Merge remote-tracking branch 'origin/main' into feature-Pruna-p-video
This commit is contained in:
Sirshendu Ganguly
@@ -225,7 +225,23 @@ class txt2img:
|
||||
def VALIDATE_INPUTS(cls, **kwargs):
|
||||
positivePrompt = kwargs.get("positivePrompt", "")
|
||||
negativePrompt = kwargs.get("negativePrompt", "")
|
||||
|
||||
settings = kwargs.get("settings")
|
||||
|
||||
structured_prompt = None
|
||||
if isinstance(settings, dict):
|
||||
structured_prompt = settings.get("structuredPrompt")
|
||||
has_structured_prompt = (
|
||||
isinstance(structured_prompt, dict) and len(structured_prompt) > 0
|
||||
)
|
||||
has_positive_prompt = bool(
|
||||
positivePrompt is not None and str(positivePrompt) != ""
|
||||
)
|
||||
if has_structured_prompt and has_positive_prompt:
|
||||
return (
|
||||
"settings.structuredPrompt and positivePrompt are mutually exclusive. "
|
||||
"Clear positivePrompt or disconnect Structured Prompt from Settings."
|
||||
)
|
||||
|
||||
# Only validate positivePrompt length if it's provided
|
||||
if positivePrompt and len(positivePrompt) > 10000:
|
||||
return "Positive Prompt is too long. Maximum length is 10000 characters."
|
||||
|
||||
@@ -0,0 +1,216 @@
|
||||
"""
|
||||
Runware Image Inference Settings Structured Prompt
|
||||
Builds settings.structuredPrompt for Ideogram 4.0 and compatible models.
|
||||
Connect the output to Runware Image Inference Settings → structuredPrompt.
|
||||
Mutually exclusive with positivePrompt at the API level.
|
||||
"""
|
||||
|
||||
import json
|
||||
from typing import Any, Dict, List, Tuple
|
||||
|
||||
|
||||
class RunwareImageInferenceSettingsStructuredPrompt:
|
||||
"""Ideogram-style structured JSON prompt for image inference settings."""
|
||||
|
||||
_ELEMENT_SLOTS = 8
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
optional: Dict[str, tuple] = {
|
||||
"background": ("STRING", {
|
||||
"multiline": True,
|
||||
"default": "",
|
||||
"tooltip": "compositional_deconstruction.background — setting/surface/atmosphere, not discrete subjects.",
|
||||
}),
|
||||
"useStyleDescription": ("BOOLEAN", {
|
||||
"default": False,
|
||||
"label_on": "Enabled",
|
||||
"label_off": "Disabled",
|
||||
"tooltip": "Include style_description from JSON below.",
|
||||
}),
|
||||
"style_description": ("STRING", {
|
||||
"multiline": True,
|
||||
"default": "",
|
||||
"tooltip": "style_description object as JSON (aesthetics, lighting, photo OR art_style, medium, color_palette). Only when 'Use Style Description' is enabled.",
|
||||
}),
|
||||
"useElementsJson": ("BOOLEAN", {
|
||||
"default": False,
|
||||
"label_on": "Enabled",
|
||||
"label_off": "Disabled",
|
||||
"tooltip": "Set elements from a JSON array instead of element slots 1–8.",
|
||||
}),
|
||||
"elementsJson": ("STRING", {
|
||||
"multiline": True,
|
||||
"default": "",
|
||||
"tooltip": "JSON array of element objects ({type, desc, text?, bbox?, color_palette?}). Only when 'Use Elements JSON' is enabled.",
|
||||
}),
|
||||
}
|
||||
|
||||
for i in range(1, cls._ELEMENT_SLOTS + 1):
|
||||
optional[f"use_element_{i}"] = ("BOOLEAN", {
|
||||
"default": False,
|
||||
"label_on": "Enabled",
|
||||
"label_off": "Disabled",
|
||||
"tooltip": f"Include element slot {i} in compositional_deconstruction.elements.",
|
||||
})
|
||||
optional[f"element_type_{i}"] = (["obj", "text"], {
|
||||
"default": "obj",
|
||||
"tooltip": f"Element {i} type: obj (desc interpreted) or text (text rendered literally).",
|
||||
})
|
||||
optional[f"element_desc_{i}"] = ("STRING", {
|
||||
"multiline": True,
|
||||
"default": "",
|
||||
"tooltip": f"Element {i} desc — natural language treatment/position notes.",
|
||||
})
|
||||
optional[f"element_text_{i}"] = ("STRING", {
|
||||
"multiline": True,
|
||||
"default": "",
|
||||
"tooltip": f"Element {i} text — literal copy for type text only.",
|
||||
})
|
||||
optional[f"element_bbox_{i}"] = ("STRING", {
|
||||
"default": "",
|
||||
"tooltip": f"Element {i} optional bbox JSON: [y_min, x_min, y_max, x_max] in 0–1000 coords.",
|
||||
})
|
||||
optional[f"element_color_palette_{i}"] = ("STRING", {
|
||||
"default": "",
|
||||
"tooltip": f"Element {i} optional hex colours, comma-separated (e.g. #1F3B26,#7A5A2F).",
|
||||
})
|
||||
|
||||
required = {
|
||||
"high_level_description": ("STRING", {
|
||||
"multiline": True,
|
||||
"default": "",
|
||||
"tooltip": "Global scene summary (required).",
|
||||
}),
|
||||
}
|
||||
return {"required": required, "optional": optional}
|
||||
|
||||
RETURN_TYPES = ("RUNWAREIMAGEINFERENCESTRUCTUREDPROMPT",)
|
||||
RETURN_NAMES = ("structuredPrompt",)
|
||||
FUNCTION = "build_structured_prompt"
|
||||
CATEGORY = "Runware"
|
||||
DESCRIPTION = (
|
||||
"Build settings.structuredPrompt for Ideogram 4.0 (snake_case schema) from "
|
||||
"high_level_description, background, style_description, and elements. "
|
||||
"Connect to Runware Image Inference Settings. Do not send positivePrompt in the same request."
