mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-07-08 15:37:46 +08:00
Merge branch 'master' into pixal3d
This commit is contained in:
Alexis Rolland
GitHub
commit
ed16bd8319
@ -1,4 +1,4 @@
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from typing import Literal
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from typing import Any, Literal
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from pydantic import BaseModel, Field
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@ -316,3 +316,36 @@ VIDEO_TASKS_EXECUTION_TIME = {
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"1080p": 150,
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},
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}
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class SeedAudioConfig(BaseModel):
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format: str = Field(default="mp3")
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sample_rate: int = Field(default=24000)
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speech_rate: int = Field(default=0)
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loudness_rate: int = Field(default=0)
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pitch_rate: int = Field(default=0)
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class SeedAudioReference(BaseModel):
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speaker: str | None = Field(default=None)
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audio_data: str | None = Field(default=None)
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audio_url: str | None = Field(default=None)
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image_data: str | None = Field(default=None)
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image_url: str | None = Field(default=None)
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class SeedAudioRequest(BaseModel):
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model: str = Field(default="seed-audio-1.0")
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text_prompt: str = Field(...)
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references: list[SeedAudioReference] | None = Field(default=None)
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audio_config: SeedAudioConfig = Field(default_factory=SeedAudioConfig)
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watermark: dict[str, Any] = Field(default_factory=dict)
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class SeedAudioResponse(BaseModel):
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audio: str | None = Field(default=None)
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url: str | None = Field(default=None)
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duration: float | None = Field(default=None)
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original_duration: float | None = Field(default=None)
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code: int | None = Field(default=None)
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message: str | None = Field(default=None)
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@ -1,147 +0,0 @@
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from enum import Enum
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from typing import Optional
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from pydantic import BaseModel, Field, confloat
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class StabilityFormat(str, Enum):
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png = 'png'
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jpeg = 'jpeg'
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webp = 'webp'
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class StabilityAspectRatio(str, Enum):
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ratio_1_1 = "1:1"
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ratio_16_9 = "16:9"
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ratio_9_16 = "9:16"
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ratio_3_2 = "3:2"
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ratio_2_3 = "2:3"
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ratio_5_4 = "5:4"
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ratio_4_5 = "4:5"
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ratio_21_9 = "21:9"
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ratio_9_21 = "9:21"
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def get_stability_style_presets(include_none=True):
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presets = []
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if include_none:
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presets.append("None")
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return presets + [x.value for x in StabilityStylePreset]
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class StabilityStylePreset(str, Enum):
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_3d_model = "3d-model"
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analog_film = "analog-film"
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anime = "anime"
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cinematic = "cinematic"
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comic_book = "comic-book"
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digital_art = "digital-art"
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enhance = "enhance"
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fantasy_art = "fantasy-art"
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isometric = "isometric"
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line_art = "line-art"
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low_poly = "low-poly"
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modeling_compound = "modeling-compound"
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neon_punk = "neon-punk"
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origami = "origami"
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photographic = "photographic"
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pixel_art = "pixel-art"
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tile_texture = "tile-texture"
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class Stability_SD3_5_Model(str, Enum):
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sd3_5_large = "sd3.5-large"
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# sd3_5_large_turbo = "sd3.5-large-turbo"
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sd3_5_medium = "sd3.5-medium"
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class Stability_SD3_5_GenerationMode(str, Enum):
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text_to_image = "text-to-image"
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image_to_image = "image-to-image"
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class StabilityStable3_5Request(BaseModel):
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model: str = Field(...)
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mode: str = Field(...)
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prompt: str = Field(...)
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negative_prompt: Optional[str] = Field(None)
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aspect_ratio: Optional[str] = Field(None)
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seed: Optional[int] = Field(None)
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output_format: Optional[str] = Field(StabilityFormat.png.value)
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image: Optional[str] = Field(None)
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style_preset: Optional[str] = Field(None)
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cfg_scale: float = Field(...)
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strength: Optional[confloat(ge=0.0, le=1.0)] = Field(None)
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class StabilityUpscaleConservativeRequest(BaseModel):
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prompt: str = Field(...)
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negative_prompt: Optional[str] = Field(None)
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seed: Optional[int] = Field(None)
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output_format: Optional[str] = Field(StabilityFormat.png.value)
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image: Optional[str] = Field(None)
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creativity: Optional[confloat(ge=0.2, le=0.5)] = Field(None)
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class StabilityUpscaleCreativeRequest(BaseModel):
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prompt: str = Field(...)
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negative_prompt: Optional[str] = Field(None)
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seed: Optional[int] = Field(None)
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output_format: Optional[str] = Field(StabilityFormat.png.value)
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image: Optional[str] = Field(None)
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creativity: Optional[confloat(ge=0.1, le=0.5)] = Field(None)
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style_preset: Optional[str] = Field(None)
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class StabilityStableUltraRequest(BaseModel):
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prompt: str = Field(...)
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negative_prompt: Optional[str] = Field(None)
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aspect_ratio: Optional[str] = Field(None)
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seed: Optional[int] = Field(None)
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output_format: Optional[str] = Field(StabilityFormat.png.value)
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image: Optional[str] = Field(None)
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style_preset: Optional[str] = Field(None)
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strength: Optional[confloat(ge=0.0, le=1.0)] = Field(None)
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class StabilityStableUltraResponse(BaseModel):
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image: Optional[str] = Field(None)
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finish_reason: Optional[str] = Field(None)
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seed: Optional[int] = Field(None)
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class StabilityResultsGetResponse(BaseModel):
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image: Optional[str] = Field(None)
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finish_reason: Optional[str] = Field(None)
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seed: Optional[int] = Field(None)
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id: Optional[str] = Field(None)
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name: Optional[str] = Field(None)
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errors: Optional[list[str]] = Field(None)
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status: Optional[str] = Field(None)
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result: Optional[str] = Field(None)
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class StabilityAsyncResponse(BaseModel):
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id: Optional[str] = Field(None)
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class StabilityTextToAudioRequest(BaseModel):
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model: str = Field(...)
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prompt: str = Field(...)
