v2.0.0-beta.3

Set PROMPTCONTROL_ENABLE_CACHE_HACK=1 in your environment to enable

README.md

@@ -1,13 +1,10 @@
 # ComfyUI prompt control
 
-Nodes for LoRA and prompt scheduling that make basic operations in ComfyUI completely prompt-controllable.
+Control LoRA and prompt scheduling, advanced text encoding, regional prompting, and much more, through your text prompt. Generates dynamic graphs that are literally identical to handcrafted noodle soup.
 
 ## Prompt Control v2
 
-Prompt control has been almost completely rewritten. It now uses ComfyUI's lazy execution to build graphs from the text prompt at runtime. This has some advantages:
-
-- ComfyUI will not re-run unchanged parts of generated graphs. This is especially useful for two-pass workflows where previously you'd be forced to re-run the first sampling pass even with filtering. That is no longer the case and it does the right thing.
-- The generated graph is often exactly equivalent to a manually built workflow using native ComfyUI nodes. There are no more weird sampling hooks that could cause problems with other nodes
+Prompt control has been almost completely rewritten. It now uses ComfyUI's lazy execution to build graphs from the text prompt at runtime. The generated graph is often exactly equivalent to a manually built workflow using native ComfyUI nodes. There are no more weird sampling hooks that could cause problems with other nodes
 
 Prompt Control also comes with `PCTextEncode`, which provides advanced text encoding with many additional features compared to ComfyUI's base `CLIPTextEncode`.
 
@@ -19,11 +16,11 @@ Prompt Control also comes with `PCTextEncode`, which provides advanced text enco
 
 ### Is it stable now?
 
-Unless I run into bugs or significant annoyances that require changing the interface, probably.
+Unless I run into bugs or significant annoyances that require changing the interface, it probably won't change too much, but until I tag 2.0, everything can change.
 
 ### Everything broke, where are the old nodes?
 
-If you really need them, check out the [legacy branch](https://github.com/asagi4/comfyui-prompt-control/tree/legacy). However, I will not fix bugs in that branch, and I strongly recommend just migrating your workflows to the new nodes.
+If you really need them, you can install the [legacy nodes](https://github.com/asagi4/comfyui-prompt-control-legacy). However, I will not fix bugs in those nodes, and I strongly recommend just migrating your workflows to the new nodes.
 
 You can have both installed at the same time; none of the nodes conflict.
 
@@ -43,9 +40,9 @@ See the [syntax documentation](doc/syntax.md)
 If you find prompt scheduling inconvenient for some reason, `PCTextEncode` can be used as a drop-in replacement for `CLIPTextEncode` to get everything else.
 
 
-[This example workflow](workflows/example-lazy.json?raw=1) shows LoRA scheduling and prompt editing and compares it with the same prompt implemented with built-in ComfyUI nodes.
+[This workflow](workflows/example-lazy.json?raw=1) shows LoRA scheduling and prompt editing and compares it with the same prompt implemented with built-in ComfyUI nodes.
 
-[This example workflow](workflows/example.json?raw=1) implements a two-pass workflow illustrating more features, including custom masks and filtering.
+[Here](workflows/example-2pass.json?raw=1) is a two-pass workflow illustrating more features, including custom masks and filtering.
 
 The tools in this repository combine well with the macro and wildcard functionality in [comfyui-utility-nodes](https://github.com/asagi4/comfyui-utility-nodes)
 
@@ -65,23 +62,23 @@ Then restart ComfyUI afterwards.
 
 # Core nodes
 
-## PCLazyTextEncode and PCLazyTextEncodeAvanced
+## PCLazyTextEncode and PCLazyTextEncodeAdvanced
 
 `PCLazyTextEncode` uses ComfyUI's lazy graph execution mechanism to generate a graph of `PCTextEncode` and `SetConditioningTimestepRange` nodes from a prompt with schedules. This has the advantage that if a part of the schedule doesn't change, ComfyUI's caching mechanism allows you to avoid re-encoding the non-changed part.
 
 for example, if you first encode `[cat:dog:0.1]` and later change that to `[cat:dog:0.5]`, no re-encoding takes place.
 
