82199439c7
meta/muse-image/text-to-image + paired meta/muse-image/edit, the FAL listing of Meta's Muse Image model (launched on the Meta Model API in Aug 2026 at $0.01/image). - aspect_ratio size family (16:9 / 1:1 / 9:16 from the vendor's 21:9..9:21 enum); always sent on t2i for deterministic framing, deliberately omitted on edits so Muse follows the input image. - No seed in the vendor schema (Grok Imagine 2.0 precedent) - the supports whitelist filters it. - Edit takes 1-10 reference image_urls (max_reference_images=10). Schema verified against FAL's OpenAPI for both endpoints. Live E2E blocked by the FAL account balance lock (403), same as prior catalog additions.
756 lines
31 KiB
Python
756 lines
31 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_default_model_is_klein(self, image_tool):
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assert image_tool.DEFAULT_MODEL == "fal-ai/flux-2/klein/9b"
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def test_nano_banana_2_in_catalog(self, image_tool):
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meta = image_tool.FAL_MODELS["fal-ai/nano-banana-2"]
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# Invariants (not value snapshots): NB2 is an aspect-ratio family
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# with an edit endpoint whose ref cap matches FAL's published limit.
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assert meta["size_style"] == "aspect_ratio"
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assert meta["edit_endpoint"].startswith("fal-ai/nano-banana-2")
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assert meta["max_reference_images"] >= 1
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assert meta["edit_supports"] >= {"prompt", "image_urls"}
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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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assert "image_urls" in meta["edit_supports"], \
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f"{mid} edit_supports must allow image_urls"
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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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class TestAugust2026Catalog:
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"""The Aug 2026 FAL catalog expansion, surfaced in the model picker."""
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NEW_MODELS = (
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"bytedance/seedream/v5/pro/text-to-image",
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"bytedance/seedream/v5/lite/text-to-image",
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"ideogram/v4/instant",
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"ideogram/v4/fast",
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"alibaba/qwen-image-3/text-to-image",
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"microsoft/mai-image-2.5-pro",
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"google/nano-banana-2-lite",
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"fal-ai/recraft/v4.1/text-to-image",
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"fal-ai/nano-banana-2",
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)
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def test_new_models_are_in_the_catalog(self, image_tool):
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missing = [m for m in self.NEW_MODELS if m not in image_tool.FAL_MODELS]
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assert not missing, f"missing from FAL_MODELS: {missing}"
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def test_paired_edit_endpoints_are_wired(self, image_tool):
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expected = {
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"bytedance/seedream/v5/pro/text-to-image": "bytedance/seedream/v5/pro/edit",
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"alibaba/qwen-image-3/text-to-image": "alibaba/qwen-image-3/edit",
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"google/nano-banana-2-lite": "google/nano-banana-2-lite/edit",
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"fal-ai/nano-banana-2": "fal-ai/nano-banana-2/edit",
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}
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for model_id, edit_endpoint in expected.items():
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assert image_tool.FAL_MODELS[model_id]["edit_endpoint"] == edit_endpoint
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def test_text_only_models_declare_no_edit_endpoint(self, image_tool):
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"""These have no `/edit` app on FAL; claiming one would 404 mid-request."""
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for model_id in (
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"bytedance/seedream/v5/lite/text-to-image",
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"ideogram/v4/instant",
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"ideogram/v4/fast",
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"microsoft/mai-image-2.5-pro",
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"fal-ai/recraft/v4.1/text-to-image",
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):
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assert "edit_endpoint" not in image_tool.FAL_MODELS[model_id]
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def test_recraft_v41_omits_keys_its_schema_lacks(self, image_tool):
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"""Recraft V4.1 exposes no num_images/output_format/seed — the
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`supports` whitelist has to drop them rather than pass them upstream."""
