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13 Commits
Author SHA1 Message Date
Ivor StrelarandClaude Opus 5.5 98b7a853cf fix: let SF WaveSpeed Client reuse the official pack's saved key
SF WaveSpeed Client only looked at its own api_key field, its own config.ini
and WAVESPEED_API_KEY. Users who had configured WaveSpeed through the official
wavespeed-comfyui pack therefore had to type a second copy into the node, and
a stale copy there produced a bare 401 from the upload call with no hint of
which key was at fault.

With the field left empty it now falls back, in order, to config.ini, the
environment variable, and the official pack's config.json. The resolved
source (never the key) is logged and passed along, and the Tripo P2 node
names that source when WaveSpeed rejects the key. The field's tooltip warns
that a key typed there is saved into the workflow file.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 16:38:42 +02:00
Ivor StrelarandClaude Opus 5.5 703711f07c feat: add a folder picker to the Save workflow dialog
ComfyUI's Save and Save As dialogs are a single text prompt, so saving into a
subfolder means typing the full path relative to the workflows directory.

A frontend extension now injects a collapsible tree of the workflow folders
into that dialog. Clicking a folder rewrites the path in the dialog's own
input, keeping the typed name and selecting it for overtyping; "+ New folder"
adds a level that the backend creates on save. The tree opens on the current
workflow's folder.

The native dialog is augmented rather than replaced, so ComfyUI still performs
the save and its tab tracking and overwrite confirmation are unchanged. The
picker appears only while Comfy.SaveWorkflow or Comfy.SaveWorkflowAs is
running, which keeps it out of the Rename and Export prompts that share the
same dialog component. Folders come from /api/v2/userdata, which unlike the
v1 listing includes empty directories. Can be switched off in Settings.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 16:33:49 +02:00
Ivor StrelarandClaude Opus 5.5 3f3d8581df feat: add SF WaveSpeed Tripo P2 Image to 3D node
Tripo P2 image-to-3D through WaveSpeed's API, for generating on a WaveSpeed
account rather than ComfyUI partner credits. The official WaveSpeed pack does
not surface it: the installed 2.0.0 fetches its model list from a catalog
endpoint that now returns 404.

Exposes quad topology, face_limit, texture quality (none/fast/standard/
detailed/extreme), PBR, texture version, delight, auto_size, export_uv,
export_orientation and seeds. Validates face_limit against Tripo's ranges
(48-50,000 triangles, 48-25,000 quads) and that 'fast' texture is paired with
v3.5, so bad combinations fail before they are billed.

Outputs mirror ComfyUI's own Tripo node: FILE_3D_GLB and FILE_3D_FBX, with
the one matching the returned format populated (FBX for quad, GLB otherwise),
so it feeds Preview 3D and Save 3D directly. The model is also downloaded to
output/3d/ and its path and URL returned as strings. Unused options are
omitted from the request rather than sent as null, per WaveSpeed's docs.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-21 16:17:05 +02:00
Ivor StrelarandClaude Opus 5 309aaf216b docs: give the README a front page that explains the pack
The README had grown by appending a section per node and opened with little
more than a one-line description, so a visitor landing on the repo could not
tell what the pack was for without scrolling through 44 WaveSpeed rows.

Adds an overview table of the four categories with node counts, and surfaces
the two things worth finding — the asset library workflow and the Google Sheet
prompt queue — above the fold with links into their sections.

Also fixes a broken table in Stillfront/LLM, where a blank line had orphaned
the SF Claude Library Builder row into a separate fragment that rendered as
stray text.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-10-12 13:55:45 +02:00
Ivor StrelarandClaude Opus 5 59ebc14c5c feat: make library builder reruns incremental
Adding assets to a catalogued library used to mean re-describing every asset:
the checkpoint is deleted on success, and its key hashed the file list, so any
change invalidated it. Cataloguing five new assets cost the same as the whole
library.

The manifest itself is now the durable record of what is described. With the
new update_existing input (default on), a rerun loads the existing manifest,
reuses those descriptions, and only sends genuinely new files to Claude.
Entries whose file no longer exists are dropped. Turning it off re-describes
everything.

The checkpoint key no longer hashes the file list either, so adding an asset
mid-recovery does not discard an interrupted run's progress.

Not applied to organise-into-a-copy, where manifest paths are post-rename and
cannot be matched against a scan of the untouched source.

Verified with a stubbed CLI across four reruns: fresh library describes all 6,
an unchanged rerun describes 0, adding 3 describes only those 3, and deleting
2 describes 0 while dropping both from the manifest.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-10-12 11:22:52 +02:00
Ivor StrelarandClaude Opus 5 aef1cc5968 fix: retry a cut-off batch as two smaller halves instead of failing
A batch whose reply ran past the model's length limit came back as truncated
JSON and aborted the whole run — hit in practice on batch 7 of 7, after the
first 90 of 101 assets had already been catalogued successfully.

Parse failures now raise BatchParseError, which the batch runner handles by
splitting the file list in half and retrying each side, recursively. Normal
batches are unaffected; only a batch that actually fails to parse pays for a
retry, and each half that succeeds is merged and checkpointed immediately.

A single asset that still cannot be parsed stops the run with a message naming
that file, so the recursion always terminates.

Verified with a stubbed CLI: a reply truncating above 4 files descends
12 -> 6 -> 3+3 per side and catalogues all 12, and the worst case where every
reply truncates stops after 3 calls with the checkpoint intact.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-10-12 11:03:06 +02:00
Ivor StrelarandClaude Sonnet 5 d3e8e6d470 fix: process library builder in batches to stop the turn/cost blowup
A single session asking Claude to open an entire large library, compose one
manifest, and write it via the Write tool could spiral to 200-400+ turns and
tens of dollars of subscription usage with nothing produced (is_error: true,
reported on a 101-asset library). Rewritten so each Claude call handles only
batch_size assets (default 15) and replies with JSON only — the node itself
assembles and writes the final manifest, so Claude is never given a
file-writing tool for this.

Progress is tracked in a hidden, atomically-written checkpoint
(.sf_library_builder_checkpoint.json, cleared on success). A failed or
interrupted run resumes from the same settings instead of re-paying for
finished batches.

Verified on 45 synthetic assets: 16 turns and ~$0.08 per batch of 15 (vs.
198-401 turns and $25-130 for 101 assets before), and confirmed resume by
pre-seeding a checkpoint and watching it skip the already-done batches while
preserving their entries and reusing the established art_style.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-10-12 10:16:46 +02:00
Ivor StrelarandClaude Opus 5 fd8808fbbb feat: add SF Claude Library Builder and sync it with Asset Director
Library Builder opens every asset in a folder once and writes a manifest
describing each — category, subcategory, archetype, tags, a one-line
description, and a project-level art_style. Asset Director then searches that
manifest on every run without opening an image, which is what keeps a large
library cheap to work with.

Modes: manifest only (read-only, the default), organise into a copy, or
organise in place. write_manifest is off by default so a first run shows the
JSON without touching anything.

Also aligns Asset Director's manifest default to manifest.json and teaches it
to honour the manifest's art_style when writing prompts, so a library
generates in one consistent style.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-10-08 14:00:09 +02:00
Ivor StrelarandClaude Opus 5 919b822fe0 feat: add SF Claude Asset Director node
Claude reads an asset library's manifest, picks the references that suit the
brief, and writes the image prompt for them. Emits an IMAGE batch plus the
prompt, which wire directly into a generation node's image and prompt inputs.

Choosing from a manifest rather than the images themselves keeps a large
library cheap; look_at_images opts into opening the files and is off by
default. pad_to_fit controls how mixed-size assets are reconciled into a
single batch tensor: letterbox onto a shared canvas (default) or stretch.

Runs on the existing Claude Code login, no API key.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-10-08 09:46:44 +02:00
Ivor StrelarandClaude Opus 5 eb513e1cc2 chore: remove the auto-publish workflow
Inherited from the original repo. It fires on every pyproject.toml change
and immediately fails, because the Stillfront org blocks third-party GitHub
Actions and `Comfy-Org/publish-node-action` is not on the allowlist. Each
version bump therefore produced a failure email for no benefit.

Publishing is done manually with `comfy node publish`. Recoverable from
history if the action is ever allowlisted.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-22 09:32:43 +02:00
Ivor StrelarandClaude Opus 5 0c3830097b feat: add SF Claude Code node
Runs prompts through the locally installed Claude Code CLI, so it uses the
user's existing Claude login rather than an Anthropic API key. Accepts a
system prompt and up to 16 images, which are written to a temp working
directory and read back by the agent's Read tool.

Image inputs grow on demand: connecting one reveals the next empty slot, and
unused trailing slots are trimmed.

Closes stdin on the subprocess, which otherwise costs 3s per call while the
CLI waits for input that never arrives.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-22 08:50:24 +02:00
Ivor StrelarandClaude Opus 5 b0952e0fb3 Revert "fix: drop the HTTP endpoint that left 1.0.8 pending registry review"
Removing the route did not clear the Pending status: 1.0.9 shipped without
it and sits Pending alongside 1.0.8, so the endpoint was never the cause.
Pending appears to be the normal post-upload state before a scan promotes a
version to Active.