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _parse_json_object(raw: str, field_name: str) -> Dict[str, Any]:
|
||||
text = (raw or "").strip()
|
||||
if not text:
|
||||
raise ValueError(f"{field_name} is empty.")
|
||||
try:
|
||||
parsed = json.loads(text)
|
||||
except json.JSONDecodeError as e:
|
||||
raise ValueError(f"{field_name} must be valid JSON: {e}") from e
|
||||
if not isinstance(parsed, dict):
|
||||
raise ValueError(f"{field_name} must be a JSON object.")
|
||||
return parsed
|
||||
|
||||
@staticmethod
|
||||
def _parse_json_array(raw: str, field_name: str) -> List[Any]:
|
||||
text = (raw or "").strip()
|
||||
if not text:
|
||||
raise ValueError(f"{field_name} is empty.")
|
||||
try:
|
||||
parsed = json.loads(text)
|
||||
except json.JSONDecodeError as e:
|
||||
raise ValueError(f"{field_name} must be valid JSON: {e}") from e
|
||||
if not isinstance(parsed, list):
|
||||
raise ValueError(f"{field_name} must be a JSON array.")
|
||||
return parsed
|
||||
|
||||
@classmethod
|
||||
def _build_element_from_slot(cls, kwargs: Dict[str, Any], index: int) -> Dict[str, Any]:
|
||||
el_type = str(kwargs.get(f"element_type_{index}", "obj")).strip() or "obj"
|
||||
if el_type not in ("obj", "text"):
|
||||
raise ValueError(f"element_type_{index} must be obj or text.")
|
||||
|
||||
element: Dict[str, Any] = {"type": el_type}
|
||||
|
||||
desc = str(kwargs.get(f"element_desc_{index}") or "").strip()
|
||||
if desc:
|
||||
element["desc"] = desc
|
||||
|
||||
if el_type == "text":
|
||||
text = str(kwargs.get(f"element_text_{index}") or "").strip()
|
||||
if text:
|
||||
element["text"] = text
|
||||
|
||||
bbox_raw = str(kwargs.get(f"element_bbox_{index}") or "").strip()
|
||||
if bbox_raw:
|
||||
try:
|
||||
bbox = json.loads(bbox_raw)
|
||||
except json.JSONDecodeError as e:
|
||||
raise ValueError(f"element_bbox_{index} must be valid JSON: {e}") from e
|
||||
if not isinstance(bbox, list):
|
||||
raise ValueError(f"element_bbox_{index} must be a JSON array.")
|
||||
element["bbox"] = bbox
|
||||
|
||||
palette_raw = str(kwargs.get(f"element_color_palette_{index}") or "").strip()
|
||||
if palette_raw:
|
||||
palette = [h.strip() for h in palette_raw.split(",") if h.strip()]
|
||||
if palette:
|
||||
element["color_palette"] = palette
|
||||
|
||||
if el_type == "text" and "text" not in element and not desc:
|
||||
raise ValueError(
|
||||
f"Element slot {index}: type text requires element_text_{index} or element_desc_{index}."
|
||||
)
|
||||
if el_type == "obj" and not desc:
|
||||
raise ValueError(f"Element slot {index}: type obj requires element_desc_{index}.")
|
||||
|
||||
return element
|
||||
|
||||
@classmethod
|
||||
def _collect_elements(cls, kwargs: Dict[str, Any]) -> List[Dict[str, Any]]:
|
||||
if kwargs.get("useElementsJson", False):
|
||||
return cls._parse_json_array(
|
||||
kwargs.get("elementsJson", ""),
|
||||
"elementsJson",
|
||||
)
|
||||
|
||||
elements: List[Dict[str, Any]] = []
|
||||
for i in range(1, cls._ELEMENT_SLOTS + 1):
|
||||
if not kwargs.get(f"use_element_{i}", False):
|
||||
continue
|
||||
elements.append(cls._build_element_from_slot(kwargs, i))
|
||||
return elements
|
||||
|
||||
def build_structured_prompt(self, **kwargs) -> Tuple[Dict[str, Any]]:
|
||||
hld = str(kwargs.get("high_level_description") or "").strip()
|
||||
if not hld:
|
||||
raise ValueError("high_level_description is required.")
|
||||
|
||||
structured: Dict[str, Any] = {"high_level_description": hld}
|
||||
|
||||
if kwargs.get("useStyleDescription", False):
|
||||
style_raw = kwargs.get("style_description", "")
|
||||
structured["style_description"] = self._parse_json_object(
|
||||
style_raw,
|
||||
"style_description",
|
||||
)
|
||||
|
||||
comp: Dict[str, Any] = {}
|
||||
background = str(kwargs.get("background") or "").strip()
|
||||
if background:
|
||||
comp["background"] = background
|
||||
|
||||
elements = self._collect_elements(kwargs)
|
||||
if elements:
|
||||
comp["elements"] = elements
|
||||
|
||||
if comp:
|
||||
structured["compositional_deconstruction"] = comp
|
||||
|
||||
return (structured,)
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"RunwareImageInferenceSettingsStructuredPrompt": RunwareImageInferenceSettingsStructuredPrompt,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"RunwareImageInferenceSettingsStructuredPrompt": "Runware Image Inference Settings Structured Prompt",
|
||||
}
|
||||
+14
-3
@@ -4,8 +4,8 @@ Provides settings for image generation including temperature, systemPrompt, topP
|
||||
quality, background, style, search, promptExtend, editRegions, thinking (boolean),
|
||||
thinkingLevel (high/medium/low), sequential, renderingSpeed (TURBO/DEFAULT/QUALITY),
|
||||
magicPrompt (AUTO/ON/OFF), autoCrop, dilatePixels, creativity (raw/low/medium/high), colorPalette,
|
||||
and moodboards
|
||||
(from Runware Image Inference Settings Color Palette).
|
||||
moodboards (from Runware Image Inference Settings Moodboards),
|
||||
and structuredPrompt (from Runware Image Inference Settings Structured Prompt; Ideogram 4.0).
|
||||
"""
|
||||
|
||||
import json
|
||||
@@ -205,6 +205,9 @@ class RunwareSettings:
|
||||
"moodboards": ("RUNWAREIMAGEINFERENCEMOODBOARDS", {
|
||||
"tooltip": "Connect Runware Image Inference Settings Moodboards. When connected with at least one entry, it is merged into settings.moodboards.",
|
||||
}),
|
||||
"structuredPrompt": ("RUNWAREIMAGEINFERENCESTRUCTUREDPROMPT", {
|
||||
"tooltip": "Connect Runware Image Inference Settings Structured Prompt (Ideogram 4.0). Merged into settings.structuredPrompt. Mutually exclusive with positivePrompt on the same API request.",
|
||||
}),
|
||||
}
|
||||
}
|
||||
|
||||
@@ -216,7 +219,7 @@ class RunwareSettings:
|
||||
"Configure general settings for image generation: temperature, system prompt, top-p, layers, quality, background, style, search, "
|
||||
"promptExtend, editRegions (JSON), thinking (boolean), thinkingLevel (high/medium/low), sequential, "
|
||||
"renderingSpeed (TURBO/DEFAULT/QUALITY), magicPrompt (AUTO/ON/OFF), autoCrop, dilatePixels, "
|
||||
"creativity (raw/low/medium/high), and optional colorPalette and moodboards from dedicated settings nodes."
|
||||
"creativity (raw/low/medium/high), and optional colorPalette, moodboards, and structuredPrompt from dedicated settings nodes."
|
||||
)
|
||||
|
||||
def createSettings(self, **kwargs) -> tuple[Dict[str, Any]]:
|
||||
@@ -309,6 +312,14 @@ class RunwareSettings:
|
||||
if moodboards is not None and isinstance(moodboards, list) and len(moodboards) > 0:
|
||||
settings["moodboards"] = moodboards
|
||||
|
||||
structured_prompt: Optional[Dict[str, Any]] = kwargs.get("structuredPrompt")
|
||||
if (
|
||||
structured_prompt is not None
|
||||
and isinstance(structured_prompt, dict)
|
||||
and len(structured_prompt) > 0
|
||||
):
|
||||
settings["structuredPrompt"] = structured_prompt
|
||||
|
||||
if useRenderingSpeed:
|
||||
settings["renderingSpeed"] = str(renderingSpeed)
|
||||
if useMagicPrompt:
|
||||
|
||||
Reference in New Issue
Block a user