57_WolveandClaude Opus 4.7
f6f5690fcd
Bug: after generate_image surfaced an image via the files event, the
next edit_image call returned 'No image found in the chat'. The image
was attached to the assistant's message, but _extract_attached_image
only scanned the user's __files__ param and image_url content blocks
on user messages — it never looked at messages.files for any role.
Fix: rewrite extraction to scan messages[].files in reverse for ALL
roles, so an assistant-emitted image from a prior tool call is found
the same way as a user-attached upload. Use Open WebUI's internal
Files.get_file_by_id when the file dict has an id, so we get raw
bytes from disk without going through the auth-protected
/api/v1/files/{id}/content endpoint. Old path-key and URL-fetch
paths kept as fallbacks.
Refactored shared helpers _file_dict_is_image and _read_file_dict
out of the loop to keep the search logic readable.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
861 lines
36 KiB
Python
861 lines
36 KiB
Python
"""
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title: Smart Image Generator & Editor (ComfyUI)
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author: ai-stack
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version: 0.7.0
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description: Generate or edit images via ComfyUI with automatic SDXL
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checkpoint routing. Two methods — generate_image (txt2img) and
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edit_image (img2img on the user's most recently attached image). The
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LLM picks (or auto-detects) the right model — photoreal, Pony
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score-tag, NoobAI/Illustrious furry, etc. — and each style ships
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with the creator-recommended sampler, scheduler, CFG, steps, CLIP
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skip, prompt-prefix dialect, and negatives. The image is uploaded
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to Open WebUI's file store and surfaced via a `files` event (the
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canonical pattern used by Open WebUI's own image-gen path); the
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function return is a short confirmation so the LLM doesn't try to
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describe or re-emit the image.
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required_open_webui_version: 0.5.0
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"""
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import asyncio
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import base64
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import inspect
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import io
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import re
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import time
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import uuid
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from typing import Awaitable, Callable, Literal, Optional
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import aiohttp
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from pydantic import BaseModel, Field
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# Open WebUI's runtime — only available when the tool is loaded inside the
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# Open WebUI process. Guarded so the module still imports for standalone
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# linting/testing; if the imports fail at runtime, _push_image_to_chat
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# falls back to emitting a markdown data-URI message.
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try:
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from fastapi import UploadFile
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from open_webui.models.files import Files
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from open_webui.models.users import Users
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from open_webui.routers.files import upload_file_handler
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_OPENWEBUI_RUNTIME = True
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except ImportError:
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_OPENWEBUI_RUNTIME = False
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StyleName = Literal[
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"photo", "juggernaut", "pony", "general",
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"furry-nai", "furry-noob", "furry-il",
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]
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# ─────────────────────────────────────────────────────────────────────────────
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# Per-style settings — sampler/scheduler/cfg/steps/clip_skip/prefix/negatives
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# come from each model's creator page on Civitai. Three prefix dialects in
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# play: photoreal (no prefix, natural language), Pony score chain (REQUIRED
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# for any Pony-derived checkpoint), and Booru quality tags (NoobAI /
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# Illustrious lineage). Never cross-contaminate.
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# ─────────────────────────────────────────────────────────────────────────────
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STYLES = {
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"photo": {
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"ckpt": "CyberRealisticXLPlay_V8.0_FP16.safetensors",
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"sampler": "dpmpp_2m_sde",
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"scheduler": "karras",
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"cfg": 4.0,
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"steps": 28,
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"clip_skip": 1,
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"prefix": "", # natural language only — no quality tags
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"negative": (
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"cartoon, drawing, illustration, anime, manga, painting, sketch, "
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"render, 3d, cgi, watercolor, plastic skin, doll-like, oversaturated, "
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"lowres, blurry, jpeg artifacts, noisy, grainy, low quality, worst quality, "
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"bad anatomy, deformed, mutated, extra limbs, extra fingers, missing fingers, "
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"fused fingers, malformed hands, asymmetric face, "
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"watermark, signature, text, logo, label, username"
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),
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},
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"juggernaut": {
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"ckpt": "Juggernaut-XL_v9_RunDiffusionPhoto_v2.safetensors",
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"sampler": "dpmpp_2m_sde",
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"scheduler": "karras",
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"cfg": 4.5,
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"steps": 35,
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"clip_skip": 1,
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"prefix": "", # natural language only
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"negative": (
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"cartoon, drawing, illustration, anime, manga, painting, sketch, "
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"render, 3d, cgi, plastic skin, washed out, oversaturated, "
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"lowres, blurry, jpeg artifacts, low quality, worst quality, "
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"bad anatomy, deformed, mutated, extra limbs, extra fingers, missing fingers, "
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"fused fingers, malformed hands, "
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"watermark, signature, text, logo, username"
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),
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},
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"pony": {
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"ckpt": "ponyDiffusionV6XL_v6StartWithThisOne.safetensors",
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"sampler": "euler_ancestral",
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"scheduler": "normal",
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"cfg": 7.5,
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"steps": 25,
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"clip_skip": 2,
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# REQUIRED — the full chain. Just `score_9` alone is much weaker.