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duration: int = Field(190, ge=1, le=190)
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seed: int = Field(0, ge=0, le=4294967294)
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steps: int = Field(8, ge=4, le=8)
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output_format: str = Field("wav")
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class StabilityAudioToAudioRequest(StabilityTextToAudioRequest):
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strength: float = Field(0.01, ge=0.01, le=1.0)
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class StabilityAudioInpaintRequest(StabilityTextToAudioRequest):
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mask_start: int = Field(30, ge=0, le=190)
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mask_end: int = Field(190, ge=0, le=190)
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class StabilityAudioResponse(BaseModel):
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audio: Optional[str] = Field(None)
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@ -1,3 +1,4 @@
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import base64
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import hashlib
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import logging
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import math
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@ -20,6 +21,10 @@ from comfy_api_nodes.apis.bytedance import (
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GetAssetResponse,
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Image2VideoTaskCreationRequest,
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ImageTaskCreationResponse,
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SeedAudioConfig,
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SeedAudioReference,
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SeedAudioRequest,
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SeedAudioResponse,
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Seedance2TaskCreationRequest,
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SeedanceCreateAssetRequest,
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SeedanceCreateAssetResponse,
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@ -43,6 +48,8 @@ from comfy_api_nodes.apis.bytedance import (
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)
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from comfy_api_nodes.util import (
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ApiEndpoint,
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audio_bytes_to_audio_input,
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audio_input_to_mp3,
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download_url_to_image_tensor,
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download_url_to_video_output,
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downscale_image_tensor_by_max_side,
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@ -51,11 +58,14 @@ from comfy_api_nodes.util import (
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image_tensor_pair_to_batch,
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poll_op,
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sync_op,
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tensor_to_base64_string,
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upload_audio_to_comfyapi,
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upload_image_to_comfyapi,
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upload_images_to_comfyapi,
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upload_video_to_comfyapi,
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upscale_image_tensor_to_min_pixels,
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upscale_video_to_min_pixels,
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validate_audio_duration,
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validate_image_aspect_ratio,
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validate_image_dimensions,
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validate_string,
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@ -2474,6 +2484,311 @@ class ByteDanceCreateVideoAsset(IO.ComfyNode):
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return IO.NodeOutput(asset_id, resolved_group)
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MODE_TEXT = "text only"
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MODE_AUDIO = "audio reference"
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MODE_IMAGE = "image reference"
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MODE_SPEAKER = "preset voice"
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# (speaker_id, display_label) for built-in TTS 2.0 voices; resolvable ids are account-scoped.
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SEED_AUDIO_PRESET_VOICES: list[tuple[str, str]] = [
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("zh_female_vv_uranus_bigtts", "Vivi (Female, multilingual)"),
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("zh_female_xiaohe_uranus_bigtts", "Mindy (Female, multilingual)"),
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("en_female_stokie_uranus_bigtts", "Stokie (Female, English)"),
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("en_female_dacey_uranus_bigtts", "Dacey (Female, English)"),
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("en_male_tim_uranus_bigtts", "Tim (Male, English)"),
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("zh_male_m191_uranus_bigtts", "Kian (Male, multilingual)"),
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("zh_male_taocheng_uranus_bigtts", "Cedric (Male, multilingual)"),
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("zh_male_sophie_uranus_bigtts", "Sophie (Female, multilingual)"),
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("zh_female_yingyujiaoxue_uranus_bigtts", "Jean (Female, multilingual)"),
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("zh_male_dayi_uranus_bigtts", "Magnus (Male, multilingual)"),
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("zh_female_mizai_uranus_bigtts", "Mabel (Female, multilingual)"),
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("zh_female_jitangnv_uranus_bigtts", "Nadia (Female, multilingual)"),
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("zh_female_meilinvyou_uranus_bigtts", "Opal (Female, multilingual)"),
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("zh_female_liuchangnv_uranus_bigtts", "Pearl (Female, multilingual)"),
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("zh_male_ruyayichen_uranus_bigtts", "Quentin (Male, multilingual)"),
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("zh_female_vivo_uranus_bigtts", "Vienna (Female, multilingual)"),
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("zh_female_xiaoai_uranus_bigtts", "Alina (Female, multilingual)"),
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("zh_female_cancan_uranus_bigtts", "Corinne (Female, multilingual)"),
|
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("zh_female_tianmeixiaoyuan_uranus_bigtts", "Esther (Female, multilingual)"),
|
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("zh_female_tianmeitaozi_uranus_bigtts", "Freya (Female, multilingual)"),
|
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("zh_female_shuangkuaisisi_uranus_bigtts", "Gigi (Female, multilingual)"),
|
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("zh_female_peiqi_uranus_bigtts", "Holly (Female, multilingual)"),
|
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("zh_female_xiaoxue_uranus_bigtts", "Lyla (Female, multilingual)"),
|
||||
("zh_female_yuanqi_uranus_bigtts", "Daisy (Female, multilingual)"),
|
||||
("zh_female_kefunvsheng_uranus_bigtts", "Tracy (Female, multilingual)"),
|
||||
("zh_male_shaonianzixin_uranus_bigtts", "Jess (Male, multilingual)"),
|
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("zh_female_linjianvhai_uranus_bigtts", "Pinky (Female, multilingual)"),
|
||||
("zh_female_kiwi_uranus_bigtts", "Sweety (Female, multilingual)"),
|
||||
("zh_female_sajiaoxuemei_uranus_bigtts", "Sandy (Female, multilingual)"),
|
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("de_male_seven_uranus_bigtts", "Sven (Male, German)"),
|
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("jp_female_minimi_uranus_bigtts", "Minimi (Female, Japanese)"),
|
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("fr_male_usseau_uranus_bigtts", "Usseau (Male, French)"),
|
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("es_male_felipe_uranus_bigtts", "Felipe (Male, Spanish)"),
|
||||
("id_male_han_uranus_bigtts", "Han (Male, Indonesian)"),
|
||||
("pt_male_martins_uranus_bigtts", "Martins (Male, Portuguese)"),
|
||||
("it_male_enzo_uranus_bigtts", "Enzo (Male, Italian)"),
|
||||
("kr_male_shane_uranus_bigtts", "Shane (Male, Korean)"),
|
||||
("zh_male_liufei_uranus_bigtts", "Felix (Male, Chinese)"),
|
||||
("zh_female_qingxinnvsheng_uranus_bigtts", "Celeste (Female, Chinese)"),
|
||||
("zh_male_sunwukong_uranus_bigtts", "Monkey King (Male, Chinese)"),
|
||||
]
|
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SEED_AUDIO_VOICE_OPTIONS = [label for _, label in SEED_AUDIO_PRESET_VOICES]
|
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SEED_AUDIO_VOICE_MAP = {label: speaker_id for speaker_id, label in SEED_AUDIO_PRESET_VOICES}
|
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|
||||
_AUDIO_TAG_RE = re.compile(r"@Audio(\d+)", re.IGNORECASE)
|
||||
|
||||
|
||||
def max_audio_tag(prompt: str) -> int:
|
||||
"""Highest N referenced as @AudioN in the prompt (0 if none)."""
