Add custom nodes, Civitai loras (LFS), and vast.ai setup script

Includes 30 custom nodes committed directly, 7 Civitai-exclusive
loras stored via Git LFS, and a setup script that installs all
dependencies and downloads HuggingFace-hosted models on vast.ai.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

custom_nodes/comfyui-image-saver/saver/saver.py

@@ -0,0 +1,63 @@
+from typing import Any, cast
+from PIL.PngImagePlugin import PngInfo
+from PIL.Image import Image
+
+import json
+import piexif
+import piexif.helper
+
+def save_image(image: Image, filepath: str, extension: str, quality_jpeg_or_webp: int, lossless_webp: bool, optimize_png: bool, a111_params: str, prompt: dict[str, Any] | None, extra_pnginfo: dict[str, Any] | None, embed_workflow: bool) -> None:
+    if extension == 'png':
+        metadata = PngInfo()
+        if a111_params:
+            metadata.add_text("parameters", a111_params)
+
+        if embed_workflow:
+            if extra_pnginfo is not None:
+                for k, v in extra_pnginfo.items():
+                    metadata.add_text(k, json.dumps(v, separators=(',', ':')))
+            if prompt is not None:
+                metadata.add_text("prompt", json.dumps(prompt, separators=(',', ':')))
+
+        image.save(filepath, pnginfo=metadata, optimize=optimize_png)
+    else: # webp & jpeg
+        image.save(filepath, optimize=True, quality=quality_jpeg_or_webp, lossless=lossless_webp)
+
+        # Native example adding workflow to exif:
+        # https://github.com/comfyanonymous/ComfyUI/blob/095610717000bffd477a7e72988d1fb2299afacb/comfy_extras/nodes_images.py#L113
+        pnginfo_json = {}
+        prompt_json = {}
+        if embed_workflow:
+            if extra_pnginfo is not None:
+                pnginfo_json = {piexif.ImageIFD.Make - i: f"{k}:{json.dumps(v, separators=(',', ':'))}" for i, (k, v) in enumerate(extra_pnginfo.items())}
+            if prompt is not None:
+                prompt_json = {piexif.ImageIFD.Model: f"prompt:{json.dumps(prompt, separators=(',', ':'))}"}
+
+        def get_exif_bytes() -> bytes:
+            exif_dict = ({
+                "0th": pnginfo_json | prompt_json
+                } if pnginfo_json or prompt_json else {}) | ({
+                "Exif": {
+                    piexif.ExifIFD.UserComment: cast(bytes, piexif.helper.UserComment.dump(a111_params, encoding="unicode"))
+                },
+            } if a111_params else {})
+            return cast(bytes, piexif.dump(exif_dict))
+
+        exif_bytes = get_exif_bytes()
+
+        # JPEG format limits the EXIF bytes to a maximum of 65535 bytes
+        if extension == "jpg" or extension == "jpeg":
+            MAX_EXIF_SIZE = 65535
+            if len(exif_bytes) > MAX_EXIF_SIZE and embed_workflow:
+                print("ComfyUI-Image-Saver: Error: Workflow is too large, removing client request prompt.")
+                prompt_json = {}
+                exif_bytes = get_exif_bytes()
+                if len(exif_bytes) > MAX_EXIF_SIZE:
+                    print("ComfyUI-Image-Saver: Error: Workflow is still too large, cannot embed workflow!")
+                    pnginfo_json = {}
+                    exif_bytes = get_exif_bytes()
+            if len(exif_bytes) > MAX_EXIF_SIZE:
+                print("ComfyUI-Image-Saver: Error: Metadata exceeds maximum size for JPEG. Cannot save metadata.")
+                return
+
+        piexif.insert(exif_bytes, filepath)