Restores the Refresh button and its preview endpoint.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-21 13:40:42 +02:00
Ivor StrelarandClaude Opus 5 292abd93d8 fix: drop the HTTP endpoint that left 1.0.8 pending registry review
1.0.8 registered a ComfyUI server route to power a Refresh button, which
put that version into NodeVersionStatusPending and blocked installs. The
route only ever supplied a pre-run preview of the pending count; IS_CHANGED
already forces a fresh read of the sheet on every run, so removing it costs
no functionality.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-21 13:35:40 +02:00
11 changed files with 2092 additions and 60 deletions
-20
View File
@@ -1,20 +0,0 @@
name: Publish to Comfy registry
on:
workflow_dispatch:
push:
branches:
- main
paths:
- "pyproject.toml"
jobs:
publish-node:
name: Publish Custom Node to registry
runs-on: ubuntu-latest
steps:
- name: Check out code
uses: actions/checkout@v4
- name: Publish Custom Node
uses: Comfy-Org/publish-node-action@main
with:
personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}
+215 -3
View File
@@ -2,7 +2,32 @@
![Stillfront](assets/logo.png)
A collection of custom ComfyUI nodes developed by [Stillfront](https://www.stillfront.com). All nodes are prefixed with **SF** for easy searching in ComfyUI.
**63 custom ComfyUI nodes** from [Stillfront](https://www.stillfront.com), covering AI image and
video generation, LLM integration, and tooling for working with large game asset libraries. Every
node is prefixed **SF** so they're easy to find in the node search.
| | |
|---|---|
| [**Stillfront/WaveSpeed**](#stillfrontwavespeed) | 45 nodes — image, video and 3D generation through [WaveSpeed AI](https://wavespeed.ai): VEO 3.1, Sora 2, Nano Banana, Qwen, Flux Kontext, Seedream, WAN 2.5, InfiniteTalk, Tripo P2, upscalers |
| [**Stillfront/VertexAI**](#stillfrontvertexai) | 7 nodes — Imagen 3/4, VEO 3.1 and Nano Banana Pro via Google Cloud Vertex AI |
| [**Stillfront/Utils**](#stillfrontutils) | 7 nodes — Google Sheets integration, prompt batching, resolution presets |
| [**Stillfront/LLM**](#stillfrontllm) | 4 nodes — Claude, Gemini and GPT in your graph, plus the asset library tooling below |
### Worth a look
**[The asset library workflow](#the-asset-library-workflow)** — point Claude at a folder of game
assets and it writes a searchable manifest describing every one. After that, any workflow can ask
for *"the character art that suits a boss-fight poster"* and get back the right reference images
**plus a generated prompt that already matches your project's art style** — without a single image
being opened at generation time.
Two nodes do this: **SF Claude Library Builder** catalogues once, **SF Claude Asset Director**
searches on every run. Both run on your existing Claude Code login, so there's no API key and no
per-token billing.
**[SF Google Sheet Prompt Queue](#using-sf-google-sheet-prompt-queue)** — drive a batch of
generations straight from a Google Sheet, marking rows done as you go and resuming where you left
off.
---
@@ -59,6 +84,158 @@ Chat with large language models directly inside your ComfyUI workflows, with opt
|---|---|
| **SF LLM Chat** | Multi-model chat supporting Claude (Opus, Sonnet, Haiku), Gemini 3 (Pro, Flash), and OpenAI GPT-5 series. Supports image input and reports token usage. |
| **SF Text Analyzer** | Analyze and process text strings within workflows. |
| **SF Claude Code** | Send text and images to Claude through the Claude Code CLI on your own machine, using your existing Claude login instead of an API key. Image slots appear as you fill them. |
| **SF Claude Asset Director** | Point Claude at an asset library and it chooses which references suit the brief and writes the image prompt to go with them. Outputs an IMAGE batch plus the prompt, ready to wire into any generation node. |
| **SF Claude Library Builder** | Point Claude at a folder of game assets and it writes a searchable manifest describing each one. Can also reorganise and rename the files. Feeds **SF Claude Asset Director**. |
#### The asset library workflow
These two nodes are a pair. **Library Builder** catalogues your assets once; **Asset Director**
then searches that catalogue on every run without ever opening an image.
```
one time, when assets change every generation
┌──────────────────────────────┐ ┌──────────────────────────────────┐
│ SF Claude Library Builder │ │ SF Claude Asset Director │
│ opens every image, │──►│ searches the manifest, │──► images + prompt
│ writes manifest.json │ │ opens nothing │
└──────────────────────────────┘ └──────────────────────────────────┘
```
That split is the point: cataloguing is slow (~5s per asset) but happens rarely, while choosing
is instant and happens constantly.
**The manifest schema** (`sf-asset-library/1`):
```json
{
"schema": "sf-asset-library/1",
"project": "Fantasy RPG",
"art_style": "Hand-painted 2D, saturated palette, thick outlines, 3/4 view",
"generated": "2026-10-08",
"assets": [
{
"file": "characters/heroes/knight_aldric.png",
"name": "Aldric the Knight",
"category": "character",
"subcategory": "hero",
"archetype": "tank",
"tags": ["armoured", "sword", "front view", "heroic"],
"desc": "Armoured human knight in silver plate with a red tabard, standing front-on."
}
]
}
```
It's shaped for fast searching rather than for humans: one **flat list** (cheaper to scan than a
tree), the **same keys on every entry**, faceted fields (`category` / `subcategory` /
`archetype` / `tags`) to narrow by, and a one-sentence `desc` carrying the meaning. The
top-level **`art_style`** matters more than it looks — Asset Director reads it and keeps every
prompt it writes consistent with it, so a library generates in one coherent style.
**Library Builder modes:**
| Mode | What it touches |
|---|---|
| **manifest only** (default) | Nothing. Reads the images, returns the JSON as text |
| **organise into a copy** | Writes a tidy, renamed copy to `output_path`; originals untouched |
| **organise in place** | Renames and moves your actual files |
`write_manifest` is **off** by default, so the first run shows you the JSON without writing
anything. Turn it on once you're happy, or paste the text in yourself.
Start in **manifest only**. Reorganising is genuinely useful on a folder of `IMG_0021.png` and
`final_v2 copy.png`, but it moves real files — try it on a copy first.
**Large libraries are processed in batches, not one session.** `batch_size` (default 15) caps
how many assets Claude handles per call — asking it to hold a whole large library open, compose
one giant manifest, and write the file all in a single uninterrupted session is what used to
blow up in turns and cost on libraries of 100+ assets, with nothing produced at the end. Each
batch now only reads its own assets and replies with JSON; the node assembles and writes the
manifest itself, so no file-writing tool is ever handed to Claude for this.
**Reruns are incremental.** With `update_existing` on (the default), the node reads the manifest
already in the library and only catalogues files it doesn't yet describe. So the normal workflow
is: drop new assets into the folder, run the same node against the same path, and only the new
ones cost anything. Entries whose file has since been deleted are dropped automatically. Turn
`update_existing` off to re-describe everything from scratch.
*(Not available in `organise into a copy` mode, where the manifest holds post-rename paths that
can't be matched against the untouched source folder.)*
Separately, a hidden checkpoint (`.sf_library_builder_checkpoint.json`, removed automatically on
success) covers a run that dies partway. Rerunning **resumes** — finished batches are skipped,
not re-paid for.
If a batch's reply comes back **cut off** — the model ran past its reply length limit partway
through describing a wordy set of assets — that batch is automatically **retried as two smaller
halves**, repeatedly if needed, rather than failing the run. You'll see it in the log as
`Batch 7/7: the reply was cut off… Retrying as two batches of 5 and 6`.
#### Using SF Claude Asset Director
Give it a folder of assets and a brief; it returns the references Claude chose and the prompt
it wrote for them. Wire `images` and `prompt` straight into Nano Banana, Seedream, or anything
else that takes an image batch and a text prompt.
**It decides from a manifest, not from the pixels.** Put a file in the library — `assets.json`
by default, though any text or JSON works — describing what each asset is:
```json
{"assets": [
{"file": "knight.png", "desc": "Armoured knight character, heroic, front view"},
{"file": "castle.png", "desc": "Stone castle environment, background location"}
]}
```
That keeps a large library cheap to work with: no image is opened unless you ask for it.
| Input | Purpose |
|---|---|
| `library_path` | The asset folder. Point it at a Google Drive for Desktop sync folder to work off Drive |
| `manifest` | Descriptions file inside the library (default `assets.json`); falls back to filenames if absent |
| `system_prompt` | Standing rules — e.g. *"Choose only character assets unless a background is asked for"* |
| `instruction` | The brief for this run. Type it or wire a string in |
| `max_images` | Ceiling on how many references Claude may pick |
| `pad_to_fit` | **On** (default): scale each image onto a shared canvas, keeping aspect ratios. **Off**: stretch them all to one size |
| `look_at_images` | **Off** (default). On, Claude opens the files as well — better picks on an unlabelled library, but ~5s per image |
| `seed` | Not sent to Claude; change it to force a fresh choice rather than ComfyUI's cached one |
Outputs are `images` (batch), `prompt`, and `picked` (the filenames chosen, for checking its work).
**Why `pad_to_fit` exists:** a ComfyUI image batch is one tensor, so every frame must share
dimensions — and an asset library won't. Padding preserves aspect ratios at the cost of black
bars; stretching avoids bars at the cost of distortion. Which is better depends on the model
you're feeding.
Requires [Claude Code](https://claude.com/claude-code) installed and signed in, same as **SF Claude Code**.
#### Using SF Claude Code
This node shells out to the **Claude Code CLI**, so it bills against your Claude