-for added fun, put `NODE(NodeClassName, paramname)` in a prompt to generate a graph using **any other node** that's compatible. The node can't have required parameters besides a single CLIP parameter (which must be named `clip`) and the text prompt, and it must return a `CONDITIONING` as its first return value.
+for added fun, put `NODE(NodeClassName, textinputname)` in a prompt to generate a graph using **any other node** that's compatible. The node can't have required parameters besides a single CLIP parameter (which must be named `clip`) and the text prompt, and it must return a `CONDITIONING` as its first return value. The "default" values are `PCTextEncode` and `text`.
+
+For example, if you for some reason do not want the advanced features of `PCTextEncode`, use `NODE(CLIPTextEncode)` in the prompt and you'll still get scheduling with ComfyUI's regular TE node.
 
 The advanced node enables filtering the prompt for multi-pass workflows.
 
 ## PCLazyLoraLoader and PCLazyLoraLoaderAdvanced
 
-This node reads LoRA expressions from the scheduled prompt and constructs a graph of `LoraLoader`s and `CreateHookLora`s as necessary to provide the necessary LoRA scheduling.
+This node reads LoRA expressions from the scheduled prompt and constructs a graph of `LoraLoader`s and `CreateHookLora`s as necessary to provide the necessary LoRA scheduling. Just use it in place of a `LoRALoader` and use the output normally.
 
-If you have `apply_hooks` set to true, you **do not** need to apply the `HOOKS`  output to a CLIP model separately; it's provided in case you want to use it elsewhere.
-
-The advanced node enables filtering the prompt for multi-pass workflows.
+The Advanced node gives you access to the generated hooks. If you have `apply_hooks` set to true, you **do not** need to apply the `HOOKS`  output to a CLIP model separately; it's provided in case you want to use it elsewhere. The advanced node also enables filtering the prompt for multi-pass workflows.
 
 ## PCTextEncode
 
@@ -168,4 +165,8 @@ The parameters affect how the masked and unmasked prompts are combined to produc
 
 # Known issues
 
-- None at the moment
+- ComfyUI's caching mechanism has an issue that makes it unnecessarily invalidate caches for certain inputs; you'll still get some benefit from the lazy nodes, but changing inputs that shouldn't affect downstream nodes (especially if using filtering) will still cause them to be recomputed because ComfyUI doesn't realize the inputs haven't changed.
+
+If you want to enable a hack to fix this, set `PROMPTCONTROL_ENABLE_CACHE_HACK=1` in your environment. Unset it to disable.
+
+It's a purely optional performance optimization that allows Prompt Control nodes to override their cache keys in a way that should not interfere with other nodes. Note that the optimization only works if the text input to the lazy nodes is a constant (so either directly on the node or from a primitive); outputs from other nodes can't be optimized.

__init__.py

@@ -1,3 +1,10 @@
+"""
+@author: asagi4
+@title: ComfyUI Prompt Control
+@nickname: ComfyUI Prompt Control
+@description: Control LoRA and prompt scheduling, advanced text encoding, regional prompting, and much more, through your text prompt. Generates dynamic graphs that are literally identical to handcrafted noodle soup.
+"""
+
 import os
 import sys
 import logging
@@ -8,7 +15,7 @@ log = logging.getLogger("comfyui-prompt-control")
 log.propagate = False
 if not log.handlers:
     h = logging.StreamHandler(sys.stdout)
-    h.setFormatter(logging.Formatter("[%(levelname)s] PromptControl: %(message)s"))
+    h.setFormatter(logging.Formatter("[PromptControl] %(levelname)s: %(message)s"))
     log.addHandler(h)
 
 if os.environ.get("PROMPTCONTROL_DEBUG"):
@@ -16,6 +23,8 @@ if os.environ.get("PROMPTCONTROL_DEBUG"):
 else:
     log.setLevel(logging.INFO)
 
+cache_hack = importlib.import_module(".prompt_control.cache_hack", package=__name__)
+cache_hack.init()
 
