import json import math from pathlib import Path import copy from metadata_utils import ( build_a1111_metadata, build_imh_metadata, ensure_metahub_save_node, ensure_prompt_in_workflow, get_workflow_json, save_png_with_metadata, ) from PIL import Image def _read_png_text_chunks(path: Path) -> dict: data = path.read_bytes() if data[:8] != b"\x89PNG\r\n\x1a\n": raise AssertionError("Not a PNG file") offset = 8 chunks = {} while offset + 8 <= len(data): length = int.from_bytes(data[offset:offset + 4], "big") chunk_type = data[offset + 4:offset + 8] chunk_data = data[offset + 8:offset + 8 + length] offset += 12 + length if chunk_type == b"tEXt": if b"\x00" in chunk_data: keyword, text = chunk_data.split(b"\x00", 1) chunks[keyword.decode("latin-1")] = text.decode("latin-1") return chunks def _save_simple_png(path: Path) -> None: image = Image.new("RGB", (2, 2), color=(0, 0, 0)) image.save(path, "PNG") def test_ensure_prompt_in_workflow_adds_prompt(): workflow = {"workflow": {"nodes": []}} prompt = {"1": {"class_type": "KSampler", "inputs": {}}} result = ensure_prompt_in_workflow(workflow, prompt) assert result["prompt"] == prompt def test_ensure_prompt_in_workflow_preserves_existing_prompt(): existing = {"9": {"class_type": "SaveImage", "inputs": {}}} workflow = {"prompt": existing} prompt = {"1": {"class_type": "KSampler", "inputs": {}}} result = ensure_prompt_in_workflow(workflow, prompt) assert result["prompt"] is existing def test_ensure_metahub_save_node_updates_prompt_by_id(): workflow = {"prompt": {"7": {"class_type": "SaveImage", "inputs": {}}}} ensure_metahub_save_node(workflow, "7") assert workflow["prompt"]["7"]["class_type"] == "MetaHubSaveNode" def test_ensure_metahub_save_node_updates_single_prompt_saveimage(): workflow = {"prompt": {"1": {"class_type": "SaveImage", "inputs": {}}}} ensure_metahub_save_node(workflow, None) assert workflow["prompt"]["1"]["class_type"] == "MetaHubSaveNode" def test_ensure_metahub_save_node_skips_multiple_prompt_saveimage(): workflow = { "prompt": { "1": {"class_type": "SaveImage", "inputs": {}}, "2": {"class_type": "SaveImage", "inputs": {}}, } } ensure_metahub_save_node(workflow, None) assert workflow["prompt"]["1"]["class_type"] == "SaveImage" assert workflow["prompt"]["2"]["class_type"] == "SaveImage" def test_ensure_metahub_save_node_updates_workflow_node_by_id(): workflow = { "workflow": { "nodes": [ { "id": 5, "type": "SaveImage", "title": "Save Image", "properties": {"node_name": "Save Image"}, } ] } } ensure_metahub_save_node(workflow, "5") node = workflow["workflow"]["nodes"][0] assert node["type"] == "MetaHubSaveNode" assert node["title"] == "MetaHub Save Image" assert node["properties"]["node_name"] == "MetaHub Save Image" def test_get_workflow_json_wraps_raw_workflow(): extra_pnginfo = {"nodes": [], "links": []} result = get_workflow_json(extra_pnginfo) assert result == {"workflow": extra_pnginfo} def test_get_workflow_json_accepts_extra_pnginfo_envelope(): extra_pnginfo = {"extra_pnginfo": {"workflow": {"nodes": []}}} result = get_workflow_json(extra_pnginfo) assert result == {"workflow": {"nodes": []}} def test_get_workflow_json_accepts_prompt_dict(): prompt = {"1": {"class_type": "KSampler", "inputs": {}}} result = get_workflow_json(prompt) assert result == {"prompt": prompt} def test_build_imh_metadata_includes_workflow_and_prompt(): params = { "positive": "pos", "negative": "neg", "seed": 123, "steps": 20, "cfg": 7.5, "sampler": "euler", "scheduler": "normal", "model_name": "model.safetensors", "model_hash": "abcdef1234", "width": 