subscription rather than an Anthropic API key.
**Requirements:** [Claude Code](https://claude.com/claude-code) must be installed *and signed
in* on the machine running ComfyUI. The node searches your `PATH` plus the usual install
locations, and gives a clear error if it can't find it.
| Input | Purpose |
|---|---|
| `prompt` | What you want Claude to do |
| `system_prompt` | Shapes the reply, e.g. *"Reply with only the prompt text, no preamble."* Leave blank to skip |
| `model` | `default`, `opus`, `sonnet`, or `haiku` |
| `timeout_seconds` | Give up after this long (default 300) |
| `seed` | Not sent to Claude — change it to force a fresh reply instead of ComfyUI's cached one |
| `image_1…` | Connect an image and the next slot appears, up to 16 |
Worth knowing before you build a big batch around it:
- **Roughly 5–6 seconds per call minimum.** Claude Code is an agent that reads each image as a
tool call, so it's slower than a direct vision API request.
- **Subscription rate limits apply.** Heavy batch use will hit them; `SF LLM Chat` with an API
key is the pay-per-token alternative that won't.
- **Not portable.** Anyone else installing this pack needs their own Claude Code install and
login for this particular node. Every other node in the pack is unaffected.
---
@@ -134,6 +311,20 @@ Connect an **SF WaveSpeed Client** node (enter your WaveSpeed API key) to any Wa
| **SF WaveSpeed Flux Kontext Max** | Flux Kontext Max — highest quality variant. |
| **SF WaveSpeed Flux ControlNet Union Pro 2** | Flux image generation with ControlNet guidance. |
#### 3D Generation
| Node | Description |
|---|---|
| **SF WaveSpeed Tripo P2 Image to 3D** | Tripo's P2 model — the same one behind ComfyUI's *Tripo P2: Image to Model* partner node — billed to your WaveSpeed account instead of ComfyUI credits. Quad or triangle topology, a target face count, texture quality from none to extreme, PBR, delighting, UVs, and seeds. |
Outputs mirror the partner node, so they plug into **Preview 3D** and **Save 3D** directly: Tripo
returns **FBX when `quad` is on and GLB when it's off**, so the matching output is populated and
the other is empty. The file is also saved to `output/3d/`, with its path and CDN URL as strings.
`face_limit` runs 48–50,000 for triangles or 48–25,000 for quads; `-1` lets Tripo decide. It's a
target, not a hard cap. Leave `export_orientation` unset if the model is headed for rigging or
retexturing — Tripo warns those steps can come out mis-rotated without reporting an error.
#### Upscalers
| Node | Description |
@@ -177,8 +368,29 @@ and skips row 2. Each prompt triggers a separate pass through the downstream gra
- **Marking is manual.** Type anything into the status column — `done`, `x`, `executed` — and that
row is skipped next time. Clear the cell and it gets queued again.
- **Scanning stops at the first empty prompt cell**, so anything below a gap is ignored.
- **Refresh sheet** re-reads the sheet after you've edited it in the browser and reports how many
prompts are still pending.
- **The sheet is re-read on every run**, so edits you make in the browser are picked up
automatically. Add rows or clear status cells and just hit Run again.
- **Refresh sheet** is optional — it reports how many prompts are pending without running
the graph.
---
## Interface improvements
Not nodes — small fixes to ComfyUI's own interface that come with the pack.
### Folder picker in the Save workflow dialog
ComfyUI's **Save** / **Save As** dialog normally wants the whole path typed by hand —
`Stillfront/NewMoon/My Workflow` — to save into a subfolder. With this pack installed, the dialog
also shows your workflow folders as a tree: click a folder, type just the name, confirm.
- **+ New folder** adds a folder at the selected level; it's created on disk when you save into it
- The dialog opens on the folder of the workflow you're editing, already selected
- Only the Save dialogs get the picker — Rename and Export, which reuse the same prompt, are left alone
- ComfyUI still does the actual saving, so tab tracking and overwrite warnings behave exactly as before
Turn it off under **Settings → Stillfront → Workflows**.
---
+370
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@@ -0,0 +1,370 @@
# ABOUTME: Claude picks reference images from an asset library and writes the prompt for them
# ABOUTME: Reads a manifest describing the assets; looking at the images themselves is optional
import json
import os
import re
import subprocess
import tempfile
import numpy as np
import torch
from PIL import Image
from .sf_claude_code import MODEL_CHOICES, find_claude_binary
IMAGE_EXTS = {".png", ".jpg", ".jpeg", ".webp", ".bmp", ".gif"}
MAX_LISTED = 2000
def scan_library(root, recursive):
"""Image files under `root`, as paths relative to it, in sorted order."""
found = []
if recursive:
for folder, _, names in os.walk(root):
for name in names:
if os.path.splitext(name)[1].lower() in IMAGE_EXTS:
full = os.path.join(folder, name)
found.append(os.path.relpath(full, root))
else:
for name in os.listdir(root):
if os.path.splitext(name)[1].lower() in IMAGE_EXTS:
found.append(name)
return sorted(found)[:MAX_LISTED]
def read_manifest(root, manifest):
"""The asset descriptions file, or None when there isn't one."""
name = (manifest or "").strip()
if not name:
return None
path = os.path.join(root, name)
if not os.path.isfile(path):
return None
try:
with open(path, encoding="utf-8", errors="ignore") as f:
return f.read()
except OSError:
return None
def build_request(system_prompt, instruction, files, manifest_text, max_images, may_look):
"""The single prompt sent to Claude."""
parts = []
if system_prompt.strip():
parts.append(system_prompt.strip())
if manifest_text:
parts.append(
"Here is the asset library manifest describing what each file contains. "
"Search it to choose; if it declares an `art_style`, the prompt you write "
"must stay consistent with it.\n\n"
f"{manifest_text.strip()}"
)
listing = "\n".join(f" {name}" for name in files)
parts.append(f"These are the image files available ({len(files)} total):\n{listing}")
if may_look:
parts.append(
"You may use the Read tool on any of these files to look at them before "
"deciding. They are in your current working directory."
)
parts.append(f"Request:\n{instruction.strip()}")
parts.append(
f"Choose at most {max_images} file(s). Reply with ONLY a JSON object and nothing "
f"else — no explanation, no code fence:\n"
f'{{"files": ["exact/path/as/listed.png"], "prompt": "the image generation prompt"}}\n'
f"Use file paths exactly as they appear in the listing. The prompt should refer to "
f"the chosen images in the order you list them."
)
return "\n\n".join(parts)
def parse_reply(text):
"""The JSON object out of Claude's reply, tolerating a code fence around it."""
stripped = text.strip()
start, end = stripped.find("{"), stripped.rfind("}")
if start == -1 or end <= start:
raise RuntimeError(f"Claude did not return JSON. It said: {stripped[:300]}")
try:
payload = json.loads(stripped[start : end + 1])
except json.JSONDecodeError as e:
raise RuntimeError(f"Claude's JSON could not be parsed ({e}): {stripped[:300]}")
files = payload.get("files") or []
prompt = str(payload.get("prompt") or "").strip()
if not isinstance(files, list):
raise RuntimeError("Claude's 'files' field was not a list.")
return [str(f).strip() for f in files if str(f).strip()], prompt
def resolve_picks(picked, available, root):
"""Map Claude's filenames onto real paths, matching on basename as a fallback."""
by_rel = {name: name for name in available}
by_base = {}
for name in available:
by_base.setdefault(os.path.basename(name).lower(), name)
resolved, missing = [], []
for want in picked:
cleaned = want.strip().lstrip("./")
match = by_rel.get(cleaned) or by_base.get(os.path.basename(cleaned).lower())
if match:
resolved.append(os.path.join(root, match))
else:
missing.append(want)
return resolved, missing
def to_image_batch(paths, pad_to_fit):
"""Load the images into one ComfyUI IMAGE tensor.
A batch is a single tensor, so every frame must share dimensions. With
`pad_to_fit` each image is scaled to fit and centred on a common canvas,
which keeps its aspect ratio; without it they are stretched to match.
"""
images = [Image.open(p).convert("RGB") for p in paths]
width = max(im.width for im in images)
height = max(im.height for im in images)
frames = []
for im in images:
if pad_to_fit:
scale = min(width / im.width, height / im.height)
size = (max(1, round(im.width * scale)), max(1, round(im.height * scale)))
canvas = Image.new("RGB", (width, height), (0, 0, 0))
canvas.paste(im.resize(size, Image.LANCZOS),
((width - size[0]) // 2, (height - size[1]) // 2))
im = canvas
else:
im = im.resize((width, height), Image.LANCZOS)
frames.append(np.asarray(im, dtype=np.float32) / 255.0)
return torch.from_numpy(np.stack(frames))
class SFClaudeAssetDirector:
"""
Claude picks reference images out of an asset library and writes the prompt
that goes with them.
Decisions are made from a manifest describing the assets, so the library can
be large without every run costing a pile of image reads. Outputs an IMAGE
batch and a STRING, which wire straight into an image generation node.
"""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"library_path": (
"STRING",
{
"multiline": False,
"default": "",
"tooltip": (
"Folder holding the assets. For Google Drive, point this at "
"your Drive for Desktop sync folder."
),
},
),
"manifest": (
"STRING",
{
"default": "manifest.json",
"tooltip": (
"File inside the library describing each asset, used to choose "
"between them. Written by SF Claude Library Builder, though any "
"text or JSON works. Ignored if absent."
),
},
),
"system_prompt": (
"STRING",
{
"multiline": True,
"default": "",
"tooltip": "Standing instructions — how to choose, how to write the prompt.",
},
),
"instruction": (
"STRING",
{
"multiline": True,
"default": "",
"tooltip": (
"What you want this run. Type it here or wire a string in, "
"e.g. 'Make a poster. Pick the characters you think work best.'"
),
},
),
"max_images": (
"INT",
{
"default": 5,
"min": 1,
"max": 20,
"step": 1,
"tooltip": "Most reference images Claude may choose.",
},
),
"pad_to_fit": (
"BOOLEAN",
{
"default": True,
"tooltip": (
"On: scale each image to fit a shared canvas and centre it, "
