkeypatch
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):
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"""Portal billing configuration is the root cause, not a missing model."""
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from unittest.mock import MagicMock
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managed_gateway = MagicMock()
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managed_gateway.gateway_origin = "https://fal-queue-gateway.example.com"
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managed_gateway.nous_user_token = "test-token"
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monkeypatch.setattr(
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image_tool, "_resolve_managed_fal_gateway", lambda: managed_gateway
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)
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payload = {
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"error": {
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"code": "BILLING_ERROR",
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"message": "Charge authorization failed",
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"details": {
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"upstreamPayload": {
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"code": "unsupported_pricing_meter",
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"error": "Unsupported resolver usage meter",
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}
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},
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}
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}
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billing_error = _MockHttpxError(409, payload=payload)
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mock_managed_client = MagicMock()
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mock_managed_client.submit.side_effect = billing_error
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monkeypatch.setattr(
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image_tool, "_get_managed_fal_client", lambda gw: mock_managed_client
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)
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with pytest.raises(ValueError) as exc_info:
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image_tool._submit_fal_request(
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"openai/gpt-image-2.5/flare/text-to-image", {"prompt": "x"}
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)
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msg = str(exc_info.value)
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assert "Charge authorization failed" in msg
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assert "BILLING_ERROR" in msg
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assert "unsupported_pricing_meter" in msg
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assert "may not yet be enabled" not in msg
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def test_non_http_exception_from_managed_bubbles_up(self, image_tool, monkeypatch):
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"""Connection errors, timeouts, etc. from managed mode aren't 4xx —
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they should bubble up unchanged so callers can retry or diagnose."""
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from unittest.mock import MagicMock
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managed_gateway = MagicMock()
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monkeypatch.setattr(image_tool, "_resolve_managed_fal_gateway",
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lambda: managed_gateway)
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conn_error = ConnectionError("network down")
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mock_managed_client = MagicMock()
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mock_managed_client.submit.side_effect = conn_error
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monkeypatch.setattr(image_tool, "_get_managed_fal_client",
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lambda gw: mock_managed_client)
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with pytest.raises(ConnectionError):
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image_tool._submit_fal_request("fal-ai/flux-2-pro", {"prompt": "x"})
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@staticmethod
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def _rate_limited(retry_after):
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return _MockHttpxError(429, "Too Many Requests", payload={"error": {
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"code": "RATE_LIMIT_EXCEEDED", "message": "Rate limit exceeded.", "retryAfter": retry_after}})
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def test_short_429_is_retried_once_under_a_fresh_idempotency_key(self, image_tool, monkeypatch):
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"""A gateway 429 with a short retryAfter is waited out and resubmitted once (new key)."""
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from unittest.mock import MagicMock
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monkeypatch.setattr(image_tool, "_resolve_managed_fal_gateway", lambda: MagicMock())
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mock_managed_client = MagicMock()
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mock_managed_client.submit.side_effect = [self._rate_limited(0), "handle"]
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monkeypatch.setattr(image_tool, "_get_managed_fal_client", lambda gw: mock_managed_client)
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assert image_tool._submit_fal_request("fal-ai/gpt-image-2", {"prompt": "x"}) == "handle"
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keys = [call.kwargs["headers"]["x-idempotency-key"] for call in mock_managed_client.submit.call_args_list]
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assert len(keys) == 2 and keys[0] != keys[1]
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def test_long_429_is_reported_as_a_rate_limit_not_a_missing_model(self, image_tool, monkeypatch):
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"""A 429 beyond the retry cap names the rate limit; agents must not be told to switch models."""
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from unittest.mock import MagicMock
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monkeypatch.setattr(image_tool, "_resolve_managed_fal_gateway", lambda: MagicMock())
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mock_managed_client = MagicMock()
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mock_managed_client.submit.side_effect = self._rate_limited(120)
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monkeypatch.setattr(image_tool, "_get_managed_fal_client", lambda gw: mock_managed_client)
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with pytest.raises(ValueError) as exc_info:
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image_tool._submit_fal_request("fal-ai/gpt-image-2", {"prompt": "x"})
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msg = str(exc_info.value)
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assert "120" in msg
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assert "may not yet be enabled" not in msg
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assert mock_managed_client.submit.call_count == 1
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class TestKreaModelNormalization:
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"""Native ``krea-2-*`` detection for managed Krea routing."""
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def test_native_models_detected(self, image_tool):
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for mid in ("krea-2-medium", "krea-2-large", "krea-2-medium-turbo"):
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assert image_tool._normalize_krea_model(mid) == mid
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def test_non_krea_models_are_not_krea(self, image_tool):
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for mid in ("fal-ai/flux-2/klein/9b", "fal-ai/nano-banana-pro", None, "", 123):
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assert image_tool._normalize_krea_model(mid) is None
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class TestManagedKreaRouting:
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"""`_maybe_route_managed_model` only fires for Krea / Portal models in managed mode."""
