de5edd7064
Two ComfyUI issues found while testing. 1. Empty output with no error: the Knowledge Base Loader resolved a relative `path` against ComfyUI's working directory, not this package, so the default `knowledge_base/` loaded 0 entries (an empty KB is valid) and every concept became unknown -> empty prompts. Relative paths now resolve against the package root, and the loader warns when the Knowledge Base is empty. 2. Add a `raw` string output (a JSON dump of the node's data) to the Scene Analyzer, Scene Validator, Resolver, Category Splitter, and Prompt Builder nodes, plus a summary `raw` on the Knowledge Base Loader, for inspecting the pipeline in the graph. Adds a shared to_raw_json helper. Tests: package-relative path resolution (independent of cwd), empty-KB warning, raw output content, and updated node metadata/return-arity expectations. Co-authored-by: kunail0804 <kunail0804@gmail.com> Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
"""ComfyUI node for the Scene Analyzer (MASTER_SPEC §20).
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A thin interface: it adapts ComfyUI inputs to the Analyzer module and surfaces the
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CompilerResult's data, warnings, and errors. It contains no compiler logic and
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never imports ComfyUI.
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"""
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from __future__ import annotations
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from typing import Any
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from compiler.analyzer.backend import OllamaBackend
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from compiler.analyzer.scene_analyzer import analyze
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from compiler.common.config import Config
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from .adapters import format_messages, to_raw_json
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class SceneAnalyzerNode:
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"""Runs the Scene Analyzer and emits Scene plus warnings/errors."""
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CATEGORY = "Scene Compiler"
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FUNCTION = "run"
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RETURN_TYPES = ("SCENE", "STRING", "STRING", "STRING")
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RETURN_NAMES = ("scene", "warnings", "errors", "raw")
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@classmethod
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def INPUT_TYPES(cls) -> dict[str, Any]:
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return {
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"required": {
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"natural_language": ("STRING", {"multiline": True, "default": ""}),
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"model_name": ("STRING", {"default": "llama3"}),
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"temperature": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 2.0, "step": 0.1}),
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"timeout": ("INT", {"default": 60, "min": 1, "max": 3600}),
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},
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"optional": {
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"system_prompt": ("STRING", {"multiline": True, "default": ""}),
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},
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}
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def run(
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self,
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natural_language: str,
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model_name: str,
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temperature: float,
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timeout: int,
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system_prompt: str = "",
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) -> tuple[Any, str, str]:
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analyzer: dict[str, Any] = {
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"model": model_name,
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"temperature": temperature,
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"timeout": timeout,
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}
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if system_prompt:
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analyzer["system_prompt"] = system_prompt
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config = Config.from_json({"analyzer": analyzer})
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backend = OllamaBackend.from_config(config)
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result = analyze(natural_language, backend, config)
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return (
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result.data,
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format_messages(result.warnings),
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format_messages(result.errors),
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to_raw_json(result.data),
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)
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