|
||||
nums = [int(m) for m in _AUDIO_TAG_RE.findall(prompt or "")]
|
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return max(nums) if nums else 0
|
||||
|
||||
|
||||
def connected_audio_indices(reference_mode: dict) -> list[int]:
|
||||
"""Indices (1-based) of connected reference_audio sockets, in order."""
|
||||
return [
|
||||
i
|
||||
for i in range(1, 3 + 1)
|
||||
if reference_mode.get(f"reference_audio_{i}") is not None
|
||||
]
|
||||
|
||||
|
||||
def validate_seed_audio_inputs(
|
||||
text_prompt: str,
|
||||
mode: str,
|
||||
audio_indices: list[int],
|
||||
has_image: bool,
|
||||
preset_voice: str | None = None,
|
||||
) -> None:
|
||||
validate_string(text_prompt, field_name="text_prompt", min_length=1, max_length=3000)
|
||||
max_tag = max_audio_tag(text_prompt)
|
||||
|
||||
if mode == MODE_TEXT:
|
||||
if max_tag:
|
||||
raise ValueError(
|
||||
f"The prompt references @Audio{max_tag}, but reference mode is '{MODE_TEXT}'. "
|
||||
f"Switch to '{MODE_AUDIO}' and connect the reference clip(s)."
|
||||
)
|
||||
elif mode == MODE_AUDIO:
|
||||
if not audio_indices:
|
||||
raise ValueError(
|
||||
f"Reference mode '{MODE_AUDIO}' requires at least one reference_audio input "
|
||||
f"(or switch to '{MODE_TEXT}')."
|
||||
)
|
||||
if audio_indices != list(range(1, len(audio_indices) + 1)):
|
||||
raise ValueError(
|
||||
"Connect reference_audio inputs in order without gaps: reference_audio_1, then _2, then _3."
|
||||
)
|
||||
if max_tag > len(audio_indices):
|
||||
raise ValueError(
|
||||
f"The prompt references @Audio{max_tag}, but only {len(audio_indices)} "
|
||||
f"reference audio(s) are connected."
|
||||
)
|
||||
elif mode == MODE_IMAGE:
|
||||
if not has_image:
|
||||
raise ValueError(f"Reference mode '{MODE_IMAGE}' requires a reference_image input.")
|
||||
if max_tag:
|
||||
raise ValueError(
|
||||
f"@AudioN tags are not used in '{MODE_IMAGE}' mode; the prompt should contain "
|
||||
f"only the text to synthesize."
|
||||
)
|
||||
elif mode == MODE_SPEAKER:
|
||||
if not preset_voice or preset_voice not in SEED_AUDIO_VOICE_MAP:
|
||||
raise ValueError(f"Reference mode '{MODE_SPEAKER}' requires selecting a preset voice.")
|
||||
if max_tag > 1:
|
||||
raise ValueError(
|
||||
f"'{MODE_SPEAKER}' mode uses a single voice, so @Audio{max_tag} is out of range. "
|
||||
f"Remove the @AudioN tags — the whole prompt is read in the selected voice."
|
||||
)
|
||||
else:
|
||||
raise ValueError(f"Unknown reference mode: {mode!r}")
|
||||
|
||||
|
||||
class ByteDanceSeedAudioNode(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls) -> IO.Schema:
|
||||
return IO.Schema(
|
||||
node_id="ByteDanceSeedAudio",
|
||||
display_name="ByteDance Seed Audio 1.0",
|
||||
category="api node/audio/ByteDance",
|
||||
description=(
|
||||
"Generate speech, music, sound effects and multi-speaker dialogue from a single prompt "
|
||||
"with ByteDance Seed Audio 1.0. Describe the voice(s), emotion, ambience, background music "
|
||||
"and sound effects in the prompt, and include the lines to speak. Optionally pick a built-in "
|
||||
"preset voice, clone voices from up to 3 reference clips (tagged @Audio1-3 in the prompt), "
|
||||
"or derive a voice from a character image. Up to 2 minutes of audio per run."
|
||||
),
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"text_prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip=(
|
||||
"Describe the voice(s), emotion, pacing, ambience, background music and sound "
|
||||
"effects, and include the lines to speak (name characters inline for dialogue). "
|
||||
"In 'audio reference' mode, refer to connected clips by order as @Audio1, @Audio2, "
|
||||
"@Audio3. Maximum 3000 characters."
|
||||
),
|
||||
),
|
||||
IO.DynamicCombo.Input(
|
||||
"reference_mode",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(MODE_TEXT, []),
|
||||
IO.DynamicCombo.Option(
|
||||
MODE_AUDIO,
|
||||
[
|
||||
IO.Audio.Input(
|
||||
"reference_audio_1",
|
||||
optional=True,
|
||||
tooltip="Reference clip for voice cloning, tagged @Audio1 in the prompt. "
|
||||
"Up to 30s.",
|
||||
),
|
||||
IO.Audio.Input(
|
||||
"reference_audio_2",
|
||||
optional=True,
|
||||
tooltip="Reference clip tagged @Audio2 in the prompt. Up to 30s.",
|
||||
),
|
||||
IO.Audio.Input(
|
||||
"reference_audio_3",
|
||||
optional=True,
|
||||
tooltip="Reference clip tagged @Audio3 in the prompt. Up to 30s.",
|
||||
),
|
||||
],
|
||||
),
|
||||
IO.DynamicCombo.Option(
|
||||
MODE_IMAGE,
|
||||
[
|
||||
IO.Image.Input(
|
||||
"reference_image",
|
||||
optional=True,
|
||||
tooltip="A single character image; the model derives a voice from it. "
|
||||
"Cannot be combined with reference audio.",
|
||||
),
|
||||
],
|
||||
),
|
||||
IO.DynamicCombo.Option(
|
||||
MODE_SPEAKER,
|
||||
[
|
||||
IO.Combo.Input(
|
||||
"preset_voice",
|
||||
options=SEED_AUDIO_VOICE_OPTIONS,
|
||||
default=SEED_AUDIO_VOICE_OPTIONS[0],
|
||||
tooltip="A built-in TTS 2.0 voice that reads the prompt. No reference "
|
||||
"clip needed, and @AudioN tags are not used in this mode.",
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
tooltip=(
|
||||
"How to condition the voice: 'text only' (describe everything in the prompt), "
|
||||
"'audio reference' (clone up to 3 voices, tagged @Audio1-3), 'image reference' "
|
||||
"(derive a voice from one character image), or 'preset voice' (pick a built-in "
|
||||
"named voice that reads the prompt)."