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"prefix": "score_9, score_8_up, score_7_up, score_6_up, score_5_up, score_4_up, ",
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# Pony's creator notes negatives are usually unnecessary; conservative
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# baseline only. Source-toggle tags (source_pony/furry/anime/cartoon)
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# are intentionally omitted — they exclude entire content domains.
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"negative": (
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"score_6, score_5, score_4, "
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"worst quality, low quality, lowres, blurry, jpeg artifacts, noisy, "
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"bad anatomy, bad proportions, bad hands, extra digit, fewer digits, "
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"fused fingers, malformed limbs, deformed, ugly, "
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"censored, monochrome, "
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"watermark, signature, text, logo, artist name, patreon username, twitter username"
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),
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},
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"general": {
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"ckpt": "talmendoxlSDXL_v11Beta.safetensors",
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"sampler": "dpmpp_2m",
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"scheduler": "karras",
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"cfg": 8.0, # Talmendo wants notably higher CFG than the others
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"steps": 30,
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"clip_skip": 2,
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"prefix": "", # creator says don't push "masterpiece" — fights the amateur aesthetic
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"negative": (
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"lowres, blurry, jpeg artifacts, noisy, grainy, low quality, worst quality, "
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"bad anatomy, deformed, mutated, extra limbs, missing fingers, fused fingers, "
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"malformed hands, ugly, "
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"watermark, signature, text, logo"
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),
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},
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"furry-nai": {
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"ckpt": "reedFURRYMixSDXL_v23nai.safetensors",
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"sampler": "euler_ancestral",
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"scheduler": "normal",
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"cfg": 5.0,
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"steps": 30,
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"clip_skip": 2,
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"prefix": (
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"masterpiece, best quality, high quality, good quality, "
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"detailed eyes, highres, absurdres, furry, "
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),
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"negative": (
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"human, realistic, photorealistic, 3d, cgi, "
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"worst quality, bad_quality, normal quality, lowres, "
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"anatomical nonsense, bad anatomy, interlocked fingers, extra fingers, "
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"bad_feet, bad_hands, deformed anatomy, bad proportions, "
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"censored, simple background, transparent, face backlighting, "
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"watermark, signature, text, logo, username, jpeg artifacts"
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),
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},
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"furry-noob": {
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"ckpt": "indigoVoidFurryFusedXL_noobaiV32.safetensors",
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"sampler": "euler_ancestral", # creator: other samplers won't work
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"scheduler": "normal",
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"cfg": 4.5,
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"steps": 20,
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"clip_skip": 2,
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"prefix": (
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"masterpiece, best quality, perfect quality, absurdres, newest, "
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"very aesthetic, vibrant colors, "
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),
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"negative": (
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"human, realistic, photorealistic, 3d, cgi, "
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"shiny skin, shiny clothing, "
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"worst quality, low quality, lowres, blurry, jpeg artifacts, noisy, "
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"bad anatomy, bad hands, mutated hands, bad proportions, "
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"extra digit, fewer digits, fused fingers, malformed limbs, deformed, ugly, "
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"watermark, signature, text, logo, username, artist signature"
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),
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},
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"furry-il": {
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"ckpt": "novaFurryXL_ilV170.safetensors",
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"sampler": "euler_ancestral",
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"scheduler": "normal",
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"cfg": 4.0,
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"steps": 30,
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"clip_skip": 2,
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# Illustrious wants `newest` in positive and `old`/`oldest` in negative
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# — these are year-bucket tags from the training set. `furry` and
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# `anthro` are universally helpful here.
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"prefix": (
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"masterpiece, best quality, amazing quality, very aesthetic, "
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"high resolution, ultra-detailed, absurdres, newest, furry, anthro, "
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),
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"negative": (
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"human, multiple tails, modern, recent, old, oldest, "
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"graphic, cartoon, painting, crayon, graphite, abstract, glitch, "
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"deformed, mutated, ugly, disfigured, long body, conjoined, "
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"lowres, bad anatomy, bad hands, missing fingers, extra digits, fewer digits, "
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"cropped, very displeasing, worst quality, bad quality, sketch, "
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"jpeg artifacts, signature, watermark, username, text, simple background, "
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"bad ai-generated"
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),
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},
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}
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DEFAULT_STYLE = "general"
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# First-match-wins keyword router used when the caller didn't pick a style.
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# Order matters — narrower patterns above broader ones.