 NODE_CLASS_MAPPINGS = {}
 NODE_DISPLAY_NAME_MAPPINGS = {}

prompt_control/cache_hack.py

@@ -0,0 +1,47 @@
+import comfy_execution.caching
+from comfy_execution.graph_utils import is_link
+import nodes
+from os import environ
+
+import logging
+
+log = logging.getLogger("comfyui-prompt-control")
+
+
+include_unique_id_in_input = comfy_execution.caching.include_unique_id_in_input
+
+
+def promptcontrol_get_immediate_node_signature(self, dynprompt, node_id, ancestor_order_mapping):
+    if not dynprompt.has_node(node_id):
+        # This node doesn't exist -- we can't cache it.
+        return [float("NaN")]
+    node = dynprompt.get_node(node_id)
+    class_type = node["class_type"]
+    class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
+    inputs = node["inputs"]
+    if hasattr(class_def, "CACHE_KEY"):
+        inputs = getattr(class_def, "CACHE_KEY")(inputs)
+    signature = [class_type, self.is_changed_cache.get(node_id)]
+    if (
+        self.include_node_id_in_input()
+        or (hasattr(class_def, "NOT_IDEMPOTENT") and class_def.NOT_IDEMPOTENT)
+        or include_unique_id_in_input(class_type)
+    ):
+        signature.append(node_id)
+    for key in sorted(inputs.keys()):
+        if is_link(inputs[key]):
+            (ancestor_id, ancestor_socket) = inputs[key]
+            ancestor_index = ancestor_order_mapping[ancestor_id]
+            signature.append((key, ("ANCESTOR", ancestor_index, ancestor_socket)))
+        else:
+            signature.append((key, inputs[key]))
+    return signature
+
+
+def init():
+    if environ.get("PROMPTCONTROL_ENABLE_CACHE_HACK") != "1":
+        return
+    log.warning("Enabling Prompt Control cache hack")
+    comfy_execution.caching.CacheKeySetInputSignature.get_immediate_node_signature = (
+        promptcontrol_get_immediate_node_signature
+    )

prompt_control/nodes_lazy.py

@@ -1,6 +1,6 @@
 import logging
 from .parser import parse_prompt_schedules
-from comfy_execution.graph_utils import GraphBuilder
+from comfy_execution.graph_utils import GraphBuilder, is_link
 
 from .prompts import get_function
 
@@ -9,6 +9,13 @@ log = logging.getLogger("comfyui-prompt-control")
 from .utils import consolidate_schedule, find_nonscheduled_loras
 
 
+def cache_key_hack(inputs):
+    out = inputs.copy()
+    if not is_link(inputs["text"]):
+        out["text"] = cache_key_from_inputs(**inputs)
+    return out
+
+
 def create_lora_loader_nodes(graph, model, clip, loras):
     for path, info in loras.items():
         log.info("Creating LoraLoader for %s", path)
@@ -24,6 +31,7 @@ def create_lora_loader_nodes(graph, model, clip, loras):
 
 
 def create_hook_nodes_for_lora(graph, path, info, existing_node, start_pct, end_pct):
+    prev_keyframe = None
     next_keyframe = None
     if not existing_node:
         log.debug("Creating hook for %s", path)
@@ -67,7 +75,7 @@ def create_hook_nodes_for_lora(graph, path, info, existing_node, start_pct, end_
     return hook_node, next_keyframe
 
 
-def build_lora_schedule(graph, schedule, model, clip, apply_hooks):
+def build_lora_schedule(graph, schedule, model, clip, apply_hooks=True, return_hooks=True):
     # This gets rid of non-existent LoRAs
     consolidated = consolidate_schedule(schedule)
     non_scheduled = find_nonscheduled_loras(consolidated)
@@ -106,20 +114,27 @@ def build_lora_schedule(graph, schedule, model, clip, apply_hooks):
             n.set_input("hooks_B", h.out(0))
             res = n
         res = res.out(0)
-    if apply_hooks:
-        n = graph.node("SetClipHooks")
-        n.set_input("clip", clip)
-        n.set_input("hooks", res)
-        n.set_input("apply_to_conds", True)
-        n.set_input("schedule_clip", True)
-        clip = n.out(0)
+        if apply_hooks:
+            n = graph.node("SetClipHooks")
+            n.set_input("clip", clip)
+            n.set_input("hooks", res)
+            n.set_input("apply_to_conds", True)
+            n.set_input("schedule_clip", True)
+            clip = n.out(0)
 
     r = graph.finalize()
 
-    return {"result": (model, clip, res), "expand": r}
+    if return_hooks:
+        ret = (model, clip, res)
+    else:
+        ret = (model, clip)
+
+    return {"result": ret, "expand": r}
 
 
 class PCLazyLoraLoaderAdvanced:
+    CACHE_KEY = cache_key_hack
+
     @classmethod
     def INPUT_TYPES(s):
         return {
@@ -127,9 +142,9 @@ class PCLazyLoraLoaderAdvanced:
                 "text": ("STRING", {"multiline": True}),
                 "model": ("MODEL", {"rawLink": True}),
                 "clip": ("CLIP", {"rawLink": True}),
-                "apply_hooks": ("BOOLEAN", {"default": True}),
             },
             "optional": {
+                "apply_hooks": ("BOOLEAN", {"default": True}),
                 "tags": ("STRING", {"default": ""}),
                 "start": ("FLOAT", {"min": 0.0, "max": 1.0, "default": 0.0, "step": 0.01}),
                 "end": ("FLOAT", {"min": 0.0, "max": 1.0, "default": 1.0, "step": 0.01}),
@@ -142,34 +157,38 @@ class PCLazyLoraLoaderAdvanced:
     CATEGORY = "promptcontrol"
     FUNCTION = "apply"
 