|
||||
),
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"sample_rate",
|
||||
options=["8000", "16000", "24000", "32000", "44100", "48000"],
|
||||
default="24000",
|
||||
tooltip="Output sample rate in Hz.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"speech_rate",
|
||||
default=0,
|
||||
min=-50,
|
||||
max=100,
|
||||
tooltip="Speaking speed. 0 = normal, 100 = 2.0x, -50 = 0.5x.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"loudness_rate",
|
||||
default=0,
|
||||
min=-50,
|
||||
max=100,
|
||||
tooltip="Loudness. 0 = normal, 100 = 2.0x, -50 = 0.5x.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"pitch_rate",
|
||||
default=0,
|
||||
min=-12,
|
||||
max=12,
|
||||
tooltip="Pitch shift in semitones (-12 to 12).",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=42,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
control_after_generate=True,
|
||||
tooltip="Seed controls whether the node should re-run; "
|
||||
"results are non-deterministic regardless of seed.",
|
||||
),
|
||||
],
|
||||
outputs=[IO.Audio.Output()],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd": 0.2145, "format":{"suffix":"/minute","approximate":true}}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
text_prompt: str,
|
||||
reference_mode: dict,
|
||||
sample_rate: str,
|
||||
speech_rate: int,
|
||||
loudness_rate: int,
|
||||
pitch_rate: int,
|
||||
seed: int,
|
||||
) -> IO.NodeOutput:
|
||||
mode = reference_mode["reference_mode"]
|
||||
audio_indices = connected_audio_indices(reference_mode)
|
||||
image = reference_mode.get("reference_image")
|
||||
preset_voice = reference_mode.get("preset_voice")
|
||||
validate_seed_audio_inputs(text_prompt, mode, audio_indices, image is not None, preset_voice)
|
||||
|
||||
references: list[SeedAudioReference] | None = None
|
||||
if mode == MODE_AUDIO:
|
||||
references = []
|
||||
for i in audio_indices:
|
||||
clip = reference_mode[f"reference_audio_{i}"]
|
||||
validate_audio_duration(clip, max_duration=30.0)
|
||||
mp3_bytes = audio_input_to_mp3(clip).getvalue()
|
||||
references.append(SeedAudioReference(audio_data=base64.b64encode(mp3_bytes).decode("utf-8")))
|
||||
elif mode == MODE_IMAGE:
|
||||
image = upscale_image_tensor_to_min_pixels(image, 160_000)
|
||||
references = [SeedAudioReference(image_data=tensor_to_base64_string(image, mime_type="image/png"))]
|
||||
elif mode == MODE_SPEAKER:
|
||||
references = [SeedAudioReference(speaker=SEED_AUDIO_VOICE_MAP[preset_voice])]
|
||||
|
||||
response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/byteplus/api/v3/tts/create", method="POST"),
|
||||
response_model=SeedAudioResponse,
|
||||
data=SeedAudioRequest(
|
||||
text_prompt=text_prompt,
|
||||
references=references,
|
||||
audio_config=SeedAudioConfig(
|
||||
sample_rate=int(sample_rate),
|
||||
speech_rate=speech_rate,
|
||||
loudness_rate=loudness_rate,
|
||||
pitch_rate=pitch_rate,
|
||||
),
|
||||
),
|
||||
)
|
||||
if not response.audio:
|
||||
raise Exception(
|
||||
f"Seed Audio returned no audio (code={response.code}): {response.message}"
|
||||
)
|
||||
return IO.NodeOutput(audio_bytes_to_audio_input(base64.b64decode(response.audio)))
|
||||
|
||||
|
||||
class ByteDanceExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
||||
@ -2490,6 +2805,7 @@ class ByteDanceExtension(ComfyExtension):
|
||||
ByteDance2ReferenceNode,
|
||||
ByteDanceCreateImageAsset,
|
||||
ByteDanceCreateVideoAsset,
|
||||
ByteDanceSeedAudioNode,
|
||||
]
|
||||
|
||||
|
||||
|
||||
@ -1,932 +0,0 @@
|
||||
from inspect import cleandoc
|
||||
from typing import Optional
|
||||
from typing_extensions import override
|
||||
|
||||
from comfy_api.latest import ComfyExtension, Input, IO
|
||||
from comfy_api_nodes.apis.stability import (
|
||||
StabilityUpscaleConservativeRequest,
|
||||
StabilityUpscaleCreativeRequest,
|
||||
StabilityAsyncResponse,
|
||||
StabilityResultsGetResponse,
|
||||
StabilityStable3_5Request,
|
||||
StabilityStableUltraRequest,
|
||||
StabilityStableUltraResponse,
|
||||
StabilityAspectRatio,
|
||||
Stability_SD3_5_Model,
|
||||
Stability_SD3_5_GenerationMode,
|
||||
get_stability_style_presets,
|
||||
StabilityTextToAudioRequest,
|
||||
StabilityAudioToAudioRequest,
|
||||
StabilityAudioInpaintRequest,
|
||||
StabilityAudioResponse,
|
||||
)
|
||||
from comfy_api_nodes.util import (
|
||||
validate_audio_duration,
|
||||
validate_string,
|
||||
audio_input_to_mp3,
|
||||
bytesio_to_image_tensor,
|
||||
tensor_to_bytesio,
|
||||
audio_bytes_to_audio_input,
|
||||
sync_op,
|
||||
poll_op,
|
||||
ApiEndpoint,
|
||||
)
|
||||
|
||||
import torch
|
||||
import base64
|
||||
from io import BytesIO
|
||||
from enum import Enum
|
||||
|
||||
|
||||
class StabilityPollStatus(str, Enum):
|
||||
finished = "finished"
|
||||
in_progress = "in_progress"
|
||||
failed = "failed"
|
||||
|
||||
|
||||
def get_async_dummy_status(x: StabilityResultsGetResponse):
|
||||
if x.name is not None or x.errors is not None:
|
||||
return StabilityPollStatus.failed
|
||||
elif x.finish_reason is not None:
|
||||
return StabilityPollStatus.finished
|
||||
return StabilityPollStatus.in_progress
|
||||
|
||||
|
||||
class StabilityStableImageUltraNode(IO.ComfyNode):
|
||||
"""
|
||||
Generates images synchronously based on prompt and resolution.
