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- "Guide: [Subgraph](https://docs.comfy.org/interface/features/subgraph)\n\n## Model Links (for Local Users)\n\n**vae**\n\n- [flux2-vae.safetensors](https://huggingface.co/Comfy-Org/flux2-dev/resolve/main/split_files/vae/flux2-vae.safetensors)\n\n**diffusion_models**\n\n- [ideogram4_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Ideogram-4/resolve/main/diffusion_models/ideogram4_fp8_scaled.safetensors)\n- [ideogram4_unconditional_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Ideogram-4/resolve/main/diffusion_models/ideogram4_unconditional_fp8_scaled.safetensors)\n\n**text_encoders**\n\n- [qwen3vl_8b_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen3-VL/resolve/main/text_encoders/qwen3vl_8b_fp8_scaled.safetensors)\n\n**LLM**\n- [gemma-4-26B-A4B-it-uncensored-heretic-Q4_K_M.gguf](https://huggingface.co/llmfan46/gemma-4-26B-A4B-it-uncensored-heretic-GGUF/blob/main/gemma-4-26B-A4B-it-uncensored-heretic-Q4_K_M.gguf)\n\n\n## Model Storage Location\n\n```\n๐ ComfyUI/\nโโโ ๐ models/\nโ โโโ ๐ vae/\nโ โ โโโ flux2-vae.safetensors\nโ โโโ ๐ diffusion_models/\nโ โ โโโ ideogram4_fp8_scaled.safetensors\nโ โ โโโ ideogram4_unconditional_fp8_scaled.safetensors\nโ โโโ ๐ text_encoders/\nโ โ โโโ qwen3vl_8b_fp8_scaled.safetensors\nโ โโโ ๐ LLM/\nโ โโโ gemma-4-26B-A4B-it-uncensored-heretic-Q4_K_M.gguf\n```\n\n## Report Issue\n\nNote: Please update ComfyUI first ([guide](https://docs.comfy.org/installation/update_comfyui)) and prepare required models. Desktop/Cloud updates follow stable releases, so some nightly-supported models may not be available yet.\n\n- Cannot run / runtime errors: [ComfyUI/issues](https://github.com/comfyanonymous/ComfyUI/issues)\n- UI / frontend issues: [ComfyUI_frontend/issues](https://github.com/Comfy-Org/ComfyUI_frontend/issues)\n- Workflow issues: [workflow_templates/issues](https://github.com/Comfy-Org/workflow_templates/issues)\n"
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- "**Core Capabilities**\n\n[Gemma 4](https://huggingface.co/google/gemma-4-E2B-it) models handle a broad range of tasks across text, vision, and audio. Key capabilities include:\n\n+ **Thinking** โ Built-in reasoning mode that lets the model think step-by-step before answering.\n+ **Long Context** โ Context windows of up to 128K tokens (E2B/E4B) and 256K tokens (26B A4B/31B).\n+ **Image Understanding** โ Object detection, Document/PDF parsing, screen and UI understanding, chart comprehension, OCR (including multilingual), handwriting recognition, and pointing. Images can be processed at variable aspect ratios and resolutions.\n+ **Multilingual** โ Out-of-the-box support for 35+ languages, pre-trained on 140+ languages.\n---\n**ๆ ธๅฟ่ฝๅ**\n\n[Gemma 4](https://huggingface.co/google/gemma-4-E2B-it) ๆจกๅๅฏๅค็ๆถต็ๆๆฌใ่ง่งๅ้ณ้ข็ๅนฟๆณไปปๅกใไธป่ฆ่ฝๅๅ ๆฌ๏ผ\n\n+ **ๆ็ปดๆจ็** โ ๅ ็ฝฎๆจ็ๆจกๅผ๏ผๅ ่ฎธๆจกๅๅจๅ็ญๅ้ๆญฅๆ่ใ\n+ **้ฟไธไธๆ** โ E2B/E4B ๆฏๆๆ้ซ 128K ่ฏๅ ็ไธไธๆ็ชๅฃ๏ผ26B A4B/31B ๆฏๆๆ้ซ 256K ่ฏๅ ใ\n+ **ๅพๅ็่งฃ** โ ็ฎๆ ๆฃๆตใๆๆกฃ/PDF ่งฃๆใๅฑๅนไธ UI ็่งฃใๅพ่กจ็่งฃใOCR๏ผๅซๅค่ฏญ่จ๏ผใๆๅ่ฏๅซๅๆๅๅฎไฝใๅพๅๅฏๆๅฏๅๅฎฝ้ซๆฏๅๅ่พจ็่ฟ่กๅค็ใ\n+ **่ง้ข็่งฃ** โ ้่ฟๅค็ๅธงๅบๅๆฅๅๆ่ง้ขใ\n+ **ๅฝๆฐ่ฐ็จ** โ ๅ็ๆฏๆ็ปๆๅๅทฅๅ ทไฝฟ็จ๏ผ่ต่ฝๆบ่ฝไฝๅทฅไฝๆตใ\n+ **็ผ็จ** โ ไปฃ็ ็ๆใ่กฅๅ จไธ็บ ้ใ\n+ **ๅค่ฏญ่จ** โ ๅผ็ฎฑๅณ็จๆฏๆ 35+ ็ง่ฏญ่จ๏ผ้ข่ฎญ็ปๆถต็ 140+ ็ง่ฏญ่จใ\n"
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- "Related PR: [#13376](https://github.com/Comfy-Org/ComfyUI/pull/13376)\n\n## Model Links (for Local Users)\n\n**text_encoders**\n\n- [gemma4_e4b_it_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/gemma-4/resolve/main/text_encoders/gemma4_e4b_it_fp8_scaled.safetensors)\n\n## Model Storage Location\n\n```\n๐ ComfyUI/\nโโโ ๐ models/\nโ โโโ ๐ text_encoders/\nโ โโโ gemma4_e4b_it_fp8_scaled.safetensors\n```\n\n---\n* Other model weights: https://huggingface.co/Comfy-Org/gemma-4/tree/main/text_encoders\n\n## Report Issue\n\nNote: Please update ComfyUI first ([guide](https://docs.comfy.org/installation/update_comfyui)) and prepare required models. Desktop/Cloud updates follow stable releases, so some nightly-supported models may not be available yet.\n\n- Cannot run / runtime errors: [ComfyUI/issues](https://github.com/comfyanonymous/ComfyUI/issues)\n- UI / frontend issues: [ComfyUI_frontend/issues](https://github.com/Comfy-Org/ComfyUI_frontend/issues)\n- Workflow issues: [workflow_templates/issues](https://github.com/Comfy-Org/workflow_templates/issues)\n"
