Andy RatsirarsonandClaude Sonnet 5
3ea918e84c
- Merge Omni Flash into the existing "gemini" provider: one dropdown entry, model list now includes both Veo and Omni Flash ids, each revealing its own correct settings (resolution/duration/etc). - Omni Flash runs through litellm's request/response Interactions API (litellm.interactions.acreate) instead of the polling avideo_generation/avideo_status/avideo_content trio Veo and the other providers use, since it has no status-polling endpoint. Text-to-video only for now; image/video-conditioned input and conversational editing aren't implemented yet. - Fix progress reporting for the Omni path: it now ticks up by elapsed/timeout while waiting on the single request instead of sitting at 0% and jumping straight to done. - Fix live Veo model listing to filter out models Google's API no longer serves for generation (checks supported_actions for predictLongRunning) rather than trusting name-matching alone — root cause of a live 404 on veo-3.1-fast-generate-001, which is also dropped from the static fallback list. - Bump litellm 1.92.0 -> 1.100.0. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CVFBqa77Zo9t4ps8wt7YB2
400 lines
15 KiB
Python
400 lines
15 KiB
Python
import asyncio
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import base64
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import types
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from unittest.mock import AsyncMock, patch
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import pytest
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from src import nodes
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class FakeVideoObject:
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def __init__(self, status, id="vid_1", error=None):
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self.status = status
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self.id = id
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self.error = error
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def _gemini_source(model="veo-3.1-fast-generate-preview", **overrides):
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settings = {
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"model": model,
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"size": "16:9",
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"resolution": "1K",
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"seconds": 8,
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"person_generation": "allow_all",
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}
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settings.update(overrides)
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return {"source": "text", "provider": {"provider": "gemini", "model": settings}}
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def _openai_source(model="sora-2", **overrides):
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settings = {"model": model, "size": "16:9", "resolution": "1K", "seconds": 4}
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settings.update(overrides)
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return {"source": "text", "provider": {"provider": "openai", "model": settings}}
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@pytest.fixture(autouse=True)
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def _hidden():
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nodes.APIVideoGenerate.hidden = types.SimpleNamespace(unique_id="test-node")
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yield
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nodes.APIVideoGenerate.hidden = None
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def test_generate_success_polls_until_completed():
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async def run():
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gen_mock = AsyncMock(return_value=FakeVideoObject("processing"))
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status_mock = AsyncMock(
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side_effect=[FakeVideoObject("processing"), FakeVideoObject("completed")]
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)
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content_mock = AsyncMock(return_value=b"fake-mp4-bytes")
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with patch.object(nodes, "avideo_generation", gen_mock), patch.object(
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nodes, "avideo_status", status_mock
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), patch.object(nodes, "avideo_content", content_mock), patch(
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"asyncio.sleep", AsyncMock(return_value=None)
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):
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result = await nodes.APIVideoGenerate.execute(
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prompt="a cat riding a bike",
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source=_gemini_source(),
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)
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assert isinstance(result, nodes.io.NodeOutput)
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video = result.args[0]
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assert isinstance(video, nodes.InputImpl.VideoFromFile)
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assert video.file_obj.getvalue() == b"fake-mp4-bytes"
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assert status_mock.call_count == 2
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gen_mock.assert_awaited_once()
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assert gen_mock.call_args.kwargs["model"] == "gemini/veo-3.1-fast-generate-preview"
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assert gen_mock.call_args.kwargs["aspectRatio"] == "16:9"
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assert gen_mock.call_args.kwargs["resolution"] == "720p"
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assert gen_mock.call_args.kwargs["durationSeconds"] == 8
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assert gen_mock.call_args.kwargs["personGeneration"] == "allow_all"
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assert "api_key" not in gen_mock.call_args.kwargs
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assert "api_key" not in status_mock.call_args.kwargs
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assert "api_key" not in content_mock.call_args.kwargs
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asyncio.run(run())
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def test_api_key_threaded_through_every_call():
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async def run():
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gen_mock = AsyncMock(return_value=FakeVideoObject("completed"))
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status_mock = AsyncMock()
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content_mock = AsyncMock(return_value=b"bytes")
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with patch.object(nodes, "avideo_generation", gen_mock), patch.object(
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nodes, "avideo_status", status_mock
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), patch.object(nodes, "avideo_content", content_mock), patch(
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"asyncio.sleep", AsyncMock(return_value=None)
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):
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await nodes.APIVideoGenerate.execute(
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prompt="a dog surfing",
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source=_openai_source(),
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api_key="sk-test-123",
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)
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assert gen_mock.call_args.kwargs["model"] == "openai/sora-2"
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assert gen_mock.call_args.kwargs["size"] == "1280x720"
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assert gen_mock.call_args.kwargs["seconds"] == "4"
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assert gen_mock.call_args.kwargs["api_key"] == "sk-test-123"
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assert content_mock.call_args.kwargs["api_key"] == "sk-test-123"
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status_mock.assert_not_awaited() # already completed, no polling needed
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asyncio.run(run())
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def test_failed_generation_raises_runtime_error():
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async def run():
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gen_mock = AsyncMock(return_value=FakeVideoObject("processing"))
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status_mock = AsyncMock(
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return_value=FakeVideoObject("failed", error={"message": "content filtered"})
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)
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content_mock = AsyncMock()
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with patch.object(nodes, "avideo_generation", gen_mock), patch.object(
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nodes, "avideo_status", status_mock
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), patch.object(nodes, "avideo_content", content_mock), patch(
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"asyncio.sleep", AsyncMock(return_value=None)
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):
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with pytest.raises(RuntimeError, match="content filtered"):