-    def apply(self, model, clip, text, apply_hooks, unique_id, tags="", start=0.0, end=1.0):
-        schedule = parse_prompt_schedules(text).with_filters(filters=tags, start=start, end=end)
+    def apply(self, model, clip, text, unique_id, apply_hooks=True, tags="", start=0.0, end=1.0):
+        schedule = parse_prompt_schedules(text, filters=tags, start=start, end=end)
         graph = GraphBuilder(f"PCLazyLoraLoaderAdvanced-{unique_id}")
-        return build_lora_schedule(graph, schedule, model, clip, apply_hooks)
+        return build_lora_schedule(graph, schedule, model, clip, apply_hooks=apply_hooks, return_hooks=True)
 
 
 class PCLazyLoraLoader:
+    CACHE_KEY = cache_key_hack
+
     @classmethod
     def INPUT_TYPES(s):
         return {
             "required": {
-                "text": ("STRING", {"multiline": True}),
                 "model": ("MODEL", {"rawLink": True}),
                 "clip": ("CLIP", {"rawLink": True}),
-                "apply_hooks": ("BOOLEAN", {"default": True}),
+                "text": ("STRING", {"multiline": True}),
             },
             "hidden": {"unique_id": "UNIQUE_ID"},
         }
 
-    RETURN_TYPES = ("MODEL", "CLIP", "HOOKS")
+    RETURN_TYPES = (
+        "MODEL",
+        "CLIP",
+    )
     OUTPUT_TOOLTIPS = ("Returns a model and clip with LoRAs scheduled",)
     CATEGORY = "promptcontrol"
     FUNCTION = "apply"
 
-    def apply(self, model, clip, text, apply_hooks, unique_id):
+    def apply(self, model, clip, text, unique_id):
         graph = GraphBuilder(f"PCLazyLoraLoader-{unique_id}")
         schedule = parse_prompt_schedules(text)
-        return build_lora_schedule(graph, schedule, model, clip, apply_hooks)
+        return build_lora_schedule(graph, schedule, model, clip, apply_hooks=True, return_hooks=False)
 
 
 def build_scheduled_prompts(graph, schedules, clip):
@@ -203,16 +222,23 @@ def build_scheduled_prompts(graph, schedules, clip):
         combiner.set_input("conditioning_2", othernode.out(0))
         node = combiner
 
-    return {"result": (node.out(0),), "expand": graph.finalize()}
+    g = graph.finalize()
+
+    return {"result": (node.out(0),), "expand": g}
+
+
+def cache_key_from_inputs(text, tags="", start=0.0, end=1.0, **kwargs):
+    schedules = parse_prompt_schedules(text, filters=tags, start=start, end=end)
+    return [(pct, s["prompt"]) for pct, s in schedules]
 
 
 class PCLazyTextEncode:
+    CACHE_KEY = cache_key_hack
+
     @classmethod
     def INPUT_TYPES(s):
         return {
             "required": {"clip": ("CLIP", {"rawLink": True}), "text": ("STRING", {"multiline": True})},
-            # "optional": {"defaults": ("SCHEDULE_DEFAULTS",)},
-            "hidden": {"unique_id": "UNIQUE_ID"},
         }
 
     RETURN_TYPES = ("CONDITIONING",)
@@ -220,13 +246,15 @@ class PCLazyTextEncode:
     CATEGORY = "promptcontrol"
     FUNCTION = "apply"
 
-    def apply(self, clip, text, unique_id):
+    def apply(self, clip, text):
         schedules = parse_prompt_schedules(text)
-        graph = GraphBuilder(f"PCEncodeLazy-{unique_id}")
+        graph = GraphBuilder()
         return build_scheduled_prompts(graph, schedules, clip)
 
 
 class PCLazyTextEncodeAdvanced:
+    CACHE_KEY = cache_key_hack
+
     @classmethod
     def INPUT_TYPES(s):
         return {
@@ -244,7 +272,7 @@ class PCLazyTextEncodeAdvanced:
     FUNCTION = "apply"
 
     def apply(self, clip, text, unique_id, tags="", start=0.1, end=1.0):
-        schedules = parse_prompt_schedules(text).with_filters(start=start, end=end, filters=tags)
+        schedules = parse_prompt_schedules(text, filters=tags, start=start, end=end)
         graph = GraphBuilder(f"PCLazyTextEncodeAdvanced-{unique_id}")
         return build_scheduled_prompts(graph, schedules, clip)
 

prompt_control/parser.py

@@ -5,6 +5,8 @@ from math import ceil
 logging.basicConfig()
 log = logging.getLogger("comfyui-prompt-control")
 