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p = image_tool._build_fal_payload(
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"fal-ai/recraft/v4.1/text-to-image", "hello", "landscape"
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)
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assert p["image_size"] == "landscape_16_9"
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for absent in ("num_images", "output_format", "seed"):
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assert absent not in p
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def test_nano_banana_2_pins_the_1k_billing_tier(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/nano-banana-2", "hello", "landscape")
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assert p["resolution"] == "1K"
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assert p["aspect_ratio"] == "16:9"
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assert "image_size" not in p
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def test_nano_banana_2_lite_has_no_resolution_knob(self, image_tool):
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"""The lite tier renders at a fixed 1K and declares no `resolution`."""
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meta = image_tool.FAL_MODELS["google/nano-banana-2-lite"]
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assert "resolution" not in meta["supports"]
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assert "resolution" not in meta["defaults"]
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p = image_tool._build_fal_payload("google/nano-banana-2-lite", "hello", "square")
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assert "resolution" not in p
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assert p["aspect_ratio"] == "1:1"
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def test_seedream_lite_uses_documented_size_presets(self, image_tool):
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"""Lite accepts FAL's preset enum; custom ImageSize dicts are unnecessary."""
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p = image_tool._build_fal_payload(
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"bytedance/seedream/v5/lite/text-to-image", "hello", "landscape"
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)
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assert p["image_size"] == "landscape_16_9"
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class TestMetaMuseImage:
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"""Meta Muse Image (meta/muse-image/*) — Aug 2026 addition."""
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MODEL = "meta/muse-image/text-to-image"
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def test_in_catalog_with_edit_pair(self, image_tool):
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meta = image_tool.FAL_MODELS[self.MODEL]
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assert meta["size_style"] == "aspect_ratio"
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assert meta["edit_endpoint"] == "meta/muse-image/edit"
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# FAL schema: edit takes 1-10 reference image_urls.
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assert meta["max_reference_images"] == 10
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def test_text_payload_matches_vendor_schema(self, image_tool):
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"""Muse's schema exposes only prompt/aspect_ratio/num_images/
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output_format/sync_mode — no seed, no resolution/quality knobs."""
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p = image_tool._build_fal_payload(self.MODEL, "hello", "landscape", seed=42)
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assert p["aspect_ratio"] == "16:9"
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assert p["num_images"] == 1
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assert p["output_format"] == "png"
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for absent in ("seed", "image_size", "resolution", "quality"):
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assert absent not in p
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def test_edit_payload_omits_aspect_ratio(self, image_tool):
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"""On edits Muse follows the input image's framing; we deliberately
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keep aspect_ratio off the edit whitelist."""
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p = image_tool._build_fal_edit_payload(
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self.MODEL, "swap the sky", ["https://x/a.png"], "portrait"
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)
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assert p["image_urls"] == ["https://x/a.png"]
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assert "aspect_ratio" not in p
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assert "seed" not in p
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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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def test_klein_portrait_uses_preset(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/flux-2/klein/9b", "hello", "portrait")
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assert p["image_size"] == "portrait_16_9"
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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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def test_nano_banana_portrait_uses_aspect_ratio(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/nano-banana-pro", "hello", "portrait")
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assert p["aspect_ratio"] == "9:16"
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def test_nano_banana_2_uses_aspect_ratio_and_flash_defaults(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/nano-banana-2", "hello", "landscape")
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assert p["aspect_ratio"] == "16:9"
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assert p["resolution"] == "1K"
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assert p["limit_generations"] is True
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assert "image_size" not in p
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def test_nano_banana_2_allows_thinking_level(self, image_tool):
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p = image_tool._build_fal_payload(
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"fal-ai/nano-banana-2",
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"hello",
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"square",
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overrides={"thinking_level": "minimal"},
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)
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assert p["thinking_level"] == "minimal"
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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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def test_gpt_portrait_is_literal(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/gpt-image-1.5", "hello", "portrait")
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assert p["image_size"] == "1024x1536"
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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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def test_gpt2_strips_seed_even_if_passed(self, image_tool):
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# seed isn't in the GPT Image 2 API surface either.