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ROUTING_RULES = [
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# Pony score chain is the single strongest signal — Pony only
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(re.compile(r"\bscore_\d", re.I), "pony"),
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(re.compile(r"\bpony\b", re.I), "pony"),
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# NoobAI / Illustrious explicit mentions
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(re.compile(r"\b(noobai|noob)\b", re.I), "furry-noob"),
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(re.compile(r"\b(illustrious|ilxl)\b", re.I), "furry-il"),
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# Generic furry — defaults to NovaFurry (Illustrious lineage, current sweet spot)
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(re.compile(r"\b(furry|anthro|feral|kemono|fursona|species)\b", re.I), "furry-il"),
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# Photo / photoreal
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(re.compile(r"\b(juggernaut)\b", re.I), "juggernaut"),
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(re.compile(r"\b(photo|photograph|realistic|portrait|selfie|cinematic)\b", re.I), "photo"),
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# Generic anime / illustration → Pony covers anime well
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(re.compile(r"\b(anime|manga|2d|illustration)\b", re.I), "pony"),
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]
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def _route_style(prompt: str) -> str:
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for pattern, style in ROUTING_RULES:
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if pattern.search(prompt):
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return style
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return DEFAULT_STYLE
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def _seed_value(seed: int) -> int:
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return seed if seed > 0 else int(time.time() * 1000) % (2**31)
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def _build_txt2img(positive: str, negative: str, settings: dict,
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width: int, height: int, seed: int) -> dict:
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"""
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SDXL txt2img workflow. CLIP skip via CLIPSetLastLayer so the same graph
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handles skip 1 (-1) and skip 2 (-2).
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"""
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return {
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"3": {"class_type": "KSampler", "inputs": {
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"seed": _seed_value(seed),
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"steps": settings["steps"], "cfg": settings["cfg"],
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"sampler_name": settings["sampler"], "scheduler": settings["scheduler"],
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"denoise": 1.0,
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"model": ["4", 0], "positive": ["6", 0],
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"negative": ["7", 0], "latent_image": ["5", 0],
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}},
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"4": {"class_type": "CheckpointLoaderSimple",
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"inputs": {"ckpt_name": settings["ckpt"]}},
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"5": {"class_type": "EmptyLatentImage",
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"inputs": {"width": width, "height": height, "batch_size": 1}},
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"6": {"class_type": "CLIPTextEncode", "inputs": {"text": positive, "clip": ["10", 0]}},
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"7": {"class_type": "CLIPTextEncode", "inputs": {"text": negative, "clip": ["10", 0]}},
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"8": {"class_type": "VAEDecode", "inputs": {"samples": ["3", 0], "vae": ["4", 2]}},
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"9": {"class_type": "SaveImage",
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"inputs": {"filename_prefix": "smartgen", "images": ["8", 0]}},
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"10": {"class_type": "CLIPSetLastLayer",
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"inputs": {"stop_at_clip_layer": -settings["clip_skip"],
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"clip": ["4", 1]}},
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}
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def _build_inpaint(positive: str, negative: str, settings: dict,
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image_filename: str, mask_text: str,
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denoise: float, seed: int) -> dict:
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"""
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SDXL inpainting workflow with text-driven masking. Uses
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comfyui_segment_anything (GroundingDINO + SAM-HQ — installed by the
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Dockerfile) to derive a mask from `mask_text` (a noun phrase like
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"the dog's collar"), then SetLatentNoiseMask + KSampler repaint
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only that region. Everything outside the mask stays pixel-perfect.
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First inpaint downloads ~3 GB of SAM/GroundingDINO weights into
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/opt/comfyui/models/{sams,grounding-dino}/ — subsequent runs reuse
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them.
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"""
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return {
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"3": {"class_type": "KSampler", "inputs": {
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"seed": _seed_value(seed),
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"steps": settings["steps"], "cfg": settings["cfg"],
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"sampler_name": settings["sampler"], "scheduler": settings["scheduler"],
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"denoise": denoise,
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"model": ["4", 0], "positive": ["6", 0],
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"negative": ["7", 0], "latent_image": ["13", 0],
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}},
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"4": {"class_type": "CheckpointLoaderSimple",
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"inputs": {"ckpt_name": settings["ckpt"]}},
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"6": {"class_type": "CLIPTextEncode", "inputs": {"text": positive, "clip": ["10", 0]}},
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"7": {"class_type": "CLIPTextEncode", "inputs": {"text": negative, "clip": ["10", 0]}},
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"8": {"class_type": "VAEDecode", "inputs": {"samples": ["3", 0], "vae": ["4", 2]}},
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"9": {"class_type": "SaveImage",
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"inputs": {"filename_prefix": "smartinpaint", "images": ["8", 0]}},
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"10": {"class_type": "CLIPSetLastLayer",
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"inputs": {"stop_at_clip_layer": -settings["clip_skip"],
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"clip": ["4", 1]}},
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"11": {"class_type": "VAEEncode", "inputs": {"pixels": ["12", 0], "vae": ["4", 2]}},
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"12": {"class_type": "LoadImage", "inputs": {"image": image_filename}},
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"13": {"class_type": "SetLatentNoiseMask",
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"inputs": {"samples": ["11", 0], "mask": ["16", 1]}},
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"14": {"class_type": "SAMModelLoader (segment anything)",
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"inputs": {"model_name": "sam_hq_vit_h (2.57GB)"}},
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"15": {"class_type": "GroundingDinoModelLoader (segment anything)",
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"inputs": {"model_name": "GroundingDINO_SwinT_OGC (694MB)"}},
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"16": {"class_type": "GroundingDinoSAMSegment (segment anything)",
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"inputs": {
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"sam_model": ["14", 0],
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"grounding_dino_model": ["15", 0],
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"image": ["12", 0],
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"prompt": mask_text,
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"threshold": 0.3,
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}},
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}
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def _build_img2img(positive: str, negative: str, settings: dict,
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image_filename: str, denoise: float, seed: int) -> dict:
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"""
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SDXL img2img workflow. Loads `image_filename` (already uploaded to
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ComfyUI's /input/), VAE-encodes it to latent, and feeds that into the
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sampler at the requested denoise. Resolution is whatever the source
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image is — no resize.