+from functools import lru_cache
+
 if lark.__version__ == "0.12.0":
     x = "Your lark package reports an ancient version (0.12.0) and will not work. If you have the 'lark-parser' package in your Python environment, remove that and *reinstall* lark!"
     log.error(x)
@@ -14,16 +16,13 @@ if lark.__version__ == "0.12.0":
 prompt_parser = lark.Lark(
     r"""
 !start: (prompt | /[][():|]/+)*
-prompt: (emphasized | embedding | scheduled | alternate | sequence | interpolate | loraspec | PLAIN | /</ | />/ | WHITESPACE)+
+prompt: (emphasized | embedding | scheduled | alternate | sequence | loraspec | PLAIN | /</ | />/ | WHITESPACE)+
 !emphasized: "(" prompt? ")"
         | "(" prompt ":" prompt ")"
         | "[" prompt "]"
 scheduled: "[" [prompt ":"] [prompt] ":" _WS? NUMBER ["," NUMBER] "]"
         | "[" [prompt ":"] [prompt] ":" _WS? TAG "]"
 sequence:  "[SEQ" ":" [prompt] ":" NUMBER (":" [prompt] ":" NUMBER)+ "]"
-interpolate.100: "[INT" ":" interp_prompts ":" interp_steps "]"
-interp_prompts: prompt (":" [prompt])+
-interp_steps: NUMBER ("," NUMBER)+ [":" NUMBER]
 alternate: "[" [prompt] ("|" [prompt])+ [":" NUMBER] "]"
 loraspec.99: "<lora:" FILENAME lora_weights [lora_block_weights] ">"
 lora_weights.1: (":" _WS? NUMBER)~1..2
@@ -94,7 +93,6 @@ def clamp(a, b, c):
 
 def get_steps(tree):
     res = [100]
-    interpolation_steps = []
 
     def tostep(s):
         w = float(s) * 100
@@ -116,7 +114,6 @@ def get_steps(tree):
             for i, _ in enumerate(tree.children[:-1]):
                 tree.children[i] = tostep(tree.children[i])
 
-            interpolation_steps.append((tuple(tree.children[:-1]), tree.children[-1]))
             res.extend(tree.children[:-1])
 
         def sequence(self, tree):
@@ -134,7 +131,7 @@ def get_steps(tree):
 
     CollectSteps().visit(tree)
 
-    return sorted(set(interpolation_steps)), sorted(set(res))
+    return sorted(set(res))
 
 
 def at_step(step, filters, tree):
@@ -180,24 +177,6 @@ def at_step(step, filters, tree):
                     previous_step = s
             return ""
 
-        def interpolate(self, args):
-            prompts, starts = args
-            starts = starts[:-1]
-            prev_prompt = None
-            if step < starts[0]:
-                return prompts[0]
-            for i, x in enumerate(starts):
-                prev_prompt = prompts[i]
-                if x >= step:
-                    break
-            return prev_prompt
-
-        def interp_steps(self, args):
-            return list(args)
-
-        def interp_prompts(self, args):
-            return ["".join(flatten(a or [])) for a in args]
-
         def alternate(self, args):
             step_size = args[-1]
             idx = ceil(step / step_size)
@@ -268,22 +247,15 @@ def at_step(step, filters, tree):
 
 
 class PromptSchedule(object):
-    def __init__(self, prompt, filters="", start=0.0, end=1.0, defaults=None, masks=None):
+    def __init__(self, prompt, filters="", start=0.0, end=1.0):
         self.filters = filters
         self.start = start
         self.end = end
         self.prompt = prompt.strip()
         self.defaults = {}
-        if defaults:
-            self.defaults = defaults
         self.loaded_loras = {}
 
