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feat(api-nodes): add Gpt 5.5 and 5.5-pro LLM models
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@ -56,14 +56,14 @@ class ModelResponseProperties(BaseModel):
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instructions: str | None = Field(None)
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max_output_tokens: int | None = Field(None)
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model: str | None = Field(None)
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temperature: float | None = Field(1, description="Controls randomness in the response", ge=0.0, le=2.0)
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temperature: float | None = Field(None, description="Controls randomness in the response", ge=0.0, le=2.0)
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top_p: float | None = Field(
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1,
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None,
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description="Controls diversity of the response via nucleus sampling",
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ge=0.0,
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le=1.0,
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)
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truncation: str | None = Field("disabled", description="Allowed values: 'auto' or 'disabled'")
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truncation: str | None = Field(None, description="Allowed values: 'auto' or 'disabled'")
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class ResponseProperties(BaseModel):
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@ -49,6 +49,8 @@ class SupportedOpenAIModel(str, Enum):
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gpt_5 = "gpt-5"
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gpt_5_mini = "gpt-5-mini"
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gpt_5_nano = "gpt-5-nano"
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gpt_5_5 = "gpt-5.5"
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gpt_5_5_pro = "gpt-5.5-pro"
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async def validate_and_cast_response(response, timeout: int = None) -> torch.Tensor:
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@ -739,6 +741,16 @@ class OpenAIChatNode(IO.ComfyNode):
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"usd": [0.002, 0.008],
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"format": { "approximate": true, "separator": "-", "suffix": " per 1K tokens" }
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}
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: $contains($m, "gpt-5.5-pro") ? {
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"type": "list_usd",
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"usd": [0.03, 0.18],
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"format": { "approximate": true, "separator": "-", "suffix": " per 1K tokens" }
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}
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: $contains($m, "gpt-5.5") ? {
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"type": "list_usd",
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"usd": [0.005, 0.03],
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"format": { "approximate": true, "separator": "-", "suffix": " per 1K tokens" }
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}
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: $contains($m, "gpt-5-nano") ? {
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"type": "list_usd",
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"usd": [0.00005, 0.0004],
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