Marcel Hofer
7d0600f141
Add separate image and text Decision Router nodes with configurable system prompts, up to 52 user-defined routes, per-item decisions, normalized decision_json output, and native IMAGE/STRING route sockets. Run Clef-Flash 9B, Clef 27B, and OpenJev 27B in-process through llama.cpp. Add decision-head, logits, MTMD vision, and dynamic CUDA backend capability checks before model downloads. Keep model weights and vision projectors out of the repository; do not launch a separate llama-server or upgrade PyTorch/Transformers. Block inactive route outputs so unused downstream branches are skipped. Keep dynamic route names synchronized with connected outputs and preserve stable socket identities. Register the commercial UI variant while keeping non-commercial OpenJev unavailable in commercial builds. Update all 3.0.0 package metadata, README, runtime and workflow guides, the illustrated router example, and the detailed update log. Refresh regression expectations for commercial router registration and the current provider model catalog. Validation: all 220 tests pass in the bundled ComfyUI Python 3.12 runtime. Python compilation, JavaScript syntax, version metadata, README image, and staged diff checks pass. The Image Router was manually exercised with Clef-Flash 9B on fox, dog, cat, and none routes. Coverage limits: full-weight inference for Clef 27B and OpenJev 27B, text-mode smoke tests, and clean installs across other OS/Python/CUDA combinations remain unverified. The documented Windows x64, CPython 3.12, CUDA 13.0 JamePeng runtime is the only verified build matrix.
118 lines
4.1 KiB
Python
118 lines
4.1 KiB
Python
"""
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{
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"name": "ComfyUI-ThinkingLLM",
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"description": "A multimodal ComfyUI AI node pack with Qwen, Gemma 4, GGUF, Whisper, image and text decision routing, and live thinking output.",
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"author": "goodguy1963",
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"version": "3.0.0",
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"url": "https://github.com/goodguy1963/ComfyUI-ThinkingLLM",
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"category": "image"
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}
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"""
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import importlib.util
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import os
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import sys
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# Get the directory of the current script
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current_dir = os.path.dirname(__file__)
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sys.path.insert(0, current_dir)
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NODE_CLASS_MAPPINGS = {}
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NODE_DISPLAY_NAME_MAPPINGS = {}
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COMMERCIAL_RELEASE = os.environ.get("THINKINGLLM_COMMERCIAL_RELEASE") == "1"
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WEB_DIRECTORY = "./web_commercial" if COMMERCIAL_RELEASE else "./web"
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COMMERCIAL_MODULES = {
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"AILab_OutputCleaner",
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"AILab_QwenVL",
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"AILab_QwenVL_PromptEnhancer",
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"AILab_StreamDisplay",
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}
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COMMERCIAL_NODE_MODULES = {
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"decision_router",
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"story_split_node",
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"system_prompt_preset",
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"vram_cleanup",
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}
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LEGACY_NODE_REPLACEMENTS = {
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"AILab_QwenVL": "ThinkingLLM_QwenVL",
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"AILab_QwenVL_Advanced": "ThinkingLLM_QwenVL_Advanced",
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"AILab_QwenVL_GGUF": "ThinkingLLM_QwenVL_GGUF",
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"AILab_QwenVL_GGUF_Advanced": "ThinkingLLM_QwenVL_GGUF_Advanced",
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"AILab_QwenVL_PromptEnhancer": "ThinkingLLM_QwenVL_PromptEnhancer",
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"AILab_QwenVL_GGUF_PromptEnhancer": "ThinkingLLM_QwenVL_GGUF_PromptEnhancer",
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}
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if COMMERCIAL_RELEASE:
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LEGACY_NODE_REPLACEMENTS = {
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old: new for old, new in LEGACY_NODE_REPLACEMENTS.items() if "GGUF" not in old
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}
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def load_modules_from_directory(directory):
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for file in os.listdir(directory):
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if file.endswith(".py"):
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file_path = os.path.join(directory, file)
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module_name = os.path.basename(file)[:-3]
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if module_name == os.path.basename(__file__)[:-3]:
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continue
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if COMMERCIAL_RELEASE:
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allowed = (
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COMMERCIAL_MODULES
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if os.path.abspath(directory) == os.path.abspath(current_dir)
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else COMMERCIAL_NODE_MODULES
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)
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if module_name not in allowed:
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continue
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try:
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spec = importlib.util.spec_from_file_location(module_name, file_path)
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if spec is None or spec.loader is None:
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raise ImportError(f"Unable to create import spec for {module_name}")
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module = importlib.util.module_from_spec(spec)
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sys.modules[module_name] = module
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spec.loader.exec_module(module)
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if hasattr(module, "NODE_CLASS_MAPPINGS"):
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NODE_CLASS_MAPPINGS.update(module.NODE_CLASS_MAPPINGS)
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if hasattr(module, "NODE_DISPLAY_NAME_MAPPINGS"):
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NODE_DISPLAY_NAME_MAPPINGS.update(module.NODE_DISPLAY_NAME_MAPPINGS)
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except Exception as e:
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print(f"Error loading module {module_name}: {e}")
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load_modules_from_directory(current_dir)
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# Also load from nodes subdirectory
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nodes_dir = os.path.join(current_dir, "nodes")
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if os.path.exists(nodes_dir):
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load_modules_from_directory(nodes_dir)
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for legacy_node_name in LEGACY_NODE_REPLACEMENTS:
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NODE_CLASS_MAPPINGS.pop(legacy_node_name, None)
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NODE_DISPLAY_NAME_MAPPINGS.pop(legacy_node_name, None)
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def _register_legacy_node_replacements():
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try:
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from comfy_api.latest._io import NodeReplace
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from server import PromptServer
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except Exception:
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return
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manager = getattr(getattr(PromptServer, "instance", None), "node_replace_manager", None)
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if manager is None:
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return
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for old_node_id, new_node_id in LEGACY_NODE_REPLACEMENTS.items():
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manager.register(NodeReplace(new_node_id=new_node_id, old_node_id=old_node_id))
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_register_legacy_node_replacements()
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NODE_CLASS_MAPPINGS = dict(sorted(NODE_CLASS_MAPPINGS.items(), key=lambda x: NODE_DISPLAY_NAME_MAPPINGS.get(x[0], x[0])))
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NODE_DISPLAY_NAME_MAPPINGS = dict(sorted(NODE_DISPLAY_NAME_MAPPINGS.items(), key=lambda x: x[1]))
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__all__ = [
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"NODE_CLASS_MAPPINGS",
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"NODE_DISPLAY_NAME_MAPPINGS",
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"LEGACY_NODE_REPLACEMENTS",
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]
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