512, "height": 768, "lora_list": [], "generation_type": "img2img", "source_image": {"fileName": "base.png", "relativePath": "inputs/base.png"}, } workflow_json = {"workflow": {"nodes": []}, "prompt": {"1": {"class_type": "KSampler"}}} imh = build_imh_metadata(params, workflow_json) assert imh["generator"] == "ComfyUI" assert imh["workflow"] == workflow_json["workflow"] assert imh["prompt_api"] == workflow_json["prompt"] assert imh["generation_type"] == "img2img" assert imh["source_image"]["fileName"] == "base.png" def test_build_imh_metadata_sanitizes_nan(): params = { "positive": "pos", "negative": "neg", "seed": 123, "steps": 20, "cfg": 7.5, "sampler": "euler", "scheduler": "normal", "model_name": "model.safetensors", "model_hash": "abcdef1234", "width": 512, "height": 768, "lora_list": [], } workflow_json = { "workflow": {"nodes": [{"id": 1, "widgets_values": [float("nan")]}]}, "prompt": {"1": {"class_type": "KSampler", "inputs": {"seed": float("nan")}}}, } imh = build_imh_metadata(params, workflow_json) assert imh["workflow"]["nodes"][0]["widgets_values"][0] is None assert imh["prompt_api"]["1"]["inputs"]["seed"] is None def test_build_a1111_metadata_formats_text(): params = { "positive": "pos", "negative": "neg", "steps": 20, "sampler": "euler", "cfg": 7.5, "seed": 123, "width": 512, "height": 768, "model_name": "model.safetensors", "model_hash": "abcdef1234", "lora_hashes": {}, } text = build_a1111_metadata(params) assert "Negative prompt: neg" in text assert "Steps: 20" in text assert "Sampler: euler" in text assert "CFG scale: 7.5" in text assert "Seed: 123" in text assert "Size: 512x768" in text assert "Model: model.safetensors" in text assert "Model hash: abcdef1234" in text def test_save_png_with_metadata_writes_workflow_prompt(tmp_path): imh_metadata = { "workflow": {"nodes": []}, "prompt_api": {"1": {"class_type": "KSampler"}}, } image = Image.new("RGB", (2, 2), color=(0, 0, 0)) file_path = tmp_path / "test.png" save_png_with_metadata(image, str(file_path), "params", imh_metadata) loaded = Image.open(file_path) text = getattr(loaded, "text", {}) workflow_text = text.get("workflow") prompt_text = text.get("prompt") assert workflow_text assert prompt_text assert json.loads(workflow_text) == imh_metadata["workflow"] assert json.loads(prompt_text) == imh_metadata["prompt_api"] chunk_text = _read_png_text_chunks(file_path) assert "workflow" in chunk_text assert "prompt" in chunk_text def test_save_png_with_metadata_roundtrip_for_comfyui(tmp_path): params = { "positive": "pos", "negative": "neg", "seed": 123, "steps": 20, "cfg": 7.5, "sampler": "euler", "scheduler": "normal", "model_name": "model.safetensors", "model_hash": "abcdef1234", "width": 512, "height": 768, "lora_list": [], } workflow_json = { "workflow": {"nodes": [{"id": 7, "type": "SaveImage", "title": "Save Image"}], "links": []}, "prompt": {"7": {"class_type": "SaveImage", "inputs": {"images": ["1", 0]}}}, } ensure_metahub_save_node(workflow_json, "7") imh_metadata = build_imh_metadata(params, workflow_json) file_path = tmp_path / "roundtrip.png" _save_simple_png(file_path) image = Image.open(file_path) save_png_with_metadata(image, str(file_path), "params", imh_metadata) text_chunks = _read_png_text_chunks(file_path) assert "workflow" in text_chunks assert "prompt" in text_chunks workflow_loaded = json.loads(text_chunks["workflow"]) prompt_loaded = json.loads(text_chunks["prompt"]) assert workflow_loaded["nodes"][0]["type"] == "MetaHubSaveNode" assert prompt_loaded["7"]["class_type"] == "MetaHubSaveNode"