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
31 lines
1.0 KiB
Python
31 lines
1.0 KiB
Python
from .base import Model
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from ..settings.base import Resolutions, Sizes
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from ..settings.video import VideoSettings, dimensions_string
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class _SoraModel(Model):
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"""Shared Sora video logic for the OpenAI and Azure providers, which expose
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the same model family and parameters via litellm. Subclasses set PROVIDER."""
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# MAX_SECONDS=12 is a reasonable-but-unconfirmed ceiling: litellm's own
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# default is "4" and no hard max was confirmed against Sora's API docs.
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VIDEO_SETTINGS = VideoSettings(
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SIZE=[Sizes._16_9, Sizes._9_16],
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RESOLUTIONS=[Resolutions._1K, Resolutions._2K],
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MIN_SECONDS=4,
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MAX_SECONDS=12,
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)
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@classmethod
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def list_models(cls) -> list[str]:
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return ["sora-2", "sora-2-pro", "sora-2-pro-high-res"]
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@classmethod
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def video_kwargs(cls, model_id: str, settings: dict) -> dict:
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size = dimensions_string(settings["size"], settings["resolution"], "x")
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return {"size": size, "seconds": str(settings["seconds"])}
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class OpenAIModel(_SoraModel):
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PROVIDER = "openai"
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