mirror of
https://github.com/rookiestar28/ComfyUI-OpenClaw.git
synced 2026-08-14 08:52:45 +00:00
139 lines
4.9 KiB
Python
139 lines
4.9 KiB
Python
import json
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import logging
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import random
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from typing import Any, Dict, List, Tuple
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try:
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from ..models.schemas import GenerationParams
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except ImportError:
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from models.schemas import GenerationParams
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try:
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from ..services.metrics import metrics
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except ImportError:
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from services.metrics import metrics
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logger = logging.getLogger("ComfyUI-OpenClaw.nodes.BatchVariants")
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class OpenClawBatchVariants:
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"""
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Generates deterministic variants for batch processing.
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"""
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"positive": ("STRING", {"multiline": True}),
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"negative": ("STRING", {"multiline": True}),
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"count": ("INT", {"default": 4, "min": 1, "max": 100}),
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"seed_base": (
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"INT",
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{"default": 0, "min": 0, "max": 0xFFFFFFFFFFFFFFFF},
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),
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"seed_policy": (
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["fixed", "increment", "randomized"],
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{"default": "increment"},
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),
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"variant_policy": (
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["none", "cfg_sweep", "steps_sweep", "size_sweep"],
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{"default": "none"},
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),
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},
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"optional": {
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"params_json": ("STRING", {"multiline": True, "default": "{}"}),
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"sweep_start": ("FLOAT", {"default": 0.0, "step": 0.1}),
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"sweep_end": ("FLOAT", {"default": 0.0, "step": 0.1}),
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},
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}
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RETURN_TYPES = ("STRING", "STRING", "STRING")
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RETURN_NAMES = ("positive_list", "negative_list", "params_json_list")
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OUTPUT_IS_LIST = (True, True, True)
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FUNCTION = "generate_variants"
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CATEGORY = "openclaw"
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def generate_variants(
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self,
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positive: str,
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negative: str,
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count: int,
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seed_base: int,
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seed_policy: str,
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variant_policy: str,
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params_json: str = "{}",
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sweep_start: float = 0.0,
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sweep_end: float = 0.0,
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) -> Tuple[List[str], List[str], List[str]]:
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metrics.increment("variants_calls")
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# 1. Parse Baseline Params
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try:
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base_dict = json.loads(params_json) if params_json.strip() else {}
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except json.JSONDecodeError:
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logger.warning("Invalid JSON in params_json, using empty dict.")
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base_dict = {}
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pos_list = []
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neg_list = []
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params_list = []
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for i in range(count):
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# 2. Calculate Seed
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current_seed = seed_base
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if seed_policy == "increment":
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current_seed = seed_base + i
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elif seed_policy == "randomized":
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# Deterministic pseudo-random based on base+i
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# Using a simple LCG or hash for stability without numpy
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# seed = hash(f"{seed_base}_{i}") & 0xffffffffffffffff
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# But simple increment is usually what users want for "variations"
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# Let's stick to simple increment for now or random python if implied?
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# "randomized" usually means unpredictable.
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# Let's implement a simple hash for now to be deterministic but "jumpy"
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r = random.Random(seed_base + i)
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current_seed = r.randint(0, 0xFFFFFFFFFFFFFFFF)
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# 3. Apply Variant Policy (Sweep)
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# Create a fresh copy of base dict
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current_params = base_dict.copy()
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current_params["seed"] = current_seed
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if variant_policy != "none" and count > 1:
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# Interpolation factor (0.0 to 1.0)
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t = i / (count - 1)
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value = sweep_start + (sweep_end - sweep_start) * t
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if variant_policy == "cfg_sweep":
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current_params["cfg"] = value
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elif variant_policy == "steps_sweep":
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current_params["steps"] = int(round(value))
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elif variant_policy == "size_sweep":
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# Assume value is the target "size" (width/height)
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# We override both width and height to be square or keep aspect ratio?
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# MVP: Set both width and height to the int(value)
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# Use with caution
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s = int(round(value))
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current_params["width"] = s
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current_params["height"] = s
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# 4. Validate & Clamp
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# Using GenerationParams.from_dict to enforce schema constraints
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validated = GenerationParams.from_dict(current_params)
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# 5. Append
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pos_list.append(positive)
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neg_list.append(negative)
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params_list.append(json.dumps(validated.dict(), indent=2))
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return (pos_list, neg_list, params_list)
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# IMPORTANT: keep legacy class alias for existing imports and tests.
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MoltbotBatchVariants = OpenClawBatchVariants
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