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await nodes.APIVideoGenerate.execute(
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prompt="anything",
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source=_gemini_source(),
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)
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content_mock.assert_not_awaited()
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asyncio.run(run())
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def test_timeout_raises_when_generation_never_completes():
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async def run():
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gen_mock = AsyncMock(return_value=FakeVideoObject("processing"))
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status_mock = AsyncMock(return_value=FakeVideoObject("processing"))
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with patch.object(nodes, "avideo_generation", gen_mock), patch.object(
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nodes, "avideo_status", status_mock
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), patch("asyncio.sleep", AsyncMock(return_value=None)):
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with pytest.raises(TimeoutError):
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await nodes.APIVideoGenerate.execute(
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prompt="anything",
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source=_gemini_source(),
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poll_interval=5.0,
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timeout=12.0,
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)
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asyncio.run(run())
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def test_runwayml_kwargs_mapping():
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async def run():
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gen_mock = AsyncMock(return_value=FakeVideoObject("completed"))
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content_mock = AsyncMock(return_value=b"bytes")
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source = {
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"source": "text",
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"provider": {
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"provider": "runwayml",
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"model": {
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"model": "gen3a_turbo",
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"size": "9:16",
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"resolution": "2K",
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"seconds": 10,
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"seed": 42,
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},
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},
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}
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with patch.object(nodes, "avideo_generation", gen_mock), patch.object(
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nodes, "avideo_content", content_mock
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), patch("asyncio.sleep", AsyncMock(return_value=None)):
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await nodes.APIVideoGenerate.execute(prompt="anything", source=source)
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assert gen_mock.call_args.kwargs["model"] == "runwayml/gen3a_turbo"
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assert gen_mock.call_args.kwargs["ratio"] == "1080:1920"
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assert gen_mock.call_args.kwargs["duration"] == 10
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assert gen_mock.call_args.kwargs["seed"] == 42
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asyncio.run(run())
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def test_schema_builds_nested_source_provider_model_combo():
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schema = nodes.APIVideoGenerate.define_schema()
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source_input = next(i for i in schema.inputs if i.name == "source")
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assert [o.key for o in source_input.options] == ["text", "image"]
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text_option, image_option = source_input.options
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provider_input = text_option.inputs[0]
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assert provider_input.name == "provider"
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provider_keys = [o.key for o in provider_input.options]
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assert provider_keys == ["gemini", "openai", "azure", "runwayml"]
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for option in provider_input.options:
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model_input = option.inputs[0]
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assert model_input.name == "model"
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assert len(model_input.options) > 0
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for model_option in model_input.options:
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field_names = {i.name for i in model_option.inputs}
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assert {"size", "resolution", "seconds"} <= field_names
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gemini_text_option = next(o for o in provider_input.options if o.key == "gemini")
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gemini_text_model_input = gemini_text_option.inputs[0]
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gemini_text_model_ids = {o.key for o in gemini_text_model_input.options}
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assert "veo-3.1-fast-generate-preview" in gemini_text_model_ids
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assert "gemini-omni-flash-preview" in gemini_text_model_ids
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veo_option = next(o for o in gemini_text_model_input.options if o.key == "veo-3.1-fast-generate-preview")
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veo_field_names = {i.name for i in veo_option.inputs}
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assert "person_generation" in veo_field_names
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omni_option = next(o for o in gemini_text_model_input.options if o.key == "gemini-omni-flash-preview")
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omni_field_names = {i.name for i in omni_option.inputs}
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assert "person_generation" not in omni_field_names
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image_provider_input = image_option.inputs[0]
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assert image_provider_input.name == "provider"
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assert [o.key for o in image_provider_input.options] == ["gemini"]
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gemini_model_input = image_provider_input.options[0].inputs[0]
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assert gemini_model_input.name == "model"
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gemini_image_model_ids = {o.key for o in gemini_model_input.options}
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assert "gemini-omni-flash-preview" not in gemini_image_model_ids
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for model_option in gemini_model_input.options:
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field_names = {i.name for i in model_option.inputs}
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assert {"size", "resolution", "seconds", "reference_image", "person_generation"} <= field_names
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person_generation_input = next(
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i for i in model_option.inputs if i.name == "person_generation"
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)
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assert person_generation_input.kwargs["options"] == ["allow_adult"]
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def test_gemini_image_to_video_kwargs_mapping():
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async def run():
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gen_mock = AsyncMock(return_value=FakeVideoObject("completed"))
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content_mock = AsyncMock(return_value=b"bytes")
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fake_tensor = object()
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fake_bytesio = object()
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source = {
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"source": "image",
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"provider": {
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"provider": "gemini",
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"model": {
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"model": "veo-3.1-fast-generate-preview",
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"size": "9:16",
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"resolution": "2K",
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"seconds": 8,
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"reference_image": fake_tensor,
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"person_generation": "allow_adult",
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},
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},
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}