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def test_no_route_when_model_not_krea(self, image_tool, monkeypatch):
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monkeypatch.setattr(image_tool, "_read_configured_image_provider", lambda: None)
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monkeypatch.setattr(
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image_tool, "_read_configured_image_model", lambda: "fal-ai/flux-2/klein/9b"
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)
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assert image_tool._maybe_route_managed_model("p", "square") is None
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def test_routes_native_krea_model_to_krea_plugin_in_managed_mode(
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self, image_tool, monkeypatch
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):
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from types import SimpleNamespace
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from unittest.mock import MagicMock
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import json as _json
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monkeypatch.setattr(image_tool, "_read_configured_image_provider", lambda: None)
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monkeypatch.setattr(
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image_tool,
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"_read_configured_image_model",
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lambda: "krea-2-large",
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)
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import plugins.image_gen.krea as krea_mod
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monkeypatch.setattr(
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krea_mod,
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"_resolve_managed_krea_gateway",
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lambda: SimpleNamespace(
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vendor="krea",
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gateway_origin="https://krea-gateway.example.com",
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nous_user_token="tok",
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managed_mode=True,
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),
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)
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fake_provider = MagicMock()
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fake_provider.generate.return_value = {"success": True, "image": "/tmp/x.png"}
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monkeypatch.setattr(
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"agent.image_gen_registry.get_provider", lambda name: fake_provider
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)
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monkeypatch.setattr(
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"hermes_cli.plugins._ensure_plugins_discovered", lambda *a, **k: None
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)
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out = image_tool._maybe_route_managed_model("a cat", "portrait")
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assert out is not None
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assert _json.loads(out)["success"] is True
|
|
kwargs = fake_provider.generate.call_args.kwargs
|
|
assert kwargs["model"] == "krea-2-large"
|
|
assert kwargs["prompt"] == "a cat"
|
|
assert kwargs["aspect_ratio"] == "portrait"
|
|
|
|
|
|
class TestManagedPortalRouting:
|
|
"""A Portal model under the managed selection reaches the Portal plugin — never FAL."""
|
|
|
|
def _fake_registry(self, monkeypatch, fake_provider):
|
|
monkeypatch.setattr("agent.image_gen_registry.get_provider", lambda name: fake_provider)
|
|
monkeypatch.setattr("hermes_cli.plugins._ensure_plugins_discovered", lambda *a, **k: None)
|
|
|
|
def test_routes_portal_model_to_nous_plugin(self, image_tool, monkeypatch):
|
|
import json as _json
|
|
from unittest.mock import MagicMock
|
|
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_provider", lambda: "nous")
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_model", lambda: "openai/gpt-5.4-image-2")
|
|
fake_provider = MagicMock(display_name="Nous Portal")
|
|
fake_provider.generate.return_value = {"success": True, "image": "/tmp/x.png"}
|
|
self._fake_registry(monkeypatch, fake_provider)
|
|
|
|
out = image_tool._maybe_route_managed_model("a cat", "square")
|
|
|
|
assert _json.loads(out)["success"] is True
|
|
assert fake_provider.generate.call_args.kwargs["model"] == "openai/gpt-5.4-image-2"
|
|
|
|
def test_portal_model_without_plugin_errors_instead_of_billing_fal(self, image_tool, monkeypatch):
|
|
import json as _json
|
|
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_provider", lambda: "nous")
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_model", lambda: "openai/gpt-5.4-image-2")
|
|
self._fake_registry(monkeypatch, None)
|
|
|
|
out = image_tool._maybe_route_managed_model("a cat", "square")
|
|
|
|
assert out is not None and _json.loads(out)["success"] is False
|
|
|
|
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Opt-in upscale pass
|
|
# ---------------------------------------------------------------------------
|
|
|
|
class _FakeHandle:
|
|
def __init__(self, result):
|
|
self._result = result
|
|
|
|
def get(self):
|
|
return self._result
|
|
|
|
|
|
class TestUpscaleOptIn:
|
|
"""Explicit ``upscale`` overrides the per-model catalog default."""