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="StabilityStableImageUltraNode",
|
||||
display_name="Stability AI Stable Image Ultra",
|
||||
category="partner/image/Stability AI",
|
||||
description=cleandoc(cls.__doc__ or ""),
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="What you wish to see in the output image. A strong, descriptive prompt that clearly defines" +
|
||||
"elements, colors, and subjects will lead to better results. " +
|
||||
"To control the weight of a given word use the format `(word:weight)`," +
|
||||
"where `word` is the word you'd like to control the weight of and `weight`" +
|
||||
"is a value between 0 and 1. For example: `The sky was a crisp (blue:0.3) and (green:0.8)`" +
|
||||
"would convey a sky that was blue and green, but more green than blue.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"aspect_ratio",
|
||||
options=StabilityAspectRatio,
|
||||
default=StabilityAspectRatio.ratio_1_1,
|
||||
tooltip="Aspect ratio of generated image.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"style_preset",
|
||||
options=get_stability_style_presets(),
|
||||
tooltip="Optional desired style of generated image.",
|
||||
advanced=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=4294967294,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="The random seed used for creating the noise.",
|
||||
),
|
||||
IO.Image.Input(
|
||||
"image",
|
||||
optional=True,
|
||||
),
|
||||
IO.String.Input(
|
||||
"negative_prompt",
|
||||
default="",
|
||||
tooltip="A blurb of text describing what you do not wish to see in the output image. This is an advanced feature.",
|
||||
force_input=True,
|
||||
optional=True,
|
||||
advanced=True,
|
||||
),
|
||||
IO.Float.Input(
|
||||
"image_denoise",
|
||||
default=0.5,
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
tooltip="Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all.",
|
||||
optional=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Image.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.08}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
prompt: str,
|
||||
aspect_ratio: str,
|
||||
style_preset: str,
|
||||
seed: int,
|
||||
image: Optional[torch.Tensor] = None,
|
||||
negative_prompt: str = "",
|
||||
image_denoise: Optional[float] = 0.5,
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, strip_whitespace=False)
|
||||
# prepare image binary if image present
|
||||
image_binary = None
|
||||
if image is not None:
|
||||
image_binary = tensor_to_bytesio(image, total_pixels=1504*1504).read()
|
||||
else:
|
||||
image_denoise = None
|
||||
|
||||
if not negative_prompt:
|
||||
negative_prompt = None
|
||||
if style_preset == "None":
|
||||
style_preset = None
|
||||
|
||||
files = {
|
||||
"image": image_binary
|
||||
}
|
||||
|
||||
response_api = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/stability/v2beta/stable-image/generate/ultra", method="POST"),
|
||||
response_model=StabilityStableUltraResponse,
|
||||
data=StabilityStableUltraRequest(
|
||||
prompt=prompt,
|
||||
negative_prompt=negative_prompt,
|
||||
aspect_ratio=aspect_ratio,
|
||||
seed=seed,
|
||||
strength=image_denoise,
|
||||
style_preset=style_preset,
|
||||
),
|
||||
files=files,
|
||||
content_type="multipart/form-data",
|
||||
)
|
||||
|
||||
if response_api.finish_reason != "SUCCESS":
|
||||
raise Exception(f"Stable Image Ultra generation failed: {response_api.finish_reason}.")
|
||||
|
||||
image_data = base64.b64decode(response_api.image)
|
||||
returned_image = bytesio_to_image_tensor(BytesIO(image_data))
|
||||
|
||||
return IO.NodeOutput(returned_image)
|
||||
|
||||
|
||||
class StabilityStableImageSD_3_5Node(IO.ComfyNode):
|
||||
"""
|
||||
Generates images synchronously based on prompt and resolution.
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="StabilityStableImageSD_3_5Node",
|
||||
display_name="Stability AI Stable Diffusion 3.5 Image",
|
||||
category="partner/image/Stability AI",
|
||||
description=cleandoc(cls.__doc__ or ""),
|
||||
inputs=[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"model",
|
||||
options=Stability_SD3_5_Model,
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"aspect_ratio",
|
||||
options=StabilityAspectRatio,
|
||||
default=StabilityAspectRatio.ratio_1_1,
|
||||
tooltip="Aspect ratio of generated image.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"style_preset",
|
||||
options=get_stability_style_presets(),
|
||||
tooltip="Optional desired style of generated image.",
|
||||
advanced=True,
|
||||
),
|
||||
IO.Float.Input(
|
||||
"cfg_scale",
|
||||
default=4.0,
|
||||
min=1.0,
|
||||
max=10.0,
|
||||
step=0.1,
|
||||
tooltip="How strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt)",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=4294967294,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="The random seed used for creating the noise.",
|
||||
),
|
||||
IO.Image.Input(
|
||||
"image",
|
||||
optional=True,
|
||||
),
|
||||
IO.String.Input(
|
||||
"negative_prompt",
|
||||
default="",
|
||||
tooltip="Keywords of what you do not wish to see in the output image. This is an advanced feature.",
|
||||
force_input=True,
|
||||
optional=True,
|
||||
advanced=True,
|
||||
),
|
||||
IO.Float.Input(
|
||||
"image_denoise",
|
||||
default=0.5,
|
||||
min=0.0,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
tooltip="Denoise of input image; 0.0 yields image identical to input, 1.0 is as if no image was provided at all.",
|
||||
optional=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Image.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model"]),
|
||||
expr="""
|
||||
(
|
||||
$contains(widgets.model,"large")
|
||||
? {"type":"usd","usd":0.065}
|
||||
: {"type":"usd","usd":0.035}
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
model: str,
|
||||
prompt: str,
|
||||
aspect_ratio: str,
|
||||
style_preset: str,
|
||||
seed: int,
|
||||
cfg_scale: float,
|
||||
image: Optional[torch.Tensor] = None,
|
||||
negative_prompt: str = "",
|
||||
image_denoise: Optional[float] = 0.5,
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, strip_whitespace=False)
|
||||
# prepare image binary if image present
|
||||
image_binary = None
|
||||
mode = Stability_SD3_5_GenerationMode.text_to_image
|
||||
if image is not None:
|
||||
image_binary = tensor_to_bytesio(image, total_pixels=1504*1504).read()
|
||||
mode = Stability_SD3_5_GenerationMode.image_to_image
|
||||
aspect_ratio = None
|
||||
else:
|
||||
image_denoise = None
|
||||
|
||||
if not negative_prompt:
|
||||
negative_prompt = None
|
||||
if style_preset == "None":
|
||||
style_preset = None
|
||||
|
||||
files = {
|
||||
"image": image_binary
|
||||
}
|
||||
|
||||
response_api = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/stability/v2beta/stable-image/generate/sd3", method="POST"),
|
||||
response_model=StabilityStableUltraResponse,
|
||||
data=StabilityStable3_5Request(
|
||||
prompt=prompt,
|
||||
negative_prompt=negative_prompt,
|
||||
aspect_ratio=aspect_ratio,
|
||||
seed=seed,
|
||||
strength=image_denoise,
|
||||
style_preset=style_preset,
|
||||
cfg_scale=cfg_scale,
|
||||
model=model,
|
||||
mode=mode,
|
||||
),
|
||||
files=files,
|
||||
content_type="multipart/form-data",
|
||||
)
|
||||
|
||||
if response_api.finish_reason != "SUCCESS":
|
||||
raise Exception(f"Stable Diffusion 3.5 Image generation failed: {response_api.finish_reason}.")