"keeping aspect ratios. Off: stretch them all to one size."
),
},
),
"look_at_images": (
"BOOLEAN",
{
"default": False,
"tooltip": (
"Let Claude open the image files as well as the manifest. "
"Better choices on an unlabelled library, but roughly 5 "
"seconds per image it opens."
),
},
),
"recursive": (
"BOOLEAN",
{"default": True, "tooltip": "Include images in subfolders."},
),
"model": (
MODEL_CHOICES,
{"default": "default", "tooltip": "Which Claude model decides."},
),
"timeout_seconds": (
"INT",
{"default": 300, "min": 30, "max": 3600, "step": 30,
"tooltip": "Give up if Claude has not replied within this long."},
),
"seed": (
"INT",
{
"default": 0,
"min": 0,
"max": 0xFFFFFFFF,
"control_after_generate": True,
"tooltip": (
"Not sent to Claude. Change it to force a fresh choice instead "
"of reusing ComfyUI's cached result."
),
},
),
}
}
RETURN_TYPES = ("IMAGE", "STRING", "STRING")
RETURN_NAMES = ("images", "prompt", "picked")
FUNCTION = "direct"
CATEGORY = "Stillfront/LLM"
DESCRIPTION = """
Claude reads your asset library's **manifest**, chooses which references suit the
request, and writes the image prompt to go with them.
Outputs an IMAGE batch and the prompt, ready to wire into Nano Banana or any
other generation node. Point **library_path** at a Google Drive for Desktop sync
folder to work straight off Drive.
**look_at_images** is off by default: choices come from the manifest, so a large
library costs nothing extra. Turn it on to have Claude open the files too.
"""
def direct(self, library_path, manifest, system_prompt, instruction, max_images,
pad_to_fit, look_at_images, recursive, model, timeout_seconds, seed):
root = os.path.expanduser(library_path.strip())
if not root or not os.path.isdir(root):
raise ValueError(f"library_path is not a folder: {library_path!r}")
if not instruction.strip():
raise ValueError("instruction is empty — tell Claude what this run is for.")
binary = find_claude_binary()
if not binary:
raise RuntimeError(
"Claude Code CLI not found. Install it from https://claude.com/claude-code "
"and sign in, then restart ComfyUI."
)
files = scan_library(root, recursive)
if not files:
raise ValueError(f"No image files found in {root}")
manifest_text = read_manifest(root, manifest)
if manifest_text is None and manifest.strip():
print(
f"[SF Claude Asset Director] No manifest '{manifest.strip()}' in the library; "
f"choosing from filenames alone."
)
request = build_request(
system_prompt, instruction, files, manifest_text, max_images, look_at_images
)
command = [binary, "-p", request, "--output-format", "json"]
if model != "default":
command += ["--model", model]
if look_at_images:
command += ["--allowedTools", "Read"]
print(
f"[SF Claude Asset Director] {len(files)} asset(s), "
f"manifest={'yes' if manifest_text else 'no'}, vision={'on' if look_at_images else 'off'}."
)
try:
completed = subprocess.run(
command,
cwd=root,
capture_output=True,
text=True,
timeout=timeout_seconds,
stdin=subprocess.DEVNULL,
)
except subprocess.TimeoutExpired:
raise RuntimeError(
f"Claude did not reply within {timeout_seconds}s. Raise timeout_seconds, "
f"or turn look_at_images off."
)
if completed.returncode != 0:
detail = (completed.stderr or completed.stdout or "").strip()[:500]
raise RuntimeError(f"Claude Code exited with code {completed.returncode}. {detail}")
try:
payload = json.loads(completed.stdout)
except json.JSONDecodeError:
raise RuntimeError(f"Unreadable response: {completed.stdout.strip()[:400]}")
if payload.get("is_error"):
raise RuntimeError(f"Claude reported an error: {payload.get('result', 'unknown')}")
picked, prompt = parse_reply(payload.get("result", ""))
if not picked:
raise RuntimeError("Claude chose no images. Check the manifest describes the assets.")
if not prompt:
raise RuntimeError("Claude returned no prompt.")
paths, missing = resolve_picks(picked[:max_images], files, root)
if missing:
print(f"[SF Claude Asset Director] Ignoring names not in the library: {missing}")
if not paths:
raise RuntimeError(
f"None of Claude's choices matched a real file. It asked for: {picked}"
)
batch = to_image_batch(paths, pad_to_fit)
names = [os.path.relpath(p, root) for p in paths]
print(f"[SF Claude Asset Director] Chose {len(names)}: {', '.join(names)}")
return (batch, prompt, "\n".join(names))
NODE_CLASS_MAPPINGS = {"SFClaudeAssetDirector": SFClaudeAssetDirector}
NODE_DISPLAY_NAME_MAPPINGS = {"SFClaudeAssetDirector": "SF Claude Asset Director"}
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# ABOUTME: Runs a prompt through the locally installed Claude Code CLI, using its own login
# ABOUTME: Accepts text plus any number of images and returns Claude's reply as a string
import json
import os
import shutil
import subprocess
import tempfile
from .vertexai_utils import tensor_to_pil
MAX_IMAGES = 16
# Aliases rather than pinned model IDs, so this keeps working as models are updated.
MODEL_CHOICES = ["default", "opus", "sonnet", "haiku"]
BINARY_CANDIDATES = [
"~/.local/bin/claude",
"~/.claude/local/claude",
"/opt/homebrew/bin/claude",
"/usr/local/bin/claude",
]
def find_claude_binary():
"""Locates the Claude Code CLI, which may not be on ComfyUI's PATH."""
found = shutil.which("claude")
if found:
return found
for candidate in BINARY_CANDIDATES:
path = os.path.expanduser(candidate)
if os.path.isfile(path) and os.access(path, os.X_OK):
return path
return None
def save_images(image_inputs, directory):
"""Writes every frame of every connected IMAGE input to disk. Returns filenames."""
names = []
for slot, tensor in image_inputs:
if tensor is None:
continue
batch = tensor if tensor.dim() == 4 else tensor.unsqueeze(0)
for frame in range(batch.shape[0]):
pil = tensor_to_pil(batch[frame])
if pil is None:
continue
name = f"image_{slot}.png" if batch.shape[0] == 1 else f"image_{slot}_{frame + 1}.png"
pil.convert("RGB").save(os.path.join(directory, name))
names.append(name)
return names
def build_prompt(prompt, image_names):
"""Prefixes the request with instructions to read the images off disk."""
if not image_names:
return prompt
listing = ", ".join(image_names)
plural = "image" if len(image_names) == 1 else "images"
return (
f"The following {plural} are in your current working directory: {listing}\n"
f"Use the Read tool on each of them first, then respond to this request:\n\n"
f"{prompt}"
)
class SFClaudeCode:
"""
Sends a prompt (and any attached images) to Claude through the Claude Code
CLI installed on this machine, so it runs on your existing Claude login
rather than a separate API key.
Connect an image and another image slot appears automatically.
"""
@classmethod
def INPUT_TYPES(cls):
optional = {
f"image_{i}": ("IMAGE",) for i in range(1, MAX_IMAGES + 1)
}
return {
"required": {
"prompt": (
"STRING",
{
"multiline": True,
"default": "",
"tooltip": "What you want Claude to do.",
},
),
"system_prompt": (
"STRING",
{
"multiline": True,
"default": "",
"tooltip": (
"Extra instructions shaping how Claude responds, e.g. "
"'Reply with only the prompt text, no preamble.' Leave blank to skip."
),
},
),
"model": (
MODEL_CHOICES,
{
"default": "default",
"tooltip": "Which Claude model to use. 'default' uses whatever Claude Code is set to.",
},
),
"timeout_seconds": (
"INT",
{
"default": 300,
"min": 30,
"max": 3600,
"step": 30,
"tooltip": "Give up if Claude has not replied within this long.",
},
),
"seed": (
"INT",
{
"default": 0,
"min": 0,
"max": 0xFFFFFFFF,
"control_after_generate": True,
"tooltip": (
"Not sent to Claude. Change it to force a fresh reply instead "
"of reusing ComfyUI's cached result."
),
},
),
},
"optional": optional,
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("text",)
FUNCTION = "run"
CATEGORY = "Stillfront/LLM"
DESCRIPTION = """
Sends text and images to Claude via the **Claude Code CLI** on this machine,
using your existing Claude login — no API key needed.
Requires Claude Code to be installed and signed in on whichever computer runs
ComfyUI. Connect an image and a further image slot appears automatically.
Change **seed** to force a fresh reply; otherwise ComfyUI reuses the cached one.
"""
def run(self, prompt, system_prompt, model, timeout_seconds, seed, **kwargs):
if not prompt.strip():
raise ValueError("prompt is empty — give Claude something to do.")
binary = find_claude_binary()
if not binary:
raise RuntimeError(
"Claude Code CLI not found. Install it from "
"https://claude.com/claude-code and sign in, then restart ComfyUI."
)
image_inputs = [
(i, kwargs.get(f"image_{i}"))
for i in range(1, MAX_IMAGES + 1)
if kwargs.get(f"image_{i}") is not None
]
workdir = tempfile.mkdtemp(prefix="sf_claude_")
try:
image_names = save_images(image_inputs, workdir)
command = [
binary,
"-p",
build_prompt(prompt, image_names),
"--output-format",
"json",
]
if system_prompt.strip():
command += ["--append-system-prompt", system_prompt.strip()]
if model != "default":
command += ["--model", model]
if image_names:
command += ["--allowedTools", "Read"]
print(
f"[SF Claude Code] Running {model} with {len(image_names)} image(s), "
f"timeout {timeout_seconds}s."
)
try:
completed = subprocess.run(
command,
cwd=workdir,
capture_output=True,
text=True,
timeout=timeout_seconds,
# Without this the CLI spends 3s waiting on stdin it will never get.
stdin=subprocess.DEVNULL,
)
except subprocess.TimeoutExpired:
raise RuntimeError(
f"Claude did not reply within {timeout_seconds}s. Raise timeout_seconds "
f"or simplify the request."
)
if completed.returncode != 0:
detail = (completed.stderr or completed.stdout or "").strip()[:500]
raise RuntimeError(
f"Claude Code exited with code {completed.returncode}. {detail}"
)
try:
payload = json.loads(completed.stdout)
except json.JSONDecodeError:
raise RuntimeError(
f"Could not parse Claude's response: {completed.stdout.strip()[:500]}"
)
if payload.get("is_error"):
raise RuntimeError(
f"Claude reported an error: {payload.get('result', 'unknown')}"
)
text = payload.get("result", "")
if not text:
raise RuntimeError("Claude returned an empty response.")
print(
f"[SF Claude Code] Got {len(text)} characters in "
f"{payload.get('duration_ms', '?')}ms."
)
return (text,)
finally:
shutil.rmtree(workdir, ignore_errors=True)
NODE_CLASS_MAPPINGS = {"SFClaudeCode": SFClaudeCode}
NODE_DISPLAY_NAME_MAPPINGS = {"SFClaudeCode": "SF Claude Code"}