|
|
|
|
def _run(self, image_tool, monkeypatch, *, model, upscale, upscaler_called):
|
|
monkeypatch.setenv("FAL_IMAGE_MODEL", model)
|
|
monkeypatch.setattr(image_tool, "fal_key_is_configured", lambda: True)
|
|
monkeypatch.setattr(image_tool, "_resolve_managed_fal_gateway", lambda: None)
|
|
monkeypatch.setattr(
|
|
image_tool, "_submit_fal_request",
|
|
lambda endpoint, arguments=None: _FakeHandle(
|
|
{"images": [{"url": "https://fal/native.png", "width": 1024, "height": 768}]}
|
|
),
|
|
)
|
|
calls = []
|
|
|
|
def _fake_upscale(url, prompt):
|
|
calls.append(url)
|
|
return {
|
|
"url": "https://fal/upscaled.png", "width": 2048, "height": 1536,
|
|
"upscaled": True, "upscale_factor": 2,
|
|
}
|
|
|
|
monkeypatch.setattr(image_tool, "_upscale_image", _fake_upscale)
|
|
|
|
import json as _json
|
|
out = _json.loads(image_tool.image_generate_tool("a cat", upscale=upscale))
|
|
assert out["success"] is True
|
|
assert bool(calls) is upscaler_called
|
|
assert out["upscaled"] is upscaler_called
|
|
expected_url = "https://fal/upscaled.png" if upscaler_called else "https://fal/native.png"
|
|
assert out["image"] == expected_url
|
|
|
|
def test_explicit_true_upscales_native_hi_res_model(self, image_tool, monkeypatch):
|
|
"""Seedream Lite has upscale=False in the catalog (native 4K) —
|
|
explicit True still wins."""
|
|
self._run(image_tool, monkeypatch,
|
|
model="bytedance/seedream/v5/lite/text-to-image",
|
|
upscale=True, upscaler_called=True)
|
|
|
|
def test_explicit_false_stays_off(self, image_tool, monkeypatch):
|
|
"""Explicit False and the catalog default agree: no upscale."""
|
|
self._run(image_tool, monkeypatch,
|
|
model="fal-ai/flux-2/klein/9b", upscale=False, upscaler_called=False)
|
|
|
|
def test_omitted_keeps_catalog_default_off(self, image_tool, monkeypatch):
|
|
self._run(image_tool, monkeypatch,
|
|
model="bytedance/seedream/v5/lite/text-to-image",
|
|
upscale=None, upscaler_called=False)
|
|
|
|
|
|
def test_upscale_failure_falls_back_to_native(self, image_tool, monkeypatch):
|
|
monkeypatch.setenv("FAL_IMAGE_MODEL", "fal-ai/flux-2/klein/9b")
|
|
monkeypatch.setattr(image_tool, "fal_key_is_configured", lambda: True)
|
|
monkeypatch.setattr(image_tool, "_resolve_managed_fal_gateway", lambda: None)
|
|
monkeypatch.setattr(
|
|
image_tool, "_submit_fal_request",
|
|
lambda endpoint, arguments=None: _FakeHandle(
|
|
{"images": [{"url": "https://fal/native.png"}]}
|
|
),
|
|
)
|
|
monkeypatch.setattr(image_tool, "_upscale_image", lambda url, prompt: None)
|
|
|
|
import json as _json
|
|
out = _json.loads(image_tool.image_generate_tool("a cat", upscale=True))
|
|
assert out["success"] is True
|
|
assert out["image"] == "https://fal/native.png"
|
|
assert out["upscaled"] is False
|
|
|
|
|
|
class TestUpscaleDispatchForwarding:
|
|
"""The tool handler forwards explicit upscale to plugin providers."""
|
|
|
|
def test_dispatch_forwards_upscale(self, image_tool, monkeypatch):
|
|
from unittest.mock import MagicMock
|
|
import json as _json
|
|
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_provider", lambda: "krea")
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_model", lambda: None)
|
|
fake_provider = MagicMock()
|
|
fake_provider.generate.return_value = {"success": True, "image": "/tmp/x.png"}
|
|
monkeypatch.setattr(
|
|
"agent.image_gen_registry.get_provider", lambda name: fake_provider
|
|
)
|
|
monkeypatch.setattr(
|
|
"hermes_cli.plugins._ensure_plugins_discovered", lambda *a, **k: None
|
|
)
|
|
|
|
out = image_tool._dispatch_to_plugin_provider("a cat", "square", upscale=True)
|
|
assert _json.loads(out)["success"] is True
|
|
assert fake_provider.generate.call_args.kwargs["upscale"] is True
|
|
|
|
def test_dispatch_omits_upscale_when_unset(self, image_tool, monkeypatch):
|
|
from unittest.mock import MagicMock
|
|
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_provider", lambda: "krea")
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_model", lambda: None)
|
|
fake_provider = MagicMock()
|
|
fake_provider.generate.return_value = {"success": True, "image": "/tmp/x.png"}
|
|
monkeypatch.setattr(
|
|
"agent.image_gen_registry.get_provider", lambda name: fake_provider
|
|
)
|
|
monkeypatch.setattr(
|
|
"hermes_cli.plugins._ensure_plugins_discovered", lambda *a, **k: None
|
|
)
|
|
|
|
image_tool._dispatch_to_plugin_provider("a cat", "square")
|
|
assert "upscale" not in fake_provider.generate.call_args.kwargs
|