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p = image_tool._build_fal_payload("fal-ai/gpt-image-2", "hi", "square", seed=42)
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assert "seed" 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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def test_nano_banana_never_gets_image_size(self, image_tool):
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# Common bug: translator accidentally setting both image_size and aspect_ratio.
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p = image_tool._build_fal_payload("fal-ai/nano-banana-pro", "hi", "landscape", seed=1)
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assert "image_size" not in p
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assert p["aspect_ratio"] == "16:9"
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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_klein_default_steps_is_4(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/flux-2/klein/9b", "hi", "square")
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assert p["num_inference_steps"] == 4
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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"] == 50
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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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class TestGptQualityPinnedToMedium:
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"""GPT-Image quality is baked into the FAL_MODELS defaults at 'medium'
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and cannot be overridden via config. Pinning keeps Nous Portal billing
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predictable across all users."""
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def test_gpt_payload_always_has_medium_quality(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/gpt-image-1.5", "hi", "square")
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assert p["quality"] == "medium"
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def test_resolve_gpt_quality_function_is_gone(self, image_tool):
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"""The _resolve_gpt_quality() helper was removed — quality is now
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a static default, not a runtime lookup."""
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assert not hasattr(image_tool, "_resolve_gpt_quality"), (
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"_resolve_gpt_quality should not exist — quality is pinned"
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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 == "fal-ai/flux-2/klein/9b"
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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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def test_empty_aspect_defaults_to_landscape(self, image_tool):
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p = image_tool._build_fal_payload("fal-ai/flux-2/klein/9b", "hi", "")
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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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class TestRegistryIntegration:
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def test_schema_exposes_expected_agent_params(self, image_tool):
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"""The static registration schema stays minimal — prompt (required)
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+ aspect_ratio. Capability args (image_url, reference_image_urls,
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upscale) are added per-model by the dynamic override so sessions
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whose active model can't honor them never see them (#95681 diet).
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Model selection stays a user-level config choice, never an
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agent-level arg."""
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props = image_tool.IMAGE_GENERATE_SCHEMA["parameters"]["properties"]
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assert set(props.keys()) == {"prompt", "aspect_ratio"}
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assert image_tool.IMAGE_GENERATE_SCHEMA["parameters"]["required"] == ["prompt"]
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# The dynamic builder owns the capability args.
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dyn = image_tool._build_dynamic_image_schema()
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assert "parameters" in dyn and "prompt" in dyn["parameters"]["properties"]
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def test_aspect_ratio_enum_is_three_values(self, image_tool):
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enum = image_tool.IMAGE_GENERATE_SCHEMA["parameters"]["properties"]["aspect_ratio"]["enum"]
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assert set(enum) == {"landscape", "square", "portrait"}
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Managed gateway 4xx translation
|
|
# ---------------------------------------------------------------------------
|
|
|
|
class _MockResponse:
|
|
def __init__(self, status_code: int, payload=None):
|
|
self.status_code = status_code
|
|
self._payload = payload
|
|
self.text = "" if payload is None else __import__("json").dumps(payload)
|
|
|
|
def json(self):
|
|
if self._payload is None:
|
|
raise ValueError("not json")
|
|
return self._payload
|
|
|
|
|
|
class _MockHttpxError(Exception):
|
|
"""Simulates httpx.HTTPStatusError which exposes .response.status_code."""
|
|
def __init__(self, status_code: int, message: str = "Bad Request", payload=None):
|
|
super().__init__(message)
|
|
self.response = _MockResponse(status_code, payload)
|
|
|
|
|
|
class TestExtractHttpStatus:
|
|
"""Status-code extraction should work across exception shapes."""