-        self.interpolations = None
-        self.parsed_prompt = None
-        self.interpolations, self.parsed_prompt = self._parse()
-        self.masks = masks
-        if masks is None:
-            self.masks = []
+        self.parsed_prompt = self._parse()
 
     def __iter__(self):
         # Filter out zero, it's only useful for interpolation
@@ -293,27 +265,14 @@ class PromptSchedule(object):
         filters = [x.strip() for x in self.filters.upper().split(",")]
         try:
             parsed = []
-            interpolations = set()
             tree = prompt_parser.parse(self.prompt)
-            interpolation_steps, steps = get_steps(tree)
-            log.debug("Interpolation steps: %s", interpolation_steps)
+            steps = get_steps(tree)
 
             def f(x):
                 return round(x / 100, 2)
 
             for t in steps:
                 p = at_step(t, filters, tree)
-                for control_points, step in interpolation_steps:
-                    interp_start = None
-                    interp_end = None
-                    if t == control_points[-1]:
-                        interp_start = max(control_points[0], int(self.start * 100))
-                        interp_end = min(control_points[-1], int(self.end * 100))
-                        control_points = tuple(
-                            sorted(set(f(c) for c in control_points if c >= interp_start or c <= interp_end))
-                        )
-                    if interp_start is not None and interp_end is not None and interp_end > interp_start:
-                        interpolations.add((control_points, f(step)))
                 parsed.append([f(t), p])
 
         except lark.exceptions.LarkError as e:
@@ -322,14 +281,9 @@ class PromptSchedule(object):
 
         # Tag filtering may return redundant prompts, so filter them out here
         res = []
-        prev_p = None
         prev_end = -1
 
         for end_at, p in parsed:
-            # Preserve prompt if it ends at the start of an interpolation, otherwise bump its end time
-            if p == prev_p and res[-1][0] not in [x[0][0] for x in interpolations]:
-                res[-1][0] = end_at
-                continue
             if end_at < self.start:
                 continue
             elif end_at <= self.end:
@@ -338,18 +292,12 @@ class PromptSchedule(object):
             elif end_at > self.end and prev_end < self.end:
                 res.append([end_at, p])
                 break
-            prev_p = p
 
         # Always use the last prompt if everything was filtered
         if len(res) == 0:
             res = [[1.0, parsed[-1][1]]]
 
-        return interpolations, res
-
-    def add_masks(self, *masks):
-        for mask in masks:
-            if mask is not None:
-                self.masks.append(mask)
+        return res
 
     def clone(self):
         return self.with_filters()
@@ -363,8 +311,6 @@ class PromptSchedule(object):
             filters=ifspecified(filters, self.filters),
             start=ifspecified(start, self.start),
             end=ifspecified(end, self.end),
-            defaults=ifspecified(defaults, self.defaults),
-            masks=self.masks[:],
         )
         return p
 
@@ -378,23 +324,7 @@ class PromptSchedule(object):
                 return i, x
         return len(self.parsed_prompt) - 1, self.parsed_prompt[-1]
 
-    def interpolation_at(self, step, total_steps=1):
-        i, x = self.at_step_idx(step, total_steps)
-        for y in self.parsed_prompt[i:]:
-            step = min(y[0], 1.0)
-            if x[1]["prompt"] != y[1]["prompt"]:
-                return step, y
-        return 1.0, self.parsed_prompt[-1]
 
-    def load_loras(self, lora_cache=None):
-        from .utils import Timer, load_loras_from_schedule
-
-        if lora_cache is not None:
-            self.loaded_loras = lora_cache
-        with Timer("PromptSchedule.load_loras()"):
-            self.loaded_loras = load_loras_from_schedule(self.parsed_prompt, self.loaded_loras)
-        return self.loaded_loras
-
-
-def parse_prompt_schedules(prompt):
-    return PromptSchedule(prompt)
+@lru_cache
+def parse_prompt_schedules(prompt, **kwargs):
+    return PromptSchedule(prompt, **kwargs)

prompt_control/utils.py

@@ -35,7 +35,6 @@ def find_nonscheduled_loras(consolidated_schedule):
     if not consolidated_schedule:
         return {}
     last_end, candidate_loras = consolidated_schedule[0]
-    print(candidate_loras)
     to_remove = set()
     for candidate, weights in candidate_loras.items():
         for end, loras in consolidated_schedule[1:]:

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-prompt-control"
 description = "Nodes for convenient prompt editing, making many common operations prompt-controllable"
-version = "1.2.1"
+version = "2.0.0-beta.3"
 license = { file = "LICENSE" }
 # some lark versions older than 1.1.9 apparently have a bug that breaks things, see https://github.com/asagi4/comfyui-prompt-control/issues/35
 dependencies = ["lark >= 1.1.9"]