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"""
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return {
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"3": {"class_type": "KSampler", "inputs": {
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"seed": _seed_value(seed),
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"steps": settings["steps"], "cfg": settings["cfg"],
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"sampler_name": settings["sampler"], "scheduler": settings["scheduler"],
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"denoise": denoise,
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"model": ["4", 0], "positive": ["6", 0],
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"negative": ["7", 0], "latent_image": ["11", 0],
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}},
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"4": {"class_type": "CheckpointLoaderSimple",
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"inputs": {"ckpt_name": settings["ckpt"]}},
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"6": {"class_type": "CLIPTextEncode", "inputs": {"text": positive, "clip": ["10", 0]}},
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"7": {"class_type": "CLIPTextEncode", "inputs": {"text": negative, "clip": ["10", 0]}},
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"8": {"class_type": "VAEDecode", "inputs": {"samples": ["3", 0], "vae": ["4", 2]}},
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"9": {"class_type": "SaveImage",
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"inputs": {"filename_prefix": "smartedit", "images": ["8", 0]}},
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"10": {"class_type": "CLIPSetLastLayer",
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"inputs": {"stop_at_clip_layer": -settings["clip_skip"],
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"clip": ["4", 1]}},
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"11": {"class_type": "VAEEncode", "inputs": {"pixels": ["12", 0], "vae": ["4", 2]}},
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"12": {"class_type": "LoadImage", "inputs": {"image": image_filename}},
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}
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def _file_dict_is_image(f: dict) -> bool:
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ftype = (f.get("type") or "").lower()
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fname = (f.get("name") or f.get("filename") or "").lower()
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return "image" in ftype or fname.endswith((".png", ".jpg", ".jpeg", ".webp"))
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def _read_file_dict(f: dict) -> Optional[bytes]:
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"""
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Try to read raw bytes for one file dict. Path keys first (covers local
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uploads), then Open WebUI's Files model lookup by id (covers assistant-
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emitted images that only have an id + relative URL). Returns None if
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no method worked.
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"""
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for path_key in ("path", "filepath", "file_path"):
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path = f.get(path_key)
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if path:
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try:
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with open(path, "rb") as fh:
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return fh.read()
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except OSError:
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pass
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fid = f.get("id")
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if _OPENWEBUI_RUNTIME and fid:
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try:
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file_model = Files.get_file_by_id(fid)
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if file_model is not None:
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# FileModel may expose path directly or under .meta
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path = getattr(file_model, "path", None)
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if not path:
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meta = getattr(file_model, "meta", None) or {}
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if isinstance(meta, dict):
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path = meta.get("path")
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else:
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path = getattr(meta, "path", None)
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if path:
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try:
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with open(path, "rb") as fh:
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return fh.read()
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except OSError:
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pass
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except Exception:
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pass
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return None
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async def _extract_attached_image(
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files: Optional[list],
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messages: Optional[list],
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session: aiohttp.ClientSession,
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) -> Optional[bytes]:
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"""
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Find the most recent image in the chat — including images previously
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emitted by this tool itself. Search order (most recent first):
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1. Inline base64 data URIs in `image_url` content blocks of recent
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messages (vision-model uploads, paste-from-clipboard).
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2. Files attached to messages in the conversation, scanned in
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REVERSE so the newest image wins. This covers two cases:
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a. Files the user just attached (current user message).
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b. Files the assistant emitted via prior `generate_image` /
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`edit_image` calls (attached to assistant messages by the
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`files` event in _push_image_to_chat).