|
||||
|
||||
image_data = base64.b64decode(response_api.image)
|
||||
returned_image = bytesio_to_image_tensor(BytesIO(image_data))
|
||||
|
||||
return IO.NodeOutput(returned_image)
|
||||
|
||||
|
||||
class StabilityUpscaleConservativeNode(IO.ComfyNode):
|
||||
"""
|
||||
Upscale image with minimal alterations to 4K resolution.
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="StabilityUpscaleConservativeNode",
|
||||
display_name="Stability AI Upscale Conservative",
|
||||
category="partner/image/Stability AI",
|
||||
description=cleandoc(cls.__doc__ or ""),
|
||||
inputs=[
|
||||
IO.Image.Input("image"),
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"creativity",
|
||||
default=0.35,
|
||||
min=0.2,
|
||||
max=0.5,
|
||||
step=0.01,
|
||||
tooltip="Controls the likelihood of creating additional details not heavily conditioned by the init image.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=4294967294,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="The random seed used for creating the noise.",
|
||||
),
|
||||
IO.String.Input(
|
||||
"negative_prompt",
|
||||
default="",
|
||||
tooltip="Keywords of what you do not wish to see in the output image. This is an advanced feature.",
|
||||
force_input=True,
|
||||
optional=True,
|
||||
advanced=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Image.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.4}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
image: torch.Tensor,
|
||||
prompt: str,
|
||||
creativity: float,
|
||||
seed: int,
|
||||
negative_prompt: str = "",
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, strip_whitespace=False)
|
||||
image_binary = tensor_to_bytesio(image, total_pixels=1024*1024).read()
|
||||
|
||||
if not negative_prompt:
|
||||
negative_prompt = None
|
||||
|
||||
files = {
|
||||
"image": image_binary
|
||||
}
|
||||
|
||||
response_api = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/stability/v2beta/stable-image/upscale/conservative", method="POST"),
|
||||
response_model=StabilityStableUltraResponse,
|
||||
data=StabilityUpscaleConservativeRequest(
|
||||
prompt=prompt,
|
||||
negative_prompt=negative_prompt,
|
||||
creativity=round(creativity,2),
|
||||
seed=seed,
|
||||
),
|
||||
files=files,
|
||||
content_type="multipart/form-data",
|
||||
)
|
||||
|
||||
if response_api.finish_reason != "SUCCESS":
|
||||
raise Exception(f"Stability Upscale Conservative generation failed: {response_api.finish_reason}.")
|
||||
|
||||
image_data = base64.b64decode(response_api.image)
|
||||
returned_image = bytesio_to_image_tensor(BytesIO(image_data))
|
||||
|
||||
return IO.NodeOutput(returned_image)
|
||||
|
||||
|
||||
class StabilityUpscaleCreativeNode(IO.ComfyNode):
|
||||
"""
|
||||
Upscale image with minimal alterations to 4K resolution.
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="StabilityUpscaleCreativeNode",
|
||||
display_name="Stability AI Upscale Creative",
|
||||
category="partner/image/Stability AI",
|
||||
description=cleandoc(cls.__doc__ or ""),
|
||||
inputs=[
|
||||
IO.Image.Input("image"),
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="What you wish to see in the output image. A strong, descriptive prompt that clearly defines elements, colors, and subjects will lead to better results.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"creativity",
|
||||
default=0.3,
|
||||
min=0.1,
|
||||
max=0.5,
|
||||
step=0.01,
|
||||
tooltip="Controls the likelihood of creating additional details not heavily conditioned by the init image.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"style_preset",
|
||||
options=get_stability_style_presets(),
|
||||
tooltip="Optional desired style of generated image.",
|
||||
advanced=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=4294967294,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="The random seed used for creating the noise.",
|
||||
),
|
||||
IO.String.Input(
|
||||
"negative_prompt",
|
||||
default="",
|
||||
tooltip="Keywords of what you do not wish to see in the output image. This is an advanced feature.",
|
||||
force_input=True,
|
||||
optional=True,
|
||||
advanced=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Image.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.6}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
image: torch.Tensor,
|
||||
prompt: str,
|
||||
creativity: float,
|
||||
style_preset: str,
|
||||
seed: int,
|
||||
negative_prompt: str = "",
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, strip_whitespace=False)
|
||||
image_binary = tensor_to_bytesio(image, total_pixels=1024*1024).read()
|
||||
|
||||
if not negative_prompt:
|
||||
negative_prompt = None
|
||||
if style_preset == "None":
|
||||
style_preset = None
|
||||
|
||||
files = {
|
||||
"image": image_binary
|
||||
}
|
||||
|
||||
response_api = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/stability/v2beta/stable-image/upscale/creative", method="POST"),
|
||||
response_model=StabilityAsyncResponse,
|
||||
data=StabilityUpscaleCreativeRequest(
|
||||
prompt=prompt,
|
||||
negative_prompt=negative_prompt,
|
||||
creativity=round(creativity,2),
|
||||
style_preset=style_preset,
|
||||
seed=seed,
|
||||
),
|
||||
files=files,
|
||||
content_type="multipart/form-data",
|
||||
)
|
||||
|
||||
response_poll = await poll_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/stability/v2beta/results/{response_api.id}"),
|
||||
response_model=StabilityResultsGetResponse,
|
||||
poll_interval=3,
|
||||
status_extractor=lambda x: get_async_dummy_status(x),
|
||||
)
|
||||
|
||||
if response_poll.finish_reason != "SUCCESS":
|
||||
raise Exception(f"Stability Upscale Creative generation failed: {response_poll.finish_reason}.")