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with patch.object(nodes, "avideo_generation", gen_mock), patch.object(
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nodes, "avideo_content", content_mock
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), patch.object(
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nodes.GeminiModel, "image_tensor_to_bytesio", return_value=fake_bytesio
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) as tensor_mock, patch("asyncio.sleep", AsyncMock(return_value=None)):
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await nodes.APIVideoGenerate.execute(prompt="animate this photo", source=source)
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tensor_mock.assert_called_once_with(fake_tensor)
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kwargs = gen_mock.call_args.kwargs
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assert kwargs["model"] == "gemini/veo-3.1-fast-generate-preview"
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assert kwargs["aspectRatio"] == "9:16"
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assert kwargs["resolution"] == "1080p"
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assert kwargs["durationSeconds"] == 8
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assert kwargs["personGeneration"] == "allow_adult"
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assert kwargs["input_reference"] is fake_bytesio
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asyncio.run(run())
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def test_gemini_image_to_video_requires_reference_image():
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async def run():
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gen_mock = AsyncMock(return_value=FakeVideoObject("completed"))
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source = {
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"source": "image",
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"provider": {
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"provider": "gemini",
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"model": {
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"model": "veo-3.1-fast-generate-preview",
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"size": "9:16",
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"resolution": "2K",
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"seconds": 8,
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"person_generation": "allow_adult",
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},
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},
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}
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with patch.object(nodes, "avideo_generation", gen_mock):
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with pytest.raises(ValueError, match="reference_image"):
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await nodes.APIVideoGenerate.execute(prompt="animate this photo", source=source)
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gen_mock.assert_not_awaited()
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asyncio.run(run())
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class FakeInteractionResponse:
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def __init__(self, steps):
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self.steps = steps
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def _gemini_omni_source(model="gemini-omni-flash-preview", **overrides):
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settings = {"model": model, "size": "16:9", "resolution": "720", "seconds": 5}
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settings.update(overrides)
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return {"source": "text", "provider": {"provider": "gemini", "model": settings}}
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def test_gemini_omni_uses_interactions_api_not_polling():
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async def run():
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interaction_mock = AsyncMock(
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return_value=FakeInteractionResponse(
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steps=[
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{"type": "user_input", "content": [{"type": "text", "text": "hi"}]},
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{
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"type": "model_output",
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"content": [
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{
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"type": "video",
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"data": base64.b64encode(b"fake-mp4-bytes").decode(),
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"mime_type": "video/mp4",
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}
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],
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},
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]
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)
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)
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gen_mock = AsyncMock()
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with patch.object(nodes, "acreate_interaction", interaction_mock), patch.object(
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nodes, "avideo_generation", gen_mock
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):
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result = await nodes.APIVideoGenerate.execute(
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prompt="a marble rolling down a track",
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source=_gemini_omni_source(),
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)
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gen_mock.assert_not_awaited()
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interaction_mock.assert_awaited_once()
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kwargs = interaction_mock.call_args.kwargs
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assert kwargs["model"] == "gemini/gemini-omni-flash-preview"
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assert kwargs["input"] == "a marble rolling down a track"
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assert kwargs["response_format"] == {
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"type": "video",
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"aspect_ratio": "16:9",
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"resolution": "720p",
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}
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assert "api_key" not in kwargs
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video = result.args[0]
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assert isinstance(video, nodes.InputImpl.VideoFromFile)
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assert video.file_obj.getvalue() == b"fake-mp4-bytes"
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asyncio.run(run())
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def test_gemini_omni_uri_delivery_raises_clear_error():
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async def run():
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interaction_mock = AsyncMock(
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return_value=FakeInteractionResponse(
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steps=[
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{
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"type": "model_output",
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"content": [{"type": "video", "uri": "https://example.com/video.mp4"}],
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}
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]
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)
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)
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with patch.object(nodes, "acreate_interaction", interaction_mock):
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with pytest.raises(RuntimeError, match="uri"):
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await nodes.APIVideoGenerate.execute(
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prompt="anything",
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source=_gemini_omni_source(),
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)
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asyncio.run(run())
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def test_azure_provider_string_uses_azure_prefix():
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async def run():
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gen_mock = AsyncMock(return_value=FakeVideoObject("completed"))
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content_mock = AsyncMock(return_value=b"bytes")
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source = _openai_source(model="sora-2-pro")
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source["provider"]["provider"] = "azure"
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with patch.object(nodes, "avideo_generation", gen_mock), patch.object(
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nodes, "avideo_content", content_mock
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), patch("asyncio.sleep", AsyncMock(return_value=None)):
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await nodes.APIVideoGenerate.execute(prompt="anything", source=source)
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assert gen_mock.call_args.kwargs["model"] == "azure/sora-2-pro"
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asyncio.run(run())
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