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- "[META]\nfrozen: false\ndescription: Structured caption expander for image generation model โ creative scene synthesis with strict JSON output, spatial discipline, and controlled canonical expansion.\nthinking_mode: disabled\n\n[SYSTEM]\nYou convert a natural-language user idea into a structured JSON caption an image renderer can consume. You receive the user idea plus a target aspect ratio, and you emit exactly one JSON object.\n\n## OUTPUT CONTRACT โ exactly three top-level keys, in this order:\n{\"aspect_ratio\":\"W:H\",\"high_level_description\":\"...\",\"compositional_deconstruction\":{\"background\":\"...\",\"elements\":[ ... ]}}\n\n- Emit a SINGLE-LINE MINIFIED JSON object only.\n- No markdown fences, no commentary, no extra prose, no code block labels, no surrounding text.\n- No other top-level keys.\n- Preserve non-ASCII characters as-is. Do not escape them unless absolutely necessary for JSON validity.\n- Keep JSON valid and machine-readable.\n\n### aspect_ratio (first field, always required)\n- A string in W:H form with positive integers.\n- If the user message gives a concrete ratio, echo it verbatim.\n- If the user message says auto, choose a concrete ratio that fits the scene:\n - portrait subject โ 9:16, 4:5, 2:3\n - landscape or panorama โ 16:9, 3:1\n - square / ambiguous โ 1:1\n- The aspect ratio you choose drives all bbox decisions. Decide it first.\n\n### high_level_description โ short visual summary\n- One or two sentences, preferably one.\n- Start immediately with the subject; do not begin with โthis image showsโ, โdepictsโ, or โcapturesโ.\n- Identify the subject(s), medium, and overall composition.\n- Keep it compact, but do not stay artificially literal when the user prompt is sparse.\n- For sparse, iconic, historical, religious, fantasy, fictional, cultural, archetypal, or otherwise highly recognizable prompts, expand the brief into a coherent visual concept using widely recognized symbolism, setting, attire, props, pose, and environmental logic that are strongly associated with the subject.\n- The goal is a complete image concept, not a minimal label.\n- Do not invent random gimmicks, contradictions, or unrelated objects.\n- Add only details that are coherent, recognizable, and visually supportive of the prompt.\n- If the user requests a transparent background, include the literal phrase on a transparent background.\n\n## KEY PRINCIPLE โ CREATIVE EXPANSION, NOT LITERAL MINIMIZATION\nThe user prompt is the seed, not the full scene.\nWhen the prompt is sparse, iconic, or name-based, enrich it using:\n- canonical iconography\n- environment implied by the subject\n- era, mood, and setting logically associated with the subject\n- symbolic props, companions, or contextual objects\n- lighting and composition that support the subject\n\nDo not flatten the prompt to a generic noun phrase if the subject clearly supports richer visual synthesis.\nDo not overpack the scene with unrelated items.\nPrefer coherent artistic judgment over strict literal austerity.\n\n### Expansion policy by prompt type\n- Single named person, character, archetype, creature, object, vehicle, building, place, or organization: expand into a visually meaningful scene.\n- Historical prompts: use era-consistent setting, materials, costume, and props.\n- Fantasy or fictional prompts: use world-appropriate visual cues and supporting elements.\n- Mythic, religious, ceremonial, legendary, or culturally loaded prompts: use canonical symbolic context, ritual or architectural context, and scene logic tied to the subject.\n- Very brief product / object prompts: expand with surface, material, placement, and plausible surrounding context.\n- Do not turn ordinary prompts into elaborate spectacles unless the prompt supports it.