|
||||
|
||||
image_data = base64.b64decode(response_poll.result)
|
||||
returned_image = bytesio_to_image_tensor(BytesIO(image_data))
|
||||
|
||||
return IO.NodeOutput(returned_image)
|
||||
|
||||
|
||||
class StabilityUpscaleFastNode(IO.ComfyNode):
|
||||
"""
|
||||
Quickly upscales an image via Stability API call to 4x its original size; intended for upscaling low-quality/compressed images.
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="StabilityUpscaleFastNode",
|
||||
display_name="Stability AI Upscale Fast",
|
||||
category="partner/image/Stability AI",
|
||||
description=cleandoc(cls.__doc__ or ""),
|
||||
inputs=[
|
||||
IO.Image.Input("image"),
|
||||
],
|
||||
outputs=[
|
||||
IO.Image.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.02}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(cls, image: torch.Tensor) -> IO.NodeOutput:
|
||||
image_binary = tensor_to_bytesio(image, total_pixels=4096*4096).read()
|
||||
|
||||
files = {
|
||||
"image": image_binary
|
||||
}
|
||||
|
||||
response_api = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/stability/v2beta/stable-image/upscale/fast", method="POST"),
|
||||
response_model=StabilityStableUltraResponse,
|
||||
files=files,
|
||||
content_type="multipart/form-data",
|
||||
)
|
||||
|
||||
if response_api.finish_reason != "SUCCESS":
|
||||
raise Exception(f"Stability Upscale Fast failed: {response_api.finish_reason}.")
|
||||
|
||||
image_data = base64.b64decode(response_api.image)
|
||||
returned_image = bytesio_to_image_tensor(BytesIO(image_data))
|
||||
|
||||
return IO.NodeOutput(returned_image)
|
||||
|
||||
|
||||
class StabilityTextToAudio(IO.ComfyNode):
|
||||
"""Generates high-quality music and sound effects from text descriptions."""
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="StabilityTextToAudio",
|
||||
display_name="Stability AI Text To Audio",
|
||||
category="partner/audio/Stability AI",
|
||||
essentials_category="Audio",
|
||||
description=cleandoc(cls.__doc__ or ""),
|
||||
inputs=[
|
||||
IO.Combo.Input(
|
||||
"model",
|
||||
options=["stable-audio-2.5"],
|
||||
),
|
||||
IO.String.Input("prompt", multiline=True, default=""),
|
||||
IO.Int.Input(
|
||||
"duration",
|
||||
default=190,
|
||||
min=1,
|
||||
max=190,
|
||||
step=1,
|
||||
tooltip="Controls the duration in seconds of the generated audio.",
|
||||
optional=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=4294967294,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="The random seed used for generation.",
|
||||
optional=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"steps",
|
||||
default=8,
|
||||
min=4,
|
||||
max=8,
|
||||
step=1,
|
||||
tooltip="Controls the number of sampling steps.",
|
||||
optional=True,
|
||||
advanced=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Audio.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.2}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(cls, model: str, prompt: str, duration: int, seed: int, steps: int) -> IO.NodeOutput:
|
||||
validate_string(prompt, max_length=10000)
|
||||
payload = StabilityTextToAudioRequest(prompt=prompt, model=model, duration=duration, seed=seed, steps=steps)
|
||||
response_api = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/stability/v2beta/audio/stable-audio-2/text-to-audio", method="POST"),
|
||||
response_model=StabilityAudioResponse,
|
||||
data=payload,
|
||||
content_type="multipart/form-data",
|
||||
)
|
||||
if not response_api.audio:
|
||||
raise ValueError("No audio file was received in response.")
|
||||
return IO.NodeOutput(audio_bytes_to_audio_input(base64.b64decode(response_api.audio)))
|
||||
|
||||
|
||||
class StabilityAudioToAudio(IO.ComfyNode):
|
||||
"""Transforms existing audio samples into new high-quality compositions using text instructions."""
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="StabilityAudioToAudio",
|
||||
display_name="Stability AI Audio To Audio",
|
||||
category="partner/audio/Stability AI",
|
||||
description=cleandoc(cls.__doc__ or ""),
|
||||
inputs=[
|
||||
IO.Combo.Input(
|
||||
"model",
|
||||
options=["stable-audio-2.5"],
|
||||
),
|
||||
IO.String.Input("prompt", multiline=True, default=""),
|
||||
IO.Audio.Input("audio", tooltip="Audio must be between 6 and 190 seconds long."),
|
||||
IO.Int.Input(
|
||||
"duration",
|
||||
default=190,
|
||||
min=1,
|
||||
max=190,
|
||||
step=1,
|
||||
tooltip="Controls the duration in seconds of the generated audio.",
|
||||
optional=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=4294967294,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="The random seed used for generation.",
|
||||
optional=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"steps",
|
||||
default=8,
|
||||
min=4,
|
||||
max=8,
|
||||
step=1,
|
||||
tooltip="Controls the number of sampling steps.",
|
||||
optional=True,
|
||||
advanced=True,
|
||||
),
|
||||
IO.Float.Input(
|
||||
"strength",
|
||||
default=1,
|
||||
min=0.01,
|
||||
max=1.0,
|
||||
step=0.01,
|
||||
display_mode=IO.NumberDisplay.slider,
|
||||
tooltip="Parameter controls how much influence the audio parameter has on the generated audio.",
|
||||
optional=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Audio.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.2}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls, model: str, prompt: str, audio: Input.Audio, duration: int, seed: int, steps: int, strength: float
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, max_length=10000)
|
||||
validate_audio_duration(audio, 6, 190)
|
||||
payload = StabilityAudioToAudioRequest(
|
||||
prompt=prompt, model=model, duration=duration, seed=seed, steps=steps, strength=strength
|
||||
)
|
||||
response_api = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path="/proxy/stability/v2beta/audio/stable-audio-2/audio-to-audio", method="POST"),
|
||||
response_model=StabilityAudioResponse,
|
||||
data=payload,
|
||||
content_type="multipart/form-data",
|
||||
files={"audio": audio_input_to_mp3(audio)},
|
||||
)
|
||||
if not response_api.audio:
|
||||
raise ValueError("No audio file was received in response.")
|
||||
return IO.NodeOutput(audio_bytes_to_audio_input(base64.b64decode(response_api.audio)))
|
||||
|
||||
|
||||
class StabilityAudioInpaint(IO.ComfyNode):
|
||||
"""Transforms part of existing audio sample using text instructions."""