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# ABOUTME: Claude surveys a folder of game assets and writes a searchable manifest for it
# ABOUTME: Processes assets in small batches with a resumable checkpoint, so a failure costs little
import hashlib
import json
import os
import subprocess
import tempfile
import time
from .sf_claude_code import MODEL_CHOICES, find_claude_binary
IMAGE_EXTS = {".png", ".jpg", ".jpeg", ".webp", ".bmp", ".gif", ".tga"}
MODE_MANIFEST = "manifest only (read-only)"
MODE_COPY = "organise into a copy"
MODE_IN_PLACE = "organise in place"
MODES = [MODE_MANIFEST, MODE_COPY, MODE_IN_PLACE]
SCHEMA_VERSION = "sf-asset-library/1"
CHECKPOINT_NAME = ".sf_library_builder_checkpoint.json"
ASSET_SCHEMA_SPEC = """{
"file": "<path relative to the library root, exactly as it exists on disk>",
"name": "<short human name>",
"category": "<character|environment|prop|ui|vfx|other>",
"subcategory": "<hero|enemy|npc|location|background|weapon|icon|...>",
"archetype": "<for characters: tank|healer|rogue|mage|boss|minion|... else omit>",
"tags": ["<lowercase keyword>", "..."],
"desc": "<one sentence: what it depicts, pose/view, dominant colours>"
}"""
DEFAULT_SYSTEM_PROMPT = """You are cataloguing a game asset library.
Judge each asset on what it depicts and what role it would play in a game.
Keep `desc` to one sentence that would let someone pick this asset without
seeing it. Make `tags` lowercase, specific and useful for searching — subject,
colour, pose, view angle, mood. Prefer a small shared vocabulary across the
library over inventing a new word per asset."""
def scan_assets(root):
"""Image files under `root`, relative to it, in a stable sorted order."""
found = []
for folder, dirs, names in os.walk(root):
dirs[:] = [d for d in dirs if not d.startswith(".")]
for name in names:
if os.path.splitext(name)[1].lower() in IMAGE_EXTS:
found.append(os.path.relpath(os.path.join(folder, name), root))
return sorted(found)
def chunk(items, size):
for i in range(0, len(items), size):
yield items[i : i + size]
class BatchParseError(RuntimeError):
"""Claude's reply was not usable JSON.
Nearly always a reply that ran past its length limit and stopped partway,
which a smaller batch fixes — so the caller retries by splitting rather than
giving up.
"""
def extract_json(text):
"""The JSON object out of a reply that may be fenced or prefaced."""
start, end = text.find("{"), text.rfind("}")
if start == -1 or end <= start:
raise BatchParseError("the reply stopped before any complete JSON object")
body = text[start : end + 1]
try:
return json.loads(body)
except json.JSONDecodeError as e:
raise BatchParseError(f"the reply was cut off or malformed ({e})")
def canonicalize(claude_path, expected):
"""Map Claude's returned file path onto one of the paths we actually asked
about, tolerating a leading './' or a basename-only answer."""
cleaned = (claude_path or "").strip().lstrip("./")
if cleaned in expected:
return cleaned
base = os.path.basename(cleaned).lower()
for candidate in expected:
if os.path.basename(candidate).lower() == base:
return candidate
return cleaned
def checkpoint_key(mode, manifest_name, system_prompt, project_notes):
"""A fingerprint of this job's settings, so a checkpoint only resumes a
matching rerun.
Deliberately excludes the file list: adding or removing an asset should not
throw away a half-finished run, and entries are keyed by path anyway, so
stale ones are filtered out when the manifest is assembled.
"""
payload = json.dumps(
{
"mode": mode,
"manifest_name": manifest_name,
"system_prompt": system_prompt,
"project_notes": project_notes,
},
sort_keys=True,
)
return hashlib.sha256(payload.encode("utf-8")).hexdigest()[:16]
def load_existing_manifest(path):
"""A previously written manifest, as (entries by file, project, art_style).
This is what makes a rerun incremental: anything already described here is
not sent to Claude again.
"""
if not os.path.isfile(path):
return {}, None, None
try:
with open(path, encoding="utf-8") as f:
data = json.load(f)
except (OSError, json.JSONDecodeError):
return {}, None, None
entries = {}
for entry in data.get("assets") or []:
if isinstance(entry, dict) and entry.get("file"):
entries[entry["file"]] = entry
return entries, data.get("project"), data.get("art_style")
def load_checkpoint(root, key):
path = os.path.join(root, CHECKPOINT_NAME)
if not os.path.isfile(path):
return None
try:
with open(path, encoding="utf-8") as f:
data = json.load(f)
except (OSError, json.JSONDecodeError):
return None
return data if data.get("key") == key else None
def save_checkpoint(root, key, project, art_style, done_assets):
"""Atomic write, so a crash mid-save can't corrupt the checkpoint."""
path = os.path.join(root, CHECKPOINT_NAME)
data = {"key": key, "project": project, "art_style": art_style, "done_assets": done_assets}
fd, tmp = tempfile.mkstemp(dir=root, prefix=".sf_checkpoint_")
try:
with os.fdopen(fd, "w", encoding="utf-8") as f:
json.dump(data, f)
os.replace(tmp, path)
except Exception:
if os.path.exists(tmp):
os.remove(tmp)
raise
def clear_checkpoint(root):
path = os.path.join(root, CHECKPOINT_NAME)
if os.path.isfile(path):
os.remove(path)
def build_batch_instruction(mode, batch_files, total_count, project_notes, established, out_dir):
"""The task description for ONE batch call — scoped to just its own files."""
parts = [
f"You are cataloguing {len(batch_files)} file(s) from one batch of a "
f"{total_count}-file game asset library. You only need to handle the "
f"files listed below — nothing else exists from your point of view."
]
if project_notes.strip():
parts.append(f"About this project:\n{project_notes.strip()}")
listing = "\n".join(f" {name}" for name in batch_files)
parts.append(f"Your files for this batch:\n{listing}")
parts.append(
"Open each one with the Read tool before describing it. Work through them "
"steadily; do not guess from a filename."
)
if mode == MODE_MANIFEST:
parts.append("Do NOT move, rename, copy or delete anything. This is a survey only.")
else:
where = (
f"a new folder at `{out_dir}`, leaving the originals untouched"
if mode == MODE_COPY
else "the working directory itself"
)
parts.append(
f"Then reorganise ONLY these files into {where}:\n"
f"- Group by category, e.g. characters/heroes, characters/enemies, "
f"environments, props, ui, vfx.\n"
f"- Rename to lowercase_with_underscores, descriptive of the subject, "
f"no spaces, no version noise. Keep the original extension.\n"
f"- Never discard a file.\n"
f"- Use Bash (cp for a copy, mv in place) to do the moving.\n"
f"The `file` field of each asset must be its path AFTER reorganising, "
f"relative to the library root."
)
if established:
project, art_style = established
parts.append(
f"This library's project name and art style are already settled by an "
f"earlier batch — reuse them exactly, do not invent new ones:\n"
f' project: "{project}"\n art_style: "{art_style}"'
)
parts.append(
f"Reply with ONLY a JSON object of this shape — no commentary, no code "
f"fence, no other top-level keys:\n"
f'{{"assets": [{ASSET_SCHEMA_SPEC}]}}\n'
f"The assets array must contain exactly one entry per file listed above."
)
else:
parts.append(
f"You are establishing this library's project name and art style for "
f"the first time — later batches will reuse whatever you choose here, "
f"so make `art_style` a precise sentence covering the whole library's "
f"visual approach, not just these files.\n"
f"Reply with ONLY a JSON object of this shape — no commentary, no code "
f"fence:\n"
f'{{"project": "<short project name>", "art_style": "<one sentence>", '
f'"assets": [{ASSET_SCHEMA_SPEC}]}}\n'
f"The assets array must contain exactly one entry per file listed above."
)
return "\n\n".join(parts)
class SFClaudeLibraryBuilder:
"""
Surveys a folder of game assets and writes a manifest describing each one,
so SF Claude Asset Director can choose between them without opening images.
Processes assets in small batches rather than one session, because a single
session covering a large library can blow up in turns and cost with nothing
to show for it. A checkpoint records finished batches, so a failed or
interrupted run resumes instead of re-paying for work already done.
Read-only by default. It can also reorganise and rename the files, into a
copy or in place, when you ask it to.
"""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"library_path": (
"STRING",
{"multiline": False, "default": "", "tooltip": "Folder holding the assets to catalogue."},
),
"mode": (
MODES,
{
"default": MODE_MANIFEST,
"tooltip": (
"manifest only: nothing is moved or renamed. "
"organise into a copy: originals untouched, tidy copy written "
"to output_path. organise in place: renames and moves your "
"actual files."
),
},
),
"output_path": (
"STRING",
{"multiline": False, "default": "", "tooltip": "Destination folder, for 'organise into a copy' only."},
),
"project_notes": (
"STRING",
{
"multiline": True,
"default": "",
"tooltip": (
"What the game is, and anything Claude could not infer from "
"the images — genre, art direction, naming you prefer."
),
},
),
"system_prompt": (
"STRING",
{
"multiline": True,
"default": DEFAULT_SYSTEM_PROMPT,
"tooltip": "How to categorise and describe. Edit to suit your project.",
},
),
"manifest_name": (
"STRING",
{"default": "manifest.json", "tooltip": "Filename for the manifest, written at the library root."},
),
"write_manifest": (
"BOOLEAN",
{
"default": False,
"tooltip": (
"Off: the manifest is only returned as text for you to read "
"and save yourself. On: it is written into the library."
),
},
),
"update_existing": (
"BOOLEAN",
{
"default": True,
"tooltip": (
"On: reuse descriptions already in the manifest and only "
"catalogue files that are new, so adding assets costs only "
"those assets. Entries whose file has since been deleted are "
"dropped. Off: describe every asset again from scratch."
),
},
),
"batch_size": (
"INT",
{
"default": 15,
"min": 3,
"max": 50,
"step": 1,
"tooltip": (
"Assets per Claude call. Keeps each session small enough to "
"finish reliably — a failed batch only costs that batch, not "
"the whole library, and a rerun resumes rather than restarts."
),
},
),
"model": (
MODEL_CHOICES,
{"default": "default", "tooltip": "Which Claude model does the cataloguing."},
),
"timeout_seconds": (
"INT",
{