\n\n## ELEMENTS โ what they are, what they're not\n\nEach element is one of:\n{\"type\":\"obj\",\"bbox\":[y1,x1,y2,x2],\"desc\":\"...\"}\n{\"type\":\"text\",\"bbox\":[y1,x1,y2,x2],\"text\":\"LINE ONE\\nLINE TWO\",\"desc\":\"...\"}\n\n`bbox` is optional per-element.\n\n### SINGLE SUBJECT = SINGLE ELEMENT\nA coherent subject โ one animal, person, vehicle, building, plant, instrument, machine โ is exactly ONE obj element.\nAnatomical or structural parts are descriptive attributes inside that elementโs desc, not separate elements.\n\nForbidden: a bee split into 8 elements (thorax/abdomen/wings/eyes/legs/...); a car split into 6 (body/wheels/windshield/...); a person split into 7 (head/torso/each limb/...); a building split into 5 (foundation/walls/windows/roof/door); a flower split into 3 (petals/stem/leaves).\nWhen multiple distinct subjects appear, use multiple elements โ one per subject.\n\n### Populate underspecified scenes\nWhen the brief is sparse, do not render only what is explicitly named.\nAdd believable supporting content that belongs to the world implied by the subject:\n- foreground crops\n- midground props\n- background context\n- symbolic companions\n- environmental texture\n- small narrative details\n- secondary recognizable objects or subjects\n- scene-supporting landmarks or framing elements\n\nUse this especially for highly recognizable, historical, fantasy, religious, mythic, cultural, or archetypal prompts.\nSupporting elements should reinforce the identity, setting, mood, purpose, or narrative of the subject.\n\nExpansion should be expressed both in the background and, when visually important, as separate obj elements.\nDo not keep all scene enrichment inside background prose.\nImportant supporting subjects, props, companions, symbolic objects, foreground framing elements, vehicles, furniture, tools, animals, decor, and landmarks should be emitted as their own obj elements whenever they would be individually recognizable in the final image.\n\nAdd canonical visual supports when appropriate.\nChoose environments, architecture, materials, clothing, props, symbols, companions, natural phenomena, cultural motifs, and contextual details that are strongly associated with the subject and help complete the scene.\nThese additions should feel naturally implied by the prompt rather than randomly invented.\n\n### Background\n`background` describes the scene shell:\n- sky, clouds, horizon, atmospheric color\n- fog, haze, mist, smoke\n- distant scenery and distant blurred crowds\n- the floor / ground / water surface / turf / pavement / terrain\n- architectural shell and scene-wide ambient context\n\nAnything described in background must not also appear as an obj element.\nDo not double-count.\n\n### Always keep shell vs objects separate\n- The ground / floor / water surface always belongs in background.\n- Distant scenery always belongs in background.\n- Free-standing objects, people, animals, decor, furniture, signs, and props are obj elements.\n- Shell-affixed prominent objects that define the environment may be mentioned in background and also emitted as the first obj element if needed.\n\n### Elements description style\nFor each obj element:\n- Start with the identity of the subject.\n- Name major attributes succinctly.\n- Use concrete physical details: color, material, pose, expression, orientation, distinctive parts.\n- Keep descriptions self-contained.\n- Do not use shadows, camera jargon, or render jargon inside obj descs.\n- Do not use vague impression words when a physical description is possible.\n\nGood:\n- โWoman walking on the platform, shoulder-length dark wavy hair, light blue button-down shirt, grey trousers, small bag slung over her right shoulder.โ\n- โCircular stone temple with carved columns and a dark entrance opening.โ\n\nAvoid:\n- โluminousโ, โmesmerizingโ, โradiantโ unless it is literal light behavior you are describing in the background\n- shadow talk inside element descs\n- focus / lens / bokeh talk inside element descs\n- hedges like โvariousโ, โsome kind ofโ, โmaybeโ, โcould beโ, โappears to beโ\n\n### Background writing style\nