feat: add Metadata Overwrite node for manual generation params override

__init__.py

@@ -18,6 +18,7 @@ try:  # pragma: no cover - import fallback for pytest collection
     from .py.nodes.lora_info import LoraInfoLM
     from .py.nodes.lora_syntax_to_path import LoraSyntaxToPath
     from .py.nodes.create_hook_lora import CreateHookLoraLM
+    from .py.nodes.metadata_overwrite import MetadataOverwriteLM
     from .py.metadata_collector import init as init_metadata_collector
 except (
     ImportError
@@ -66,6 +67,9 @@ except (
     CreateHookLoraLM = importlib.import_module(
         "py.nodes.create_hook_lora"
     ).CreateHookLoraLM
+    MetadataOverwriteLM = importlib.import_module(
+        "py.nodes.metadata_overwrite"
+    ).MetadataOverwriteLM
     init_metadata_collector = importlib.import_module("py.metadata_collector").init
 
 NODE_CLASS_MAPPINGS = {
@@ -88,6 +92,7 @@ NODE_CLASS_MAPPINGS = {
     LoraInfoLM.NAME: LoraInfoLM,
     LoraSyntaxToPath.NAME: LoraSyntaxToPath,
     CreateHookLoraLM.NAME: CreateHookLoraLM,
+    MetadataOverwriteLM.NAME: MetadataOverwriteLM,
 }
 
 WEB_DIRECTORY = "./web/comfyui"

py/metadata_collector/constants.py

@@ -9,6 +9,14 @@ EMBEDDINGS = "embeddings"
 SIZE = "size"
 IMAGES = "images"
 IS_SAMPLER = "is_sampler"  # New constant to mark sampler nodes
+OVERWRITE = "overwrite"  # Manual metadata overwrite from MetadataOverwriteLM node
+
+# Field names that the MetadataOverwriteLM node and its extractor share
+METADATA_OVERWRITE_FIELDS = (
+    "prompt", "negative_prompt", "seed", "steps", "cfg_scale",
+    "sampler", "scheduler", "checkpoint", "loras", "size",
+    "clip_skip", "additional_data",
+)
 
 # Complete list of categories to track
-METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, EMBEDDINGS, SIZE, IMAGES]
+METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, EMBEDDINGS, SIZE, IMAGES, OVERWRITE]

py/metadata_collector/metadata_processor.py

@@ -6,7 +6,7 @@ from .constants import IMAGES
 # Check if running in standalone mode
 standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
 
-from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IS_SAMPLER
+from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IS_SAMPLER, OVERWRITE
 from .node_extractors import NODE_EXTRACTORS
 
 logger = logging.getLogger(__name__)
@@ -524,7 +524,8 @@ class MetadataProcessor:
             "checkpoint": None,
             "loras": "",
             "size": None,
-            "clip_skip": None
+            "clip_skip": None,
+            "additional_data": "",
         }
         
         # Get the prompt object for node relationship tracing
@@ -672,7 +673,14 @@ class MetadataProcessor:
                 break
         if params["clip_skip"] is None:
             params["clip_skip"] = "1"
-        
+
+        # ---- Apply manual metadata overwrites ----
+        for overwrite_info in metadata.get(OVERWRITE, {}).values():
+            overwrite_params = overwrite_info.get("parameters", {})
+            for key, value in overwrite_params.items():
+                if value:  # truthy check — only overwrite when user provided a real value
+                    params[key] = value
+
         return params
     
     @staticmethod

py/metadata_collector/metadata_registry.py

@@ -1,7 +1,7 @@
 import time
 from nodes import NODE_CLASS_MAPPINGS  # type: ignore
 from .node_extractors import NODE_EXTRACTORS, GenericNodeExtractor
-from .constants import METADATA_CATEGORIES, IMAGES
+from .constants import METADATA_CATEGORIES, IMAGES, OVERWRITE
 
 
 class MetadataRegistry:
@@ -133,8 +133,16 @@ class MetadataRegistry:
                 if cache_key in self.node_cache:
                     cached_data = self.node_cache[cache_key]
 
+                    # Detect bypass (mode=4) / mute (mode=2) — these nodes
+                    # were intentionally disabled and should not contribute
+                    # overwrite values from a previous execution's cache.
+                    node_mode = node_data.get("mode", 0)
+                    node_is_disabled = node_mode in (2, 4)
+
                     # Apply cached metadata to the current metadata
                     for category in self.metadata_categories:
+                        if category == OVERWRITE and node_is_disabled:
+                            continue
                         if category in cached_data and node_id in cached_data[category]:
                             if node_id not in metadata[category]:
                                 metadata[category][node_id] = cached_data[category][

py/metadata_collector/node_extractors.py

@@ -2,7 +2,7 @@ import json
 import os
 import re
 
-from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER
+from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER, OVERWRITE, METADATA_OVERWRITE_FIELDS
 
 
 def _store_checkpoint_metadata(metadata, node_id, model_name):
@@ -1221,6 +1221,32 @@ class CR_ApplyControlNetStackExtractor(NodeMetadataExtractor):
                 metadata[PROMPTS][node_id]["positive_encoded"] = transformed_positive
                 metadata[PROMPTS][node_id]["negative_encoded"] = transformed_negative
 
+class MetadataOverwriteExtractor(NodeMetadataExtractor):
+    """Extract manually specified metadata from MetadataOverwriteLM node.
+
+    Stores truthy input values under the OVERWRITE category so that
+    extract_generation_params can merge them over the inferred params.
+    """
+
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        overwrite_params = {}
+        for key in METADATA_OVERWRITE_FIELDS:
+            value = inputs.get(key)
+            if value:  # truthy — only overwrite when user provided a real value
+                overwrite_params[key] = value
+
+        if overwrite_params:
+            metadata.setdefault(OVERWRITE, {})
+            metadata[OVERWRITE][node_id] = {
+                "parameters": overwrite_params,
+                "node_id": node_id,
+            }
+
+
 # Registry of node-specific extractors
 # Keys are node class names
 NODE_EXTRACTORS = {
@@ -1288,5 +1314,7 @@ NODE_EXTRACTORS = {
     "CFGGuider": CFGGuiderExtractor,            # Add CFGGuider
     # Image
     "VAEDecode": VAEDecodeExtractor,  # Added VAEDecode extractor
+    # Metadata overwrite
+    "MetadataOverwriteLM": MetadataOverwriteExtractor,
     # Add other nodes as needed
 }

py/nodes/metadata_overwrite.py

@@ -0,0 +1,154 @@
+"""Metadata Overwrite node — allows users to manually specify generation parameters
+that override the automatically collected/inferred metadata.
+
+All inputs have falsy defaults: only truthy (non-empty / non-zero) values
+will overwrite the corresponding field in the final metadata.
+"""
+
+from typing import Any
+
+from ..metadata_collector.constants import METADATA_OVERWRITE_FIELDS
+
+
+class MetadataOverwriteLM:
+    NAME = "Metadata Overwrite (LoraManager)"
+    CATEGORY = "Lora Manager/utils"
+    DESCRIPTION = (
+        "Manually specify generation parameters to override automatically collected "
+        "metadata. Only filled/connected inputs will take effect — empty defaults "
+        "are ignored."
+    )
+
+    @classmethod
+    def INPUT_TYPES(cls) -> dict[str, Any]:
+        return {
+            "optional": {
+                "prompt": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": "Positive prompt. Only overwrites when non-empty.",
+                    },
+                ),
+                "negative_prompt": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": "Negative prompt. Only overwrites when non-empty.",
+                    },
+                ),
+                "seed": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 0xFFFFFFFFFFFFFFFF,
+                        "control_after_generate": False,
+                        "tooltip": "Seed value. Only overwrites when > 0.",
+                    },
+                ),
+                "steps": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 10000,
+                        "tooltip": "Number of steps. Only overwrites when > 0.",
+                    },
+                ),
+                "cfg_scale": (
+                    "FLOAT",
+                    {
+                        "default": 0.0,
+                        "min": 0.0,
+                        "max": 100.0,
+                        "tooltip": "CFG scale. Only overwrites when > 0.",
+                    },
+                ),
+                "sampler": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": "Sampler name. Only overwrites when non-empty.",
+                    },
+                ),
+                "scheduler": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": "Scheduler name. Only overwrites when non-empty.",
+                    },
+                ),
+                "checkpoint": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": "Checkpoint / model name. Only overwrites when non-empty.",
+                    },
+                ),
+                "loras": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": (
+                            "LoRA syntax, e.g. <lora:name:strength> "
+                            "or <lora:name:model_strength:clip_strength>, "
+                            "separated by spaces. Only overwrites when non-empty."
+                        ),
+                    },
+                ),
+                "size": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": (
+                            "Image size in WIDTHxHEIGHT format (e.g. 512x768). "
+                            "Only overwrites when non-empty."
+                        ),
+                    },
+                ),
+                "clip_skip": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": -24,
+                        "max": 24,
+                        "tooltip": "Clip skip. Only overwrites when non-zero.",
+                    },
+                ),
+                "additional_data": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": (
+                            "Additional data to embed in the image metadata. "
+                            "Inserted between Clip skip and Model hash in the "
+                            "A1111-compatible parameters string. "
+                            'Example: "Copyright": "Some license info"'
+                        ),
+                    },
+                ),
+            },
+        }
+
+    RETURN_TYPES = ("METADATA",)
+    RETURN_NAMES = ("metadata",)
+    FUNCTION = "collect_metadata"
+    OUTPUT_NODE = True
+
+    def collect_metadata(self, **kwargs: Any) -> tuple[dict[str, Any]]:
+        """Collect non-falsy input values into a metadata dict.
+
+        Only values that are truthy (non-empty string, non-zero number)
+        are included — matching the overwrite logic in the metadata pipeline.
+        """
+        result: dict[str, Any] = {}
+        for key in METADATA_OVERWRITE_FIELDS:
+            value = kwargs.get(key)
+            if value:
+                result[key] = value
+        return (result,)

py/nodes/save_image.py

@@ -471,6 +471,9 @@ class SaveImageLM:
                     params.append(f"Clip skip: {abs(cs)}")
             except (ValueError, TypeError):
                 pass
+        additional_data = metadata_dict.get("additional_data", "")
+        if additional_data:
+            params.append(additional_data)
         if ckpt_hash:
             params.append(f"Model hash: {ckpt_hash[:10].upper()}")
         if ckpt_display_name:

tests/metadata_collector/test_metadata_collector.py

@@ -820,3 +820,220 @@ def test_lora_manager_checkpoint_and_unet_loaders_extract_models(metadata_regist
         "type": "checkpoint",
         "node_id": "unet_node",
     }
+
+
+# ---------------------------------------------------------------------------
+# MetadataOverwriteExtractor & overwrite merge tests
+# ---------------------------------------------------------------------------
+
+from py.metadata_collector.constants import OVERWRITE, METADATA_OVERWRITE_FIELDS
+from py.metadata_collector.node_extractors import MetadataOverwriteExtractor
+
+
+def test_metadata_overwrite_extractor_stores_truthy_values(metadata_registry):
+    """Extractor should store truthy inputs under the OVERWRITE category."""
+    metadata_registry.start_collection("prompt-ow")
+    metadata = metadata_registry.prompt_metadata["prompt-ow"]
+
+    inputs = {
+        "prompt": "a beautiful landscape",
+        "negative_prompt": "",
+        "seed": 42,
+        "steps": 0,
+        "cfg_scale": 7.5,
+        "sampler": "",
+        "scheduler": "",
+        "checkpoint": "myModel.safetensors",
+        "loras": "<lora:detail:0.8>",
+        "size": "1024x768",
+        "clip_skip": 0,
+        "additional_data": '{"Copyright": "CC0"}',
+    }
+
+    MetadataOverwriteExtractor.extract("ow-1", inputs, None, metadata)
+
+    assert OVERWRITE in metadata
+    assert "ow-1" in metadata[OVERWRITE]
+    params = metadata[OVERWRITE]["ow-1"]["parameters"]
+
+    # Truthy values stored
+    assert params["prompt"] == "a beautiful landscape"
+    assert params["seed"] == 42
+    assert params["cfg_scale"] == 7.5
+    assert params["checkpoint"] == "myModel.safetensors"
+    assert params["loras"] == "<lora:detail:0.8>"
+    assert params["size"] == "1024x768"
+    assert params["additional_data"] == '{"Copyright": "CC0"}'
+
+    # Falsy values NOT stored
+    assert "negative_prompt" not in params
+    assert "steps" not in params
+    assert "sampler" not in params
+    assert "scheduler" not in params
+    assert "clip_skip" not in params
+
+    metadata_registry.clear_metadata()
+
+
+def test_metadata_overwrite_extractor_empty_inputs(metadata_registry):
+    """Extractor with all-falsy inputs should NOT create OVERWRITE category."""
+    metadata_registry.start_collection("prompt-ow2")
+    metadata = metadata_registry.prompt_metadata["prompt-ow2"]
+
+    inputs = {key: "" for key in METADATA_OVERWRITE_FIELDS}
+    inputs.update({"seed": 0, "steps": 0, "cfg_scale": 0.0, "clip_skip": 0})
+
+    MetadataOverwriteExtractor.extract("ow-2", inputs, None, metadata)
+
+    # start_collection pre-creates empty dicts for all categories,
+    # but no node should have populated OVERWRITE with any data
+    assert not metadata[OVERWRITE]
+
+    metadata_registry.clear_metadata()
+
+
+def test_extract_generation_params_applies_overwrite(metadata_registry, populated_registry, monkeypatch):
+    """overwrite values should replace inferred params in extract_generation_params."""
+    import py.metadata_collector.metadata_processor as mp
+
+    monkeypatch.setattr(mp, "standalone_mode", False)
+
+    metadata = populated_registry["metadata"]
+    registry_obj = populated_registry["registry"]
+
+    # Simulate the MetadataOverwriteLM node having been executed with overwrite values
+    registry_obj.start_collection("promptA")
+    # Re-populate with the same data (start_collection resets)
+    registry_obj.set_current_prompt(populated_registry["prompt"])
+    metadata2 = registry_obj.prompt_metadata["promptA"]
+
+    # Inject overwrite data into metadata
+    metadata2[OVERWRITE] = {
+        "ow-1": {
+            "parameters": {
+                "seed": 777,
+                "additional_data": '{"AuthorURL": "https://civitai.com/user/foo"}',
+            },
+            "node_id": "ow-1",
+        }
+    }
+    # Copy other categories from original populated metadata
+    for cat in ("models", "prompts", "sampling", "loras", "size", "images"):
+        if cat in metadata:
+            metadata2[cat] = metadata[cat]
+    metadata2["execution_order"] = metadata["execution_order"]
+
+    params = MetadataProcessor.extract_generation_params(metadata2, id="vae")
+
+    # Overwritten values
+    assert params["seed"] == 777
+    assert params["additional_data"] == '{"AuthorURL": "https://civitai.com/user/foo"}'
+
+    # Inferred values still present (not overwritten)
+    assert params["prompt"] == "A castle on a hill"
+    assert params["cfg_scale"] == 7.5
+    assert params["checkpoint"] == "model.safetensors"
+
+    registry_obj.clear_metadata()
+
+
+def test_extract_generation_params_overwrite_falsy_skipped(metadata_registry, populated_registry, monkeypatch):
+    """Overwrite entries with falsy values should NOT replace inferred params."""
+    import py.metadata_collector.metadata_processor as mp
+
+    monkeypatch.setattr(mp, "standalone_mode", False)
+
+    metadata = populated_registry["metadata"]
+    registry_obj = populated_registry["registry"]
+
+    registry_obj.start_collection("promptA")
+    registry_obj.set_current_prompt(populated_registry["prompt"])
+    metadata2 = registry_obj.prompt_metadata["promptA"]
+
+    # Inject overwrite with falsy values
+    metadata2[OVERWRITE] = {
+        "ow-1": {
+            "parameters": {
+                "seed": 0,
+                "steps": 0,
+                "cfg_scale": 0.0,
+                "prompt": "",
+                "clip_skip": 0,
+            },
+            "node_id": "ow-1",
+        }
+    }
+    for cat in ("models", "prompts", "sampling", "loras", "size", "images"):
+        if cat in metadata:
+            metadata2[cat] = metadata[cat]
+    metadata2["execution_order"] = metadata["execution_order"]
+
+    params = MetadataProcessor.extract_generation_params(metadata2, id="vae")
+
+    # Falsy overwrites should NOT have replaced inferred values
+    assert params["prompt"] == "A castle on a hill"
+    assert params["cfg_scale"] == 7.5
+
+    registry_obj.clear_metadata()
+
+
+def test_fill_missing_metadata_skips_overwrite_for_bypassed_node(metadata_registry):
+    """Bypassed (mode=4) node should not have OVERWRITE filled from cache."""
+    metadata_registry.start_collection("prompt-bypass")
+
+    # Simulate a previous execution that cached overwrite data
+    metadata_registry.record_node_execution(
+        "ow-1",
+        "MetadataOverwriteLM",
+        {"seed": 99, "prompt": "test", "steps": 0, "cfg_scale": 0.0,
+         "negative_prompt": "", "sampler": "", "scheduler": "", "checkpoint": "",
+         "loras": "", "size": "", "clip_skip": 0, "additional_data": ""},
+        None,
+    )
+
+    # Now start a new prompt where the node is bypassed (mode=4)
+    metadata_registry.start_collection("prompt-bypass-2")
+    original_prompt = {
+        "ow-1": {"class_type": "MetadataOverwriteLM", "inputs": {}, "mode": 4},
+    }
+    metadata_registry.set_current_prompt(
+        SimpleNamespace(original_prompt=original_prompt)
+    )
+
+    metadata = metadata_registry.get_metadata("prompt-bypass-2")
+
+    # The overwrite data should NOT be present (node was bypassed, not
+    # a cache hit — it should not inherit previous execution's overwrite)
+    assert "ow-1" not in metadata.get(OVERWRITE, {})
+
+    metadata_registry.clear_metadata()
+
+
+def test_fill_missing_metadata_fills_overwrite_for_muted_node(metadata_registry):
+    """Muted (mode=2) node should also not have OVERWRITE filled from cache."""
+    metadata_registry.start_collection("prompt-mute")
+
+    # Simulate a previous execution that cached overwrite data
+    metadata_registry.record_node_execution(
+        "ow-1",
+        "MetadataOverwriteLM",
+        {"seed": 88, "prompt": "test2", "steps": 0, "cfg_scale": 0.0,
+         "negative_prompt": "", "sampler": "", "scheduler": "", "checkpoint": "",
+         "loras": "", "size": "", "clip_skip": 0, "additional_data": ""},
+        None,
+    )
+
+    # Start a new prompt where the node is muted (mode=2)
+    metadata_registry.start_collection("prompt-mute-2")
+    original_prompt = {
+        "ow-1": {"class_type": "MetadataOverwriteLM", "inputs": {}, "mode": 2},
+    }
+    metadata_registry.set_current_prompt(
+        SimpleNamespace(original_prompt=original_prompt)
+    )
+
+    metadata = metadata_registry.get_metadata("prompt-mute-2")
+
+    assert "ow-1" not in metadata.get(OVERWRITE, {})
+
+    metadata_registry.clear_metadata()