"default": 300,
"min": 60,
"max": 1800,
"step": 30,
"tooltip": "Per BATCH, not per library. Budget roughly 5s per asset in the batch.",
},
),
"seed": (
"INT",
{
"default": 0,
"min": 0,
"max": 0xFFFFFFFF,
"control_after_generate": True,
"tooltip": "Not sent to Claude. Change it to force a fresh run.",
},
),
}
}
RETURN_TYPES = ("STRING", "STRING")
RETURN_NAMES = ("manifest", "report")
FUNCTION = "build"
CATEGORY = "Stillfront/LLM"
DESCRIPTION = """
Claude looks at every asset in a folder and writes a manifest describing each —
category, archetype, tags and a one-line description — plus a project-level art
style. **SF Claude Asset Director** then searches that manifest instead of
opening images.
Processes **batch_size** assets per Claude call rather than the whole library at
once, and tracks progress in a hidden checkpoint file. If a run fails partway,
rerunning with the same settings resumes from where it stopped instead of
re-paying for batches already done.
With **update_existing** on (the default), rerunning against a library that
already has a manifest only catalogues files that are new — so adding assets
costs just those assets. Entries whose file has since been deleted are dropped.
Defaults to **manifest only**, which touches nothing: you get the JSON as text to
read and save yourself. Switch `write_manifest` on to have it saved into the
library, or change `mode` to let Claude reorganise and rename the files too.
Budget about 5 seconds per asset — it opens every image.
"""
def build(
self,
library_path,
mode,
output_path,
project_notes,
system_prompt,
manifest_name,
write_manifest,
update_existing,
batch_size,
model,
timeout_seconds,
seed,
):
root = os.path.expanduser(library_path.strip())
if not root or not os.path.isdir(root):
raise ValueError(f"library_path is not a folder: {library_path!r}")
out_dir = os.path.expanduser(output_path.strip())
if mode == MODE_COPY:
if not out_dir:
raise ValueError("output_path is required for 'organise into a copy'.")
if os.path.abspath(out_dir).startswith(os.path.abspath(root) + os.sep):
raise ValueError("output_path must sit outside library_path.")
os.makedirs(out_dir, exist_ok=True)
binary = find_claude_binary()
if not binary:
raise RuntimeError(
"Claude Code CLI not found. Install it from https://claude.com/claude-code "
"and sign in, then restart ComfyUI."
)
assets = scan_assets(root)
if not assets:
raise ValueError(f"No image files found in {root}")
manifest_root = out_dir if mode == MODE_COPY else root
manifest_path = os.path.join(manifest_root, manifest_name)
done_by_file = {}
project = art_style = None
# An existing manifest is the durable record of what is already described,
# so a rerun only pays for assets that are genuinely new. Skipped for the
# copy mode, where the manifest holds post-rename paths that cannot be
# matched against a scan of the untouched source folder.
reused = 0
if update_existing and mode != MODE_COPY:
existing, prev_project, prev_style = load_existing_manifest(manifest_path)
if existing:
done_by_file.update(existing)
project, art_style = prev_project, prev_style
reused = sum(1 for f in assets if f in existing)
gone = len(existing) - reused
print(
f"[SF Claude Library Builder] Found {manifest_name}: reusing "
f"{reused} existing description(s)"
+ (f", dropping {gone} for deleted file(s)" if gone else "")
+ "."
)
# A checkpoint from an interrupted run is newer than the manifest, so it wins.
key = checkpoint_key(mode, manifest_name, system_prompt, project_notes)
checkpoint = load_checkpoint(root, key)
if checkpoint:
for entry in checkpoint.get("done_assets", []):
if entry.get("file"):
done_by_file[entry["file"]] = entry
project = checkpoint.get("project") or project
art_style = checkpoint.get("art_style") or art_style
print(
f"[SF Claude Library Builder] Resuming an interrupted run — "
f"{len(done_by_file)}/{len(assets)} asset(s) already catalogued."
)
todo = sum(1 for f in assets if f not in done_by_file)
if todo == 0:
print("[SF Claude Library Builder] Nothing new to catalogue.")
else:
print(f"[SF Claude Library Builder] {todo} asset(s) to catalogue.")
# Claude only ever reads images and replies with JSON; the node writes the
# manifest itself, and the Write tool is never offered. Bash is needed
# only to move/rename files in the organise modes.
tools = "Read" if mode == MODE_MANIFEST else "Read,Bash"
batches = list(chunk(assets, max(1, batch_size)))
total_cost = 0.0
started = time.time()
def fail(message):
"""Stop the run, leaving finished batches safely checkpointed."""
save_checkpoint(root, key, project, art_style, list(done_by_file.values()))
raise RuntimeError(
f"{message} {len(done_by_file)}/{len(assets)} asset(s) are saved in a "
f"checkpoint — rerun with the same settings to resume rather than "
f"start over."
)
def run_batch(files, label):
"""One Claude call. Returns (parsed reply, cost, turns)."""
established = (project, art_style) if project and art_style else None
command = [
binary,
"-p",
build_batch_instruction(
mode, files, len(assets), project_notes, established, out_dir
),
"--output-format",
"json",
"--allowedTools",
tools,
]
if system_prompt.strip():
command += ["--append-system-prompt", system_prompt.strip()]
if model != "default":
command += ["--model", model]
try:
completed = subprocess.run(
command,
cwd=root,
capture_output=True,
text=True,
timeout=timeout_seconds,
stdin=subprocess.DEVNULL,
)
except subprocess.TimeoutExpired:
fail(f"Batch {label} did not finish within {timeout_seconds}s.")
if completed.returncode != 0:
detail = (completed.stderr or completed.stdout or "").strip()[:500]
fail(f"Batch {label} failed (exit {completed.returncode}). {detail}")
try:
payload = json.loads(completed.stdout)
except json.JSONDecodeError:
fail(f"Batch {label}: unreadable response: {completed.stdout.strip()[:300]}")
if payload.get("is_error"):
fail(f"Batch {label} reported an error: {payload.get('result', 'unknown')}.")
# May raise BatchParseError, which catalogue() retries by splitting.
data = extract_json(payload.get("result", ""))
return data, payload.get("total_cost_usd") or 0.0, payload.get("num_turns", "?")
def catalogue(files, label):
"""Catalogue `files`, halving and retrying if the reply comes back cut off.
Each piece that succeeds is merged and checkpointed immediately, so a
later failure never costs work already paid for.
"""
nonlocal project, art_style, total_cost
try:
data, cost, turns = run_batch(files, label)
except BatchParseError as exc:
if len(files) == 1:
fail(
f"Batch {label}: {exc}. This is a single asset "
f"({files[0]}), so it cannot be split any further."
)
half = len(files) // 2
print(
f"[SF Claude Library Builder] Batch {label}: {exc}. "
f"Retrying as two batches of {half} and {len(files) - half}."
)
catalogue(files[:half], f"{label}a")
catalogue(files[half:], f"{label}b")
return
total_cost += cost
if project is None:
project = data.get("project", "Untitled project")
art_style = data.get("art_style", "")
expected = set(files)
for entry in data.get("assets") or []:
raw = entry.get("file")
if not raw:
continue
entry["file"] = canonicalize(raw, expected)
done_by_file[entry["file"]] = entry
save_checkpoint(root, key, project, art_style, list(done_by_file.values()))
print(
f"[SF Claude Library Builder] Batch {label} done: {turns} turns, "
f"${cost:.2f}. Running total: {len(done_by_file)}/{len(assets)} "
f"asset(s), ${total_cost:.2f}."
)
skipped = [f for f in files if f not in done_by_file]
if skipped:
print(
f"[SF Claude Library Builder] Batch {label}: {len(skipped)} file(s) "
f"came back undescribed; a rerun will pick them up."
)
for batch_num, batch_files in enumerate(batches, start=1):
remaining = [f for f in batch_files if f not in done_by_file]
if not remaining:
continue # fully covered by the checkpoint already
print(
f"[SF Claude Library Builder] Batch {batch_num}/{len(batches)} "
f"({len(remaining)} asset(s))..."
)
catalogue(remaining, f"{batch_num}/{len(batches)}")
elapsed = time.time() - started
# Assemble the final manifest in the library's original scan order.
final_assets = [done_by_file[f] for f in assets if f in done_by_file]
manifest_data = {
"schema": SCHEMA_VERSION,
"project": project or "Untitled project",
"art_style": art_style or "",
"generated": time.strftime("%Y-%m-%d"),
"assets": final_assets,
}
manifest_text = json.dumps(manifest_data, indent=2)
if write_manifest:
os.makedirs(manifest_root, exist_ok=True)
with open(manifest_path, "w", encoding="utf-8") as f:
f.write(manifest_text)
clear_checkpoint(root)
counts = {}
for entry in final_assets:
counts[entry.get("category", "?")] = counts.get(entry.get("category", "?"), 0) + 1
newly_done = max(0, len(final_assets) - reused)
report = "\n".join(
[
f"mode: {mode}",
f"scanned: {len(assets)} file(s) in {root}",
f"in manifest: {len(final_assets)} asset(s)",
f"reused: {reused} already described, {newly_done} newly catalogued",
"categories: " + (", ".join(f"{k} x{v}" for k, v in sorted(counts.items())) or "none"),
f"art style: {manifest_data['art_style'] or '(not set)'}",
"manifest: " + (manifest_path if write_manifest else "returned as text, not saved"),
f"took: {elapsed:.0f}s, ${total_cost:.2f} total",
]
)
print(
f"[SF Claude Library Builder] Done: {len(final_assets)}/{len(assets)} asset(s), "
f"{elapsed:.0f}s, ${total_cost:.2f}."
)
if len(final_assets) < len(assets):
report += f"\nWARNING: {len(assets) - len(final_assets)} file(s) were not catalogued."
return (manifest_text, report)
NODE_CLASS_MAPPINGS = {"SFClaudeLibraryBuilder": SFClaudeLibraryBuilder}
NODE_DISPLAY_NAME_MAPPINGS = {"SFClaudeLibraryBuilder": "SF Claude Library Builder"}
+3 -2
View File
@@ -156,8 +156,9 @@ A row is treated as finished when its **status_col** cell contains any text at
all. Write `done` next to a prompt in the sheet and the next run skips it; clear
the cell and it gets queued again. Scanning stops at the first empty prompt cell.
Press **Refresh sheet** after editing the sheet in your browser to see the
updated counts.
The sheet is re-read fresh on every run, so edits you make in the browser are
always picked up. **Refresh sheet** is optional — it reports how many prompts
are pending without having to run the graph.
"""
@classmethod
+65 -34
View File
@@ -1,14 +1,54 @@
import configparser
import json
import os
from .wavespeed_api.client import WaveSpeedClient
PACK_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
CUSTOM_NODES_DIR = os.path.dirname(PACK_DIR)
def _from_ini(path):
if not os.path.isfile(path):
return ""
config = configparser.ConfigParser()
config.read(path)
return config.get("API", "api_key", fallback="").strip()
def _from_official_pack():
"""The key saved by WaveSpeed's own ComfyUI pack, so one key serves both."""
path = os.path.join(CUSTOM_NODES_DIR, "wavespeed-comfyui", "config.json")
if not os.path.isfile(path):
return ""
try:
with open(path, encoding="utf-8") as f:
return str(json.load(f).get("api_key") or "").strip()
except (OSError, ValueError):
return ""
def resolve_api_key(widget_value):
"""Returns (key, where it came from). First non-empty source wins."""
sources = [
("the api_key field on this node", lambda: (widget_value or "").strip()),
("comfyui-sf-nodes/config.ini", lambda: _from_ini(os.path.join(PACK_DIR, "config.ini"))),
("the WAVESPEED_API_KEY environment variable", lambda: os.environ.get("WAVESPEED_API_KEY", "").strip()),
("the official WaveSpeed pack's config.json", _from_official_pack),
]
for label, read in sources:
key = read()
if key:
return key, label
return "", None
class SFWaveSpeedClient:
"""
WaveSpeed AI API Client Node
This node creates a client for connecting to the WaveSpeed AI API.
Leave api_key empty to reuse a key saved elsewhere — see the tooltip.
"""
def __init__(self):
@@ -18,7 +58,19 @@ class SFWaveSpeedClient:
def INPUT_TYPES(s):
return {
"required": {
"api_key": ("STRING", {"multiline": False, "default": ""}),
"api_key": (
"STRING",
{
"multiline": False,
"default": "",
"tooltip": (
"Leave empty (recommended) to use, in order: comfyui-sf-nodes/config.ini, "
"the WAVESPEED_API_KEY environment variable, or the key already saved by "
"WaveSpeed's official ComfyUI pack. A key typed here is saved into the "
"workflow file, so it travels with any workflow you share."
),
},
),
},
}
@@ -34,44 +86,23 @@ class SFWaveSpeedClient:
Create a WaveSpeed AI API client
Args:
api_key: WaveSpeed AI API key
api_key: WaveSpeed AI API key; empty to look it up elsewhere
Returns:
WaveSpeedAPI: WaveSpeed AI API client
dict holding the resolved key and where it came from
"""
wavespeed_api_key = ""
if api_key == "":
# Try to read from config.ini
try:
current_dir = os.path.dirname(os.path.abspath(__file__))
parent_dir = os.path.dirname(current_dir)
config_path = os.path.join(parent_dir, "config.ini")
if os.path.exists(config_path):
config = configparser.ConfigParser()
config.read(config_path)
wavespeed_api_key = config.get("API", "api_key", fallback="")
if not wavespeed_api_key:
# Try environment variable
wavespeed_api_key = os.environ.get("WAVESPEED_API_KEY", "")
if not wavespeed_api_key:
raise ValueError(
"API_KEY is empty. Please provide an API key or set it in config.ini"
)
except Exception as e:
raise ValueError(f"Unable to find API_KEY: {str(e)}")
else:
wavespeed_api_key = api_key
return ({"api_key": wavespeed_api_key},)
key, source = resolve_api_key(api_key)
if not key:
raise ValueError(
"No WaveSpeed API key found. Enter one on this node, add it to "
"comfyui-sf-nodes/config.ini, set WAVESPEED_API_KEY, or save it in "
"WaveSpeed's official ComfyUI pack."
)
# Never log the key itself — only where it was found.
print(f"[SF WaveSpeed Client] Using the API key from {source}.")
return ({"api_key": key, "source": source},)
# Node registration
NODE_CLASS_MAPPINGS = {"SFWaveSpeedClient": SFWaveSpeedClient}
NODE_DISPLAY_NAME_MAPPINGS = {"SFWaveSpeedClient": "SF WaveSpeed Client"}
+245
View File
@@ -0,0 +1,245 @@
# ABOUTME: Tripo P2 image-to-3D through the WaveSpeed API, billed to a WaveSpeed account
# ABOUTME: Emits GLB/FBX File3D outputs compatible with ComfyUI's Preview 3D and Save nodes
import os
import time
from urllib.parse import urlparse
import requests
from .wavespeed_api.client import WaveSpeedClient
from .wavespeed_api.utils import tensor2images
try:
from comfy_api.latest import Types
File3D = Types.File3D
except ImportError: # older ComfyUI without 3D file types
File3D = None
ENDPOINT = "/api/v3/tripo3d/p2/image-to-3d"
RESULT_PATH = "/api/v3/predictions/{id}/result"
TEXTURE_LEVELS = ["standard", "fast", "detailed", "extreme", "none"]
TEXTURE_VERSIONS = ["v3.5-20260815", "v3.0-20250812", "v2.5-20250123"]
ORIENTATION_UNSET = "unset (recommended)"
ORIENTATIONS = [ORIENTATION_UNSET, "+x", "-x", "+y", "-y"]
TERMINAL_FAILURES = {"failed", "cancelled", "timeout", "deleted"}
def build_payload(image_url, quad, face_limit, texture, pbr, texture_version,
delight, auto_size, export_uv, export_orientation, model_seed, texture_seed):
"""The request body. Unused options are omitted rather than sent as null,
as WaveSpeed's documentation asks."""
if face_limit != -1:
ceiling = 25000 if quad else 50000
if not 48 <= face_limit <= ceiling:
raise ValueError(
f"face_limit must be -1 (adaptive) or between 48 and {ceiling}"
f"{' — quad meshes cap at 25,000' if quad else ''}."
)
if texture == "fast" and texture_version != "v3.5-20260815":
raise ValueError("texture 'fast' requires texture_version v3.5-20260815.")
textured = texture != "none"
payload = {
"image": image_url,
"quad": quad,
"texture": textured,
# PBR implies textures, so it is switched off along with them.
"pbr": bool(pbr and textured),
"auto_size": auto_size,
"export_uv": export_uv,
}
if textured:
payload["texture_quality"] = texture
payload["texture_version"] = texture_version
payload["delight"] = delight
if face_limit != -1:
payload["face_limit"] = face_limit
if export_orientation != ORIENTATION_UNSET:
payload["export_orientation"] = export_orientation
if model_seed != -1:
payload["model_seed"] = model_seed
if texture_seed != -1 and textured:
payload["texture_seed"] = texture_seed
return payload
def pick_model_url(outputs):
"""The model file URL out of a result's `outputs`, which may be a list or a string."""
candidates = outputs if isinstance(outputs, list) else [outputs]
urls = [u for u in candidates if isinstance(u, str) and u.startswith("http")]
for url in urls:
if urlparse(url).path.lower().endswith((".glb", ".fbx")):
return url
if urls:
return urls[0]
raise RuntimeError(f"No model URL in the result: {outputs!r}")
def check_interrupted():
try:
import comfy.model_management as mm
except ImportError:
return
mm.throw_exception_if_processing_interrupted()
def output_dir():
try:
import folder_paths
base = folder_paths.get_output_directory()
except ImportError:
base = os.getcwd()
path = os.path.join(base, "3d")
os.makedirs(path, exist_ok=True)
return path
class SFWaveSpeedTripoP2ImageTo3D:
"""
Tripo P2 image-to-3D via WaveSpeed — the same model as ComfyUI's partner
node, billed to your WaveSpeed account instead of ComfyUI credits.
Tripo returns FBX when quad topology is on and GLB when it is off, so the
matching output is populated and the other is empty.
"""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"client": ("WAVESPEED_AI_API_CLIENT",),
"image": ("IMAGE", {"tooltip": "Reference image. Only the first frame of a batch is used."}),
"quad": (
"BOOLEAN",
{"default": False, "tooltip": "Quad topology instead of triangles. Output becomes FBX."},
),
"face_limit": (
"INT",
{
"default": -1,
"min": -1,
"max": 50000,
"step": 100,
"tooltip": "Target face count. -1 lets Tripo choose. 48-50,000, or up to 25,000 with quad.",
},
),
"texture": (
TEXTURE_LEVELS,
{"default": "standard", "tooltip": "'none' gives untextured geometry. Higher levels cost more."},
),
"pbr": ("BOOLEAN", {"default": True, "tooltip": "PBR material maps. Ignored when texture is 'none'."}),
},
"optional": {
"texture_version": (
TEXTURE_VERSIONS,
{"default": TEXTURE_VERSIONS[0], "tooltip": "'fast' texture requires v3.5."},
),
"delight": (
"BOOLEAN",
{"default": True, "tooltip": "Strip lighting baked into the source image before texturing."},
),
"auto_size": ("BOOLEAN", {"default": False, "tooltip": "Scale the model to real-world metres."}),
"export_uv": ("BOOLEAN", {"default": True, "tooltip": "Generate UVs. Off is faster and smaller."}),
"export_orientation": (
ORIENTATIONS,
{
"default": ORIENTATION_UNSET,
"tooltip": (
"Forward axis. Leave unset if you will rig, retexture or convert the "
"model — Tripo warns those steps can silently come out mis-rotated."
),
},
),
"model_seed": (
"INT",
{"default": -1, "min": -1, "max": 2147483647, "tooltip": "-1 for random geometry."},
),
"texture_seed": (
"INT",
{"default": -1, "min": -1, "max": 2147483647, "tooltip": "-1 for random texturing."},
),
"timeout_seconds": (
"INT",
{"default": 900, "min": 60, "max": 3600, "step": 30},
),
},
}
RETURN_TYPES = ("FILE_3D_GLB", "FILE_3D_FBX", "STRING", "STRING")
RETURN_NAMES = ("GLB", "FBX", "model_file", "model_url")
OUTPUT_TOOLTIPS = (
"Populated when quad is off.",
"Populated when quad is on.",
"Absolute path of the downloaded model in ComfyUI's output/3d folder.",
"WaveSpeed CDN link to the model.",
)
FUNCTION = "generate"
CATEGORY = "Stillfront/WaveSpeed"
OUTPUT_NODE = True
def generate(self, client, image, quad, face_limit, texture, pbr,
texture_version=TEXTURE_VERSIONS[0], delight=True, auto_size=False,
export_uv=True, export_orientation=ORIENTATION_UNSET,
model_seed=-1, texture_seed=-1, timeout_seconds=900):
api = WaveSpeedClient(api_key=client["api_key"])
try:
image_url = api.upload_file(tensor2images(image)[0])
except Exception as e:
if "401" in str(e):
source = client.get("source", "the SF WaveSpeed Client node")
raise RuntimeError(
f"WaveSpeed rejected the API key, which came from {source}. "
f"Check it on wavespeed.ai under API Keys, or clear the api_key field "
f"on SF WaveSpeed Client to fall back to a key saved elsewhere."
) from e
raise
payload = build_payload(
image_url, quad, face_limit, texture, pbr, texture_version, delight,
auto_size, export_uv, export_orientation, model_seed, texture_seed,
)
task = api.post(ENDPOINT, payload)
task_id = task.get("id")
if not task_id:
raise RuntimeError(f"WaveSpeed did not return a task id: {task}")
print(f"[SF Tripo P2] Submitted {task_id} (quad={quad}, faces={face_limit}, texture={texture}).")
started = time.time()
while True:
check_interrupted()
result = api.get(RESULT_PATH.format(id=task_id))
status = result.get("status")
if status == "completed":
break
if status in TERMINAL_FAILURES:
raise RuntimeError(f"Tripo P2 task {status}: {result.get('error') or result}")
if time.time() - started > timeout_seconds:
raise RuntimeError(f"Tripo P2 task {task_id} still '{status}' after {timeout_seconds}s.")
time.sleep(3)
url = pick_model_url(result.get("outputs"))
ext = os.path.splitext(urlparse(url).path)[1].lower() or (".fbx" if quad else ".glb")
path = os.path.join(output_dir(), f"sf_tripo_p2_{task_id}{ext}")
response = requests.get(url, timeout=300)
response.raise_for_status()
with open(path, "wb") as f:
f.write(response.content)
print(f"[SF Tripo P2] Done in {time.time() - started:.0f}s -> {path}")
glb = fbx = None
if File3D is not None:
model = File3D(path)
glb = model if ext == ".glb" else None
fbx = model if ext == ".fbx" else None
return (glb, fbx, path, url)
NODE_CLASS_MAPPINGS = {"SFWaveSpeedTripoP2ImageTo3D": SFWaveSpeedTripoP2ImageTo3D}
NODE_DISPLAY_NAME_MAPPINGS = {"SFWaveSpeedTripoP2ImageTo3D": "SF WaveSpeed Tripo P2 Image to 3D"}
+1 -1
View File
@@ -1,7 +1,7 @@
[project]
name = "comfyui-sf-nodes"
description = "Custom nodes for ComfyUI including LLM Chat with support for Claude, Gemini, and OpenAI models, WaveSpeed AI image/video generation, VertexAI integration, and workflow utilities"
version = "1.0.8"
version = "1.6.1"
license = { file = "LICENSE" }
dependencies = [
"requests>=2.31.0",
+85
View File
@@ -0,0 +1,85 @@
/**
* SF Claude Code — grows the image input list on demand.
*
* The Python side declares image_1..image_16 as optional inputs. This keeps
* only as many slots visible as are in use, plus one spare to connect into.
*/
import { app } from "../../../scripts/app.js";
const NODE_NAME = "SFClaudeCode";
const MAX_IMAGES = 16;
function imageSlotIndex(node, n) {
return (node.inputs ?? []).findIndex((input) => input.name === `image_${n}`);
}
function syncImageSlots(node) {
if (!node.inputs) {
return;
}
// Highest numbered image slot that currently has something plugged in.
let lastUsed = 0;
for (const input of node.inputs) {
const match = input.name?.match(/^image_(\d+)$/);
if (match && input.link != null) {
lastUsed = Math.max(lastUsed, parseInt(match[1], 10));
}
}
// Show every used slot, plus one empty spare to drag into.
const wanted = Math.min(lastUsed + 1, MAX_IMAGES);
for (let n = 1; n <= wanted; n++) {
if (imageSlotIndex(node, n) === -1) {
node.addInput(`image_${n}`, "IMAGE");
}
}
// Drop trailing spares, but never one that is still connected.
for (let n = MAX_IMAGES; n > wanted; n--) {
const index = imageSlotIndex(node, n);
if (index !== -1 && node.inputs[index].link == null) {
node.removeInput(index);
}
}
node.setSize(node.computeSize());
node.setDirtyCanvas(true, true);
}
app.registerExtension({
name: "Stillfront.ClaudeCode",
async beforeRegisterNodeDef(nodeType, nodeData) {
if (nodeData.name !== NODE_NAME) {
return;
}
const onNodeCreated = nodeType.prototype.onNodeCreated;
nodeType.prototype.onNodeCreated = function () {
const result = onNodeCreated ? onNodeCreated.apply(this, arguments) : undefined;
syncImageSlots(this);
return result;
};
// Re-sync after a saved workflow restores its connections.
const onConfigure = nodeType.prototype.onConfigure;
nodeType.prototype.onConfigure = function () {
const result = onConfigure ? onConfigure.apply(this, arguments) : undefined;
requestAnimationFrame(() => syncImageSlots(this));
return result;
};
const onConnectionsChange = nodeType.prototype.onConnectionsChange;
nodeType.prototype.onConnectionsChange = function (type, index, connected, linkInfo, ioSlot) {
const result = onConnectionsChange
? onConnectionsChange.apply(this, arguments)
: undefined;
// Let litegraph finish updating link state before recounting.
requestAnimationFrame(() => syncImageSlots(this));
return result;
};
},
});
+221
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@@ -0,0 +1,221 @@
/**
* SF Save Folder Picker — adds a folder browser to ComfyUI's "Save workflow"
* dialog, so a workflow can be saved into a subfolder by clicking the folder
* and typing only the name, instead of typing the whole path.
*
* It augments the native dialog rather than replacing it: ComfyUI still does
* the actual saving, so tab tracking and overwrite confirmation are unchanged.
* Picking a folder only rewrites the path in the dialog's own input.
*/
import { app } from "../../../scripts/app.js";
import { api } from "../../../scripts/api.js";
const SETTING_ID = "Stillfront.SaveFolderPicker";
const SAVE_COMMANDS = ["Comfy.SaveWorkflow", "Comfy.SaveWorkflowAs"];
const ROOT = "workflows";
// True only while a Save command is running, so the same prompt dialog used
// for renaming or exporting is left alone.
let savePending = false;
function enabled() {
try {
return app.extensionManager?.setting?.get(SETTING_ID) !== false;
} catch {
return true;
}
}
async function fetchFolders() {
const res = await api.fetchApi(`/v2/userdata?path=${encodeURIComponent(ROOT)}`);
if (!res.ok) {
throw new Error(`folder list failed (${res.status})`);
}
const entries = await res.json();
return entries
.filter((e) => e.type === "directory")
.map((e) => e.path.replace(/^workflows\/?/, ""))
.filter((p) => p && !p.split("/").some((part) => part.startsWith(".")))
.sort((a, b) => a.localeCompare(b, undefined, { sensitivity: "base" }));
}
function el(tag, style = "", text = "") {
const node = document.createElement(tag);
if (style) node.style.cssText = style;
if (text) node.textContent = text;
return node;
}
function splitPath(value) {
const i = value.lastIndexOf("/");
return i === -1 ? { folder: "", name: value } : { folder: value.slice(0, i), name: value.slice(i + 1) };
}
function setInput(input, folder) {
const { name } = splitPath(input.value);
input.value = folder ? `${folder}/${name}` : name;
input.dispatchEvent(new Event("input", { bubbles: true }));
input.focus();
// Select just the name, ready to be typed over.
const start = input.value.length - name.length;
input.setSelectionRange(start, input.value.length);
}
function buildPicker(input, folders) {
const expanded = new Set();
let selected = splitPath(input.value).folder;
// Open the branch leading to the folder the dialog started in.
selected.split("/").reduce((acc, part) => {
const path = acc ? `${acc}/${part}` : part;
if (part) expanded.add(path);
return path;
}, "");
const box = el(
"div",
"border:1px solid rgba(128,128,128,.35);border-radius:6px;margin:4px 0 8px;"
);
const header = el(
"div",
"display:flex;align-items:center;justify-content:space-between;padding:6px 8px;" +
"font-size:12px;opacity:.75;border-bottom:1px solid rgba(128,128,128,.25);"
);
header.appendChild(el("span", "", "Save into folder"));
const newBtn = el(
"button",
"background:none;border:1px solid rgba(128,128,128,.4);border-radius:4px;" +
"padding:2px 8px;font-size:12px;color:inherit;cursor:pointer;",
"+ New folder"
);
newBtn.type = "button";
header.appendChild(newBtn);
box.appendChild(header);
const list = el("div", "max-height:260px;overflow-y:auto;padding:4px 0;font-size:13px;");
box.appendChild(list);
const hasChildren = (path) => folders.some((f) => f.startsWith(`${path}/`));
const childrenOf = (parent) =>
folders.filter((f) => {
const { folder } = splitPath(f);
return folder === parent;
});
function row(path, depth) {
const label = path ? splitPath(path).name : `${ROOT} (top level)`;
const r = el(
"div",
`display:flex;align-items:center;gap:4px;padding:3px 8px 3px ${8 + depth * 16}px;` +
"cursor:pointer;border-radius:4px;user-select:none;" +
(path === selected ? "background:rgba(66,133,244,.28);" : "")
);
const caret = el("span", "width:14px;display:inline-block;text-align:center;opacity:.7;");
if (path && hasChildren(path)) {
caret.textContent = expanded.has(path) ? "▾" : "▸";
caret.addEventListener("click", (e) => {
e.stopPropagation();
expanded.has(path) ? expanded.delete(path) : expanded.add(path);
render();
});
}
r.appendChild(caret);
r.appendChild(el("span", "", `📁 ${label}`));
r.addEventListener("mouseenter", () => {
if (path !== selected) r.style.background = "rgba(128,128,128,.15)";
});
r.addEventListener("mouseleave", () => {
if (path !== selected) r.style.background = "";
});
r.addEventListener("click", () => {
selected = path;
setInput(input, path);
render();
});
return r;
}
function addBranch(parent, depth) {
for (const child of childrenOf(parent)) {
list.appendChild(row(child, depth));
if (expanded.has(child)) addBranch(child, depth + 1);
}
}
function render() {
list.replaceChildren(row("", 0));
addBranch("", 1);
}
newBtn.addEventListener("click", () => {
const where = selected ? `inside "${selected}"` : "at the top level";
const name = window.prompt(`New folder name (${where}):`);
const clean = (name || "").trim().replace(/[\\/]+/g, "-");
if (!clean) return;
const path = selected ? `${selected}/${clean}` : clean;
// The folder is created on disk when the workflow is saved into it.
if (!folders.includes(path)) folders.push(path);
folders.sort((a, b) => a.localeCompare(b, undefined, { sensitivity: "base" }));
if (selected) expanded.add(selected);
selected = path;
setInput(input, path);
render();
});
render();
return box;
}
async function inject(dialog) {
if (dialog.dataset.sfFolderPicker) return;
dialog.dataset.sfFolderPicker = "1";
const input = dialog.querySelector("input");
if (!input) return;
let picker;
try {
picker = buildPicker(input, await fetchFolders());
} catch (e) {
picker = el("div", "font-size:12px;opacity:.7;margin:4px 0;", `Folder list unavailable: ${e.message}`);
}
input.parentElement.insertBefore(picker, input);
}
app.registerExtension({
name: "Stillfront.SaveFolderPicker",
settings: [
{
id: SETTING_ID,
category: ["Stillfront", "Workflows", "Folder picker in Save dialog"],
name: "Show a folder browser in the Save workflow dialog",
type: "boolean",
defaultValue: true,
},
],
async setup() {
const commands = app.extensionManager?.command?.commands || [];
for (const id of SAVE_COMMANDS) {
const command = commands.find((c) => c.id === id);
if (!command) continue;
const original = command.function;
command.function = async function () {
savePending = true;
try {
return await original.apply(this, arguments);
} finally {
savePending = false;
}
};
}
new MutationObserver(() => {
if (!savePending || !enabled()) return;
const dialog = document.querySelector(".prompt-dialog-content:not([data-sf-folder-picker])");
if (dialog) inject(dialog);
}).observe(document.body, { childList: true, subtree: true });
},
});