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3. The __files__ tool param as a final fallback (some Open WebUI
|
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versions pass user uploads here instead of on the message).
|
||
4. Best-effort URL fetch on any leftover file dict (likely fails
|
||
on auth-protected endpoints — last resort).
|
||
"""
|
||
# 1. Inline data URIs on recent messages.
|
||
for msg in reversed(messages or []):
|
||
content = msg.get("content") if isinstance(msg, dict) else None
|
||
if isinstance(content, list):
|
||
for block in content:
|
||
if not isinstance(block, dict) or block.get("type") != "image_url":
|
||
continue
|
||
url = (block.get("image_url") or {}).get("url", "")
|
||
if url.startswith("data:image"):
|
||
try:
|
||
return base64.b64decode(url.split(",", 1)[1])
|
||
except Exception:
|
||
pass
|
||
|
||
# 2. Files on messages, newest first.
|
||
for msg in reversed(messages or []):
|
||
if not isinstance(msg, dict):
|
||
continue
|
||
msg_files = msg.get("files")
|
||
if not isinstance(msg_files, list):
|
||
continue
|
||
for f in msg_files:
|
||
if not isinstance(f, dict) or not _file_dict_is_image(f):
|
||
continue
|
||
data = _read_file_dict(f)
|
||
if data is not None:
|
||
return data
|
||
|
||
# 3. __files__ param (current user upload, sometimes only here).
|
||
for f in files or []:
|
||
if not isinstance(f, dict) or not _file_dict_is_image(f):
|
||
continue
|
||
data = _read_file_dict(f)
|
||
if data is not None:
|
||
return data
|
||
|
||
# 4. Last-resort URL fetch (no auth — only works for public endpoints).
|
||
for source in [files or []] + [
|
||
(msg.get("files") or []) for msg in reversed(messages or []) if isinstance(msg, dict)
|
||
]:
|
||
for f in source:
|
||
if not isinstance(f, dict) or not _file_dict_is_image(f):
|
||
continue
|
||
url = f.get("url")
|
||
if not url:
|
||
continue
|
||
full = url if url.startswith("http") else f"http://localhost:8080{url}"
|
||
try:
|
||
async with session.get(full) as resp:
|
||
if resp.status == 200:
|
||
return await resp.read()
|
||
except aiohttp.ClientError:
|
||
pass
|
||
|
||
return None
|
||
|
||
|
||
async def _upload_to_comfyui(
|
||
session: aiohttp.ClientSession, base: str, raw: bytes
|
||
) -> Optional[str]:
|
||
"""POST raw bytes to ComfyUI /upload/image and return the saved name."""
|
||
name = f"smartedit_{uuid.uuid4().hex[:12]}.png"
|
||
form = aiohttp.FormData()
|
||
form.add_field("image", raw, filename=name, content_type="image/png")
|
||
form.add_field("overwrite", "true")
|
||
async with session.post(f"{base}/upload/image", data=form) as resp:
|
||
if resp.status != 200:
|
||
return None
|
||
return (await resp.json()).get("name", name)
|
||
|
||
|
||
async def _push_image_to_chat(
|
||
raw: bytes,
|
||
filename_prefix: str,
|
||
request,
|
||
user_dict: Optional[dict],
|
||
metadata: Optional[dict],
|
||
event_emitter: Optional[Callable[[dict], Awaitable[None]]],
|
||
) -> bool:
|
||
"""
|
||
Surface a generated image in the chat using Open WebUI's canonical
|
||
pattern: upload the bytes via the internal file store, then emit a
|
||
`files` event referencing the served URL. This is the same path Open
|
||
WebUI's own image-generation code uses (utils/middleware.py ~1325).
|
||
|
||
Returns True if the image was uploaded and emitted via the files
|
||
event. Returns False if anything is missing — caller should fall
|
||
back to a data-URI markdown message in that case.
|
||
"""
|
||
if not (_OPENWEBUI_RUNTIME and request and user_dict and event_emitter):
|
||
return False
|
||
|
||
try:
|
||
user = Users.get_user_by_id(user_dict.get("id"))
|
||
if not user:
|
||
return False
|
||
|
||
upload = UploadFile(
|
||
file=io.BytesIO(raw),
|
||
filename=f"{filename_prefix}_{uuid.uuid4().hex[:8]}.png",
|
||
headers={"content-type": "image/png"},
|
||
)
|
||
meta = metadata or {}
|
||
result = upload_file_handler(
|
||
request=request,
|
||
file=upload,
|
||
metadata={
|
||
"chat_id": meta.get("chat_id"),
|
||
"message_id": meta.get("message_id"),
|
||
},
|
||
process=False,
|
||
user=user,
|
||
)
|
||
# upload_file_handler may be sync or async depending on the Open
|
||
# WebUI version — handle either.
|
||
if inspect.iscoroutine(result):
|
||
file_item = await result
|
||
else:
|
||
file_item = result
|
||
|
||
url = request.app.url_path_for(
|
||
"get_file_content_by_id", id=file_item.id
|
||
)
|
||
|
||
await event_emitter({
|
||
"type": "files",
|
||
"data": {"files": [{"type": "image", "url": url}]},
|
||
})
|
||
return True
|
||
except Exception:
|
||
# Any failure (signature drift, missing route, etc.) falls back
|
||
# to the data-URI path in the caller.
|
||
return False
|
||
|
||
|
||
async def _submit_and_fetch(
|
||
session: aiohttp.ClientSession,
|
||
base: str,
|
||
workflow: dict,
|
||
timeout_seconds: int,
|
||
emit: Callable[[str, bool], Awaitable[None]],
|
||
settings: dict,
|
||
) -> tuple[Optional[bytes], Optional[str]]:
|
||
"""Submit a workflow, poll history, fetch the first output image. Returns
|
||
(image_bytes, error_message)."""
|
||
client_id = str(uuid.uuid4())
|
||
|
||
async with session.post(
|
||
f"{base}/prompt", json={"prompt": workflow, "client_id": client_id}
|
||
) as resp:
|
||
if resp.status != 200:
|
||
return None, f"ComfyUI rejected the prompt: {resp.status} {await resp.text()}"
|
||
prompt_id = (await resp.json()).get("prompt_id")
|
||
if not prompt_id:
|
||
return None, "ComfyUI didn't return a prompt_id."
|
||
|
||
await emit(
|
||
f"Sampling — {settings['sampler']}/{settings['scheduler']}, "
|
||
f"CFG {settings['cfg']}, {settings['steps']} steps", False
|
||
)
|
||
|
||
deadline = time.time() + timeout_seconds
|
||
output_images: list = []
|
||
while time.time() < deadline:
|
||
await asyncio.sleep(1.5)
|
||
async with session.get(f"{base}/history/{prompt_id}") as resp:
|
||
if resp.status != 200:
|
||
continue
|
||
history = await resp.json()
|
||
if prompt_id in history:
|
||
for node_out in history[prompt_id].get("outputs", {}).values():
|
||
output_images.extend(node_out.get("images", []))
|
||
if output_images:
|
||
break
|
||
|
||
if not output_images:
|
||
return None, f"Timed out after {timeout_seconds}s waiting for image."
|
||
|
||
img = output_images[0]
|
||
params = {
|
||
"filename": img["filename"],
|
||
"subfolder": img.get("subfolder", ""),
|
||
"type": img.get("type", "output"),
|
||
}
|
||
async with session.get(f"{base}/view", params=params) as resp:
|
||
if resp.status != 200:
|
||
return None, f"Failed to fetch image: {resp.status}"
|
||
return await resp.read(), None
|
||
|
||
|
||
class Tools:
|
||
class Valves(BaseModel):
|
||
COMFYUI_BASE_URL: str = Field(
|
||
default="http://comfyui:8188",
|
||
description="ComfyUI server URL reachable from the open-webui container.",
|
||
)
|
||
TIMEOUT_SECONDS: int = Field(
|
||
default=240,
|
||
description="Maximum wait for a single generation to complete.",
|
||
)
|
||
|
||
def __init__(self):
|
||
self.valves = self.Valves()
|
||
|
||
async def generate_image(
|
||
self,
|
||
prompt: str,
|
||
style: Optional[StyleName] = None,
|
||
negative_prompt: Optional[str] = None,
|
||
width: int = 1024,
|
||
height: int = 1024,
|
||
seed: int = 0,
|
||
__request__=None,
|
||
__user__: Optional[dict] = None,
|
||
__metadata__: Optional[dict] = None,
|
||
__event_emitter__: Optional[Callable[[dict], Awaitable[None]]] = None,
|
||
) -> str:
|
||
"""
|
||
Create a NEW image from scratch and show it to the user. Use this
|
||
whenever the user asks you to draw, generate, create, make, paint,
|
||
render, or imagine any visual content — photographs, portraits,
|
||
characters, scenes, illustrations, anime, drawings — and they have
|
||
NOT attached an existing image. If they did attach an image and
|
||
want it modified, use edit_image instead.
|
||
|
||
Pick `style` to match what the user wants:
|
||
- "photo" — photorealistic photographs, portraits, cinematic shots.
|
||
- "juggernaut" — alternate photoreal style (sharper, more saturated).
|
||
- "pony" — anime / illustration / cartoon (Pony Diffusion).
|
||
- "general" — fallback for anything that doesn't fit the others.
|
||
- "furry-nai" — anthropomorphic characters (NAI-trained mix).
|
||
- "furry-noob" — anthropomorphic characters (NoobAI base).
|
||
- "furry-il" — anthropomorphic characters (Illustrious base, default
|
||
for any "furry" / "anthro" request unless specified otherwise).
|
||
|
||
Each style auto-prepends the right quality tags and picks the right
|
||
sampler / CFG / steps / CLIP skip. Do NOT add tags like
|
||
"masterpiece" or "score_9" to `prompt` yourself; the tool handles
|
||
that.