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="StabilityAudioInpaint",
|
||||
display_name="Stability AI Audio Inpaint",
|
||||
category="partner/audio/Stability AI",
|
||||
description=cleandoc(cls.__doc__ or ""),
|
||||
inputs=[
|
||||
IO.Combo.Input(
|
||||
"model",
|
||||
options=["stable-audio-2.5"],
|
||||
),
|
||||
IO.String.Input("prompt", multiline=True, default=""),
|
||||
IO.Audio.Input("audio", tooltip="Audio must be between 6 and 190 seconds long."),
|
||||
IO.Int.Input(
|
||||
"duration",
|
||||
default=190,
|
||||
min=1,
|
||||
max=190,
|
||||
step=1,
|
||||
tooltip="Controls the duration in seconds of the generated audio.",
|
||||
optional=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=4294967294,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="The random seed used for generation.",
|
||||
optional=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"steps",
|
||||
default=8,
|
||||
min=4,
|
||||
max=8,
|
||||
step=1,
|
||||
tooltip="Controls the number of sampling steps.",
|
||||
optional=True,
|
||||
advanced=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"mask_start",
|
||||
default=30,
|
||||
min=0,
|
||||
max=190,
|
||||
step=1,
|
||||
optional=True,
|
||||
advanced=True,
|
||||
),
|
||||
IO.Int.Input(
|
||||
"mask_end",
|
||||
default=190,
|
||||
min=0,
|
||||
max=190,
|
||||
step=1,
|
||||
optional=True,
|
||||
advanced=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Audio.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
expr="""{"type":"usd","usd":0.2}""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
model: str,
|
||||
prompt: str,
|
||||
audio: Input.Audio,
|
||||
duration: int,
|
||||
seed: int,
|
||||
steps: int,
|
||||
mask_start: int,
|
||||
mask_end: int,
|
||||
) -> IO.NodeOutput:
|
||||
validate_string(prompt, max_length=10000)
|
||||
if mask_end <= mask_start:
|
||||
raise ValueError(f"Value of mask_end({mask_end}) should be greater then mask_start({mask_start})")
|
||||
validate_audio_duration(audio, 6, 190)
|
||||
|
||||
payload = StabilityAudioInpaintRequest(
|
||||
prompt=prompt,
|
||||
model=model,
|
||||
duration=duration,
|
||||
seed=seed,
|
||||
steps=steps,
|
||||
mask_start=mask_start,
|
||||
mask_end=mask_end,
|
||||
)
|
||||
response_api = await sync_op(
|
||||
cls,
|
||||
endpoint=ApiEndpoint(path="/proxy/stability/v2beta/audio/stable-audio-2/inpaint", method="POST"),
|
||||
response_model=StabilityAudioResponse,
|
||||
data=payload,
|
||||
content_type="multipart/form-data",
|
||||
files={"audio": audio_input_to_mp3(audio)},
|
||||
)
|
||||
if not response_api.audio:
|
||||
raise ValueError("No audio file was received in response.")
|
||||
return IO.NodeOutput(audio_bytes_to_audio_input(base64.b64decode(response_api.audio)))
|
||||
|
||||
|
||||
class StabilityExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
||||
return [
|
||||
StabilityStableImageUltraNode,
|
||||
StabilityStableImageSD_3_5Node,
|
||||
StabilityUpscaleConservativeNode,
|
||||
StabilityUpscaleCreativeNode,
|
||||
StabilityUpscaleFastNode,
|
||||
StabilityTextToAudio,
|
||||
StabilityAudioToAudio,
|
||||
StabilityAudioInpaint,
|
||||
]
|
||||
|
||||
|
||||
async def comfy_entrypoint() -> StabilityExtension:
|
||||
return StabilityExtension()
|
||||
@ -26,6 +26,7 @@ from .conversions import (
|
||||
text_filepath_to_base64_string,
|
||||
text_filepath_to_data_uri,
|
||||
trim_video,
|
||||
upscale_image_tensor_to_min_pixels,
|
||||
upscale_video_to_min_pixels,
|
||||
video_to_base64_string,
|
||||
)
|
||||
@ -99,6 +100,7 @@ __all__ = [
|
||||
"text_filepath_to_base64_string",
|
||||
"text_filepath_to_data_uri",
|
||||
"trim_video",
|
||||
"upscale_image_tensor_to_min_pixels",
|
||||
"upscale_video_to_min_pixels",
|
||||
"video_to_base64_string",
|
||||
# Validation utilities
|
||||
|
||||
@ -448,6 +448,15 @@ def _compute_upscale_dims(src_w: int, src_h: int, total_pixels: int) -> tuple[in
|
||||
return new_w, new_h
|
||||
|
||||
|
||||
def upscale_image_tensor_to_min_pixels(image: torch.Tensor, total_pixels: int) -> torch.Tensor:
|
||||
samples = image.movedim(-1, 1)
|
||||
dims = _compute_upscale_dims(samples.shape[3], samples.shape[2], int(total_pixels))
|
||||
if dims is None:
|
||||
return image
|
||||
new_w, new_h = dims
|
||||
return common_upscale(samples, new_w, new_h, "lanczos", "disabled").movedim(1, -1)
|
||||
|
||||
|
||||
def upscale_video_to_min_pixels(video: Input.Video, min_pixels: int) -> Input.Video:
|
||||
"""Upscale a video to meet at least ``min_pixels`` (w * h), preserving aspect ratio.
|
||||
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
comfyui-frontend-package==1.45.20
|
||||
comfyui-workflow-templates==0.11.1
|
||||
comfyui-workflow-templates==0.11.2
|
||||
comfyui-embedded-docs==0.5.6
|
||||
torch
|
||||
torchsde
|
||||
|
||||
Loading…
Reference in New Issue
Block a user