|
|
|
|
def test_extracts_from_response_attr(self, image_tool):
|
|
exc = _MockHttpxError(403)
|
|
assert image_tool._extract_http_status(exc) == 403
|
|
|
|
|
|
def test_response_attr_without_status_code_returns_none(self, image_tool):
|
|
class OddResponse:
|
|
pass
|
|
exc = Exception("weird")
|
|
exc.response = OddResponse() # type: ignore[attr-defined]
|
|
assert image_tool._extract_http_status(exc) is None
|
|
|
|
|
|
class TestManagedGatewayErrorTranslation:
|
|
"""4xx from the Nous managed gateway should be translated to a user-actionable message."""
|
|
|
|
def test_4xx_translates_to_value_error_with_remediation(self, image_tool, monkeypatch):
|
|
"""403 from managed gateway → ValueError mentioning FAL_KEY + hermes tools."""
|
|
from unittest.mock import MagicMock
|
|
|
|
# Simulate: managed mode active, managed submit raises 4xx.
|
|
managed_gateway = MagicMock()
|
|
managed_gateway.gateway_origin = "https://fal-queue-gateway.example.com"
|
|
managed_gateway.nous_user_token = "test-token"
|
|
monkeypatch.setattr(image_tool, "_resolve_managed_fal_gateway",
|
|
lambda: managed_gateway)
|
|
|
|
bad_request = _MockHttpxError(403, "Forbidden")
|
|
mock_managed_client = MagicMock()
|
|
mock_managed_client.submit.side_effect = bad_request
|
|
monkeypatch.setattr(image_tool, "_get_managed_fal_client",
|
|
lambda gw: mock_managed_client)
|
|
|
|
with pytest.raises(ValueError) as exc_info:
|
|
image_tool._submit_fal_request("fal-ai/nano-banana-pro", {"prompt": "x"})
|
|
|
|
msg = str(exc_info.value)
|
|
assert "fal-ai/nano-banana-pro" in msg
|
|
assert "403" in msg
|
|
assert "FAL_KEY" in msg
|
|
assert "hermes tools" in msg
|
|
# Original exception chained for debugging
|
|
assert exc_info.value.__cause__ is bad_request
|
|
|
|
def test_billing_meter_error_is_preserved_instead_of_called_model_unavailable(
|
|
self, image_tool, monkeypatch
|
|
):
|
|
"""Portal billing configuration is the root cause, not a missing model."""
|
|
from unittest.mock import MagicMock
|
|
|
|
managed_gateway = MagicMock()
|
|
managed_gateway.gateway_origin = "https://fal-queue-gateway.example.com"
|
|
managed_gateway.nous_user_token = "test-token"
|
|
monkeypatch.setattr(
|
|
image_tool, "_resolve_managed_fal_gateway", lambda: managed_gateway
|
|
)
|
|
payload = {
|
|
"error": {
|
|
"code": "BILLING_ERROR",
|
|
"message": "Charge authorization failed",
|
|
"details": {
|
|
"upstreamPayload": {
|
|
"code": "unsupported_pricing_meter",
|
|
"error": "Unsupported resolver usage meter",
|
|
}
|
|
},
|
|
}
|
|
}
|
|
billing_error = _MockHttpxError(409, payload=payload)
|
|
mock_managed_client = MagicMock()
|
|
mock_managed_client.submit.side_effect = billing_error
|
|
monkeypatch.setattr(
|
|
image_tool, "_get_managed_fal_client", lambda gw: mock_managed_client
|
|
)
|
|
|
|
with pytest.raises(ValueError) as exc_info:
|
|
image_tool._submit_fal_request(
|
|
"openai/gpt-image-2.5/flare/text-to-image", {"prompt": "x"}
|
|
)
|
|
|
|
msg = str(exc_info.value)
|
|
assert "Charge authorization failed" in msg
|
|
assert "BILLING_ERROR" in msg
|
|
assert "unsupported_pricing_meter" in msg
|
|
assert "Nous Portal billing" in msg
|
|
assert "may not yet be enabled" not in msg
|
|
|
|
|
|
def test_non_http_exception_from_managed_bubbles_up(self, image_tool, monkeypatch):
|
|
"""Connection errors, timeouts, etc. from managed mode aren't 4xx —
|
|
they should bubble up unchanged so callers can retry or diagnose."""
|
|
from unittest.mock import MagicMock
|
|
|
|
managed_gateway = MagicMock()
|
|
monkeypatch.setattr(image_tool, "_resolve_managed_fal_gateway",
|
|
lambda: managed_gateway)
|
|
|
|
conn_error = ConnectionError("network down")
|
|
mock_managed_client = MagicMock()
|
|
mock_managed_client.submit.side_effect = conn_error
|
|
monkeypatch.setattr(image_tool, "_get_managed_fal_client",
|
|
lambda gw: mock_managed_client)
|
|
|
|
with pytest.raises(ConnectionError):
|
|
image_tool._submit_fal_request("fal-ai/flux-2-pro", {"prompt": "x"})
|
|
|
|
|
|
class TestKreaModelNormalization:
|
|
"""Native ``krea-2-*`` detection for managed Krea routing."""
|
|
|
|
def test_native_models_detected(self, image_tool):
|
|
for mid in ("krea-2-medium", "krea-2-large", "krea-2-medium-turbo"):
|
|
assert image_tool._normalize_krea_model(mid) == mid
|
|
|
|
|
|
def test_non_krea_models_are_not_krea(self, image_tool):
|
|
for mid in ("fal-ai/flux-2/klein/9b", "fal-ai/nano-banana-pro", None, "", 123):
|
|
assert image_tool._normalize_krea_model(mid) is None
|
|
|
|
|
|
class TestManagedKreaRouting:
|
|
"""`_maybe_route_managed_krea` only fires for Krea models in managed mode."""
|
|
|
|
def test_no_route_when_model_not_krea(self, image_tool, monkeypatch):
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_provider", lambda: None)
|
|
monkeypatch.setattr(
|
|
image_tool, "_read_configured_image_model", lambda: "fal-ai/flux-2/klein/9b"
|
|
)
|
|
assert image_tool._maybe_route_managed_krea("p", "square") is None
|
|
|
|
|
|
def test_routes_native_krea_model_to_krea_plugin_in_managed_mode(
|
|
self, image_tool, monkeypatch
|
|
):
|
|
from types import SimpleNamespace
|
|
from unittest.mock import MagicMock
|
|
import json as _json
|
|
|
|
monkeypatch.setattr(image_tool, "_read_configured_image_provider", lambda: None)
|
|
monkeypatch.setattr(
|
|
image_tool,
|
|
"_read_configured_image_model",
|
|
lambda: "krea-2-large",
|
|
)
|
|
import plugins.image_gen.krea as krea_mod
|
|
|
|
monkeypatch.setattr(
|
|
krea_mod,
|
|
"_resolve_managed_krea_gateway",
|
|
lambda: SimpleNamespace(
|
|
vendor="krea",
|
|
gateway_origin="https://krea-gateway.example.com",
|
|
nous_user_token="tok",
|
|
managed_mode=True,
|
|
),
|
|
)
|
|
|
|
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._maybe_route_managed_krea("a cat", "portrait")
|
|
assert out is not None
|
|
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 TestFalKreaCatalog:
|
|
"""Krea 2 on FAL remains in the FAL picker for FAL-billed users."""
|
|
|
|
def test_fal_krea_models_in_fal_catalog(self, image_tool):
|
|
assert "fal-ai/krea/v2/medium/text-to-image" in image_tool.FAL_MODELS
|
|
assert "fal-ai/krea/v2/large/text-to-image" in image_tool.FAL_MODELS
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# 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_omitted_is_off_for_previously_default_on_model(self, image_tool, monkeypatch):
|
|
"""flux-2-pro was the old default-on model — now off like the rest."""
|
|
self._run(image_tool, monkeypatch,
|
|
model="fal-ai/flux-2-pro", 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
|