|
||
|
||
:param prompt: Plain description of the image (subject, scene,
|
||
style notes, lighting, etc.). No quality tags.
|
||
:param style: One of the values above. Omit to auto-detect.
|
||
:param negative_prompt: Extra terms to exclude. Usually unneeded.
|
||
:param width: Pixels (default 1024 — SDXL native). For portraits
|
||
use 832 with height 1216; for landscapes 1216 with height 832.
|
||
:param height: Pixels (default 1024).
|
||
:param seed: 0 to randomize, otherwise a specific seed for repeats.
|
||
:return: Markdown image of the result.
|
||
"""
|
||
chosen = style or _route_style(prompt)
|
||
settings = STYLES.get(chosen)
|
||
if not settings:
|
||
return f"Unknown style '{chosen}'. Available: {', '.join(STYLES.keys())}"
|
||
|
||
async def emit(msg: str, done: bool = False):
|
||
if __event_emitter__:
|
||
await __event_emitter__({
|
||
"type": "status",
|
||
"data": {"description": msg, "done": done},
|
||
})
|
||
|
||
await emit(f"Routing to {chosen} ({settings['ckpt']})")
|
||
|
||
positive = f"{settings['prefix']}{prompt}"
|
||
negative = settings["negative"]
|
||
if negative_prompt:
|
||
negative = f"{negative}, {negative_prompt}"
|
||
|
||
workflow = _build_txt2img(positive, negative, settings, width, height, seed)
|
||
base = self.valves.COMFYUI_BASE_URL.rstrip("/")
|
||
|
||
async with aiohttp.ClientSession() as session:
|
||
raw, err = await _submit_and_fetch(
|
||
session, base, workflow, self.valves.TIMEOUT_SECONDS, emit, settings,
|
||
)
|
||
if err:
|
||
return err
|
||
|
||
# Surface the image in the chat. Preferred path uploads to Open
|
||
# WebUI's file store and emits a `files` event (matches the built-
|
||
# in image-gen flow). Fallback inlines a data-URI markdown via a
|
||
# `message` event for environments where the file API isn't
|
||
# reachable from the tool process.
|
||
pushed = await _push_image_to_chat(
|
||
raw, "smartgen", __request__, __user__, __metadata__, __event_emitter__,
|
||
)
|
||
if not pushed and __event_emitter__:
|
||
b64 = base64.b64encode(raw).decode("ascii")
|
||
await __event_emitter__({
|
||
"type": "message",
|
||
"data": {"content": f""},
|
||
})
|
||
|
||
await emit(f"Done — {chosen}", done=True)
|
||
return (
|
||
f"Image generated and shown to the user above (style: {chosen}, "
|
||
f"checkpoint: {settings['ckpt']}). Do NOT describe the image, "
|
||
f"do NOT repeat any base64 or markdown — the user can see it. "
|
||
f"You may briefly note your style choice and offer one or two "
|
||
f"iteration ideas (different style, tighter framing, etc)."
|
||
)
|
||
|
||
async def edit_image(
|
||
self,
|
||
edit_instruction: str,
|
||
style: Optional[StyleName] = None,
|
||
mask_text: Optional[str] = None,
|
||
denoise: Optional[float] = None,
|
||
negative_prompt: Optional[str] = None,
|
||
seed: int = 0,
|
||
__request__=None,
|
||
__user__: Optional[dict] = None,
|
||
__metadata__: Optional[dict] = None,
|
||
__files__: Optional[list] = None,
|
||
__messages__: Optional[list] = None,
|
||
__event_emitter__: Optional[Callable[[dict], Awaitable[None]]] = None,
|
||
) -> str:
|
||
"""
|
||
Edit, modify, transform, or restyle an image the user has ATTACHED
|
||
to the chat. Use whenever the user uploads an image and asks to
|
||
change it. If no image is attached, use generate_image instead.
|
||
|
||
TWO MODES — choose based on whether the change is local or global:
|
||
|
||
- LOCAL change ("change the ball to a basketball", "make the dog
|
||
wear a hat", "remove the bird") → set `mask_text` to a brief
|
||
noun phrase describing the region ("the ball", "the dog", "the
|
||
bird"). The tool uses GroundingDINO+SAM to find that region
|
||
automatically and only that area is repainted; the rest of the
|
||
image stays pixel-perfect.
|
||
|
||
- GLOBAL change ("make this a sunset", "turn this into anime",
|
||
"restyle this as oil painting") → leave `mask_text` unset. The
|
||
whole image is reimagined via img2img.
|
||
|
||
Always prefer LOCAL mode when the user names a specific object,
|
||
person, or region. GLOBAL mode is for whole-image style/lighting
|
||
transformations.
|
||
|
||
Denoise tuning:
|
||
- LOCAL (mask_text set): default 1.0 — full repaint within mask.
|
||
Drop to 0.6–0.8 for subtle local edits that should retain some
|
||
original structure.
|
||
- GLOBAL (no mask_text): default 0.7 — moderate edit. Use 0.3–0.5
|
||
for subtle restyling, 0.85–1.0 for radical reimagining.
|
||
|
||
Pick `style` for the DESIRED OUTPUT, not the input image.
|
||
|
||
:param edit_instruction: What the changed area should look like.
|
||
Tool auto-prepends quality tags — don't include those.
|
||
:param style: One of the StyleName values. Omit to auto-detect.
|
||
:param mask_text: Noun phrase describing the region to edit. Set
|
||
for LOCAL changes; omit for GLOBAL.
|
||
:param denoise: 0.0 = no change, 1.0 = ignore source. Defaults to
|
||
1.0 with mask_text, 0.7 without.
|
||
:param negative_prompt: Extra terms to exclude. Usually unneeded.
|
||
:param seed: 0 to randomize, otherwise specific.
|
||
:return: Markdown image of the result, or an error if no image is attached.
|
||
"""
|
||
chosen = style or _route_style(edit_instruction)
|
||
settings = STYLES.get(chosen)
|
||
if not settings:
|
||
return f"Unknown style '{chosen}'. Available: {', '.join(STYLES.keys())}"
|
||
|
||
# Denoise default depends on mode: 1.0 (full repaint within mask)
|
||
# for inpainting, 0.7 for img2img.
|
||
if denoise is None:
|
||
denoise = 1.0 if mask_text else 0.7
|
||
denoise = max(0.0, min(1.0, denoise))
|
||
|
||
async def emit(msg: str, done: bool = False):
|
||
if __event_emitter__:
|
||
await __event_emitter__({
|
||
"type": "status",
|
||
"data": {"description": msg, "done": done},
|
||
})
|
||
|
||
base = self.valves.COMFYUI_BASE_URL.rstrip("/")
|
||
|
||
async with aiohttp.ClientSession() as session:
|
||
await emit("Looking for attached image…")
|
||
raw_in = await _extract_attached_image(__files__, __messages__, session)
|
||
if raw_in is None:
|
||
return (
|
||
"No image found in the chat. Ask the user to attach the "
|
||
"image they want edited (paperclip / drag-drop), or call "
|
||
"generate_image instead if they want a new image."
|
||
)
|
||
|
||
await emit("Uploading source to ComfyUI…")
|
||
uploaded_name = await _upload_to_comfyui(session, base, raw_in)
|
||
if not uploaded_name:
|
||
return "Failed to upload source image to ComfyUI."
|
||
|
||
mode = "inpaint" if mask_text else "img2img"
|
||
await emit(
|
||
f"Routing to {chosen} ({settings['ckpt']}), {mode}, denoise {denoise:.2f}"
|
||
+ (f", mask='{mask_text}'" if mask_text else "")
|
||
)
|
||
|
||
positive = f"{settings['prefix']}{edit_instruction}"
|
||
negative = settings["negative"]
|
||
if negative_prompt:
|
||
negative = f"{negative}, {negative_prompt}"
|
||
|
||
if mask_text:
|
||
workflow = _build_inpaint(
|
||
positive=positive,
|
||
negative=negative,
|
||
settings=settings,
|
||
image_filename=uploaded_name,
|
||
mask_text=mask_text,
|
||
denoise=denoise,
|
||
seed=seed,
|
||
)
|
||
else:
|
||
workflow = _build_img2img(
|
||
positive=positive,
|
||
negative=negative,
|
||
settings=settings,
|
||
image_filename=uploaded_name,
|
||
denoise=denoise,
|
||
seed=seed,
|
||
)
|
||
|
||
raw_out, err = await _submit_and_fetch(
|
||
session, base, workflow, self.valves.TIMEOUT_SECONDS, emit, settings,
|
||
)
|
||
if err:
|
||
return err
|
||
|
||
pushed = await _push_image_to_chat(
|
||
raw_out, "smartedit", __request__, __user__, __metadata__, __event_emitter__,
|
||
)
|
||
if not pushed and __event_emitter__:
|
||
b64 = base64.b64encode(raw_out).decode("ascii")
|
||
await __event_emitter__({
|
||
"type": "message",
|
||
"data": {"content": f""},
|
||
})
|
||
|
||
await emit(f"Done — {chosen} (denoise {denoise:.2f})", done=True)
|
||
return (
|
||
f"Edited image shown to the user above (style: {chosen}, "
|
||
f"checkpoint: {settings['ckpt']}, denoise: {denoise:.2f}). Do NOT "
|
||
f"describe the image, do NOT repeat any base64 or markdown — the "
|
||
f"user can see it. You may briefly note your choice and offer "
|
||
f"iterations (different denoise, alternate style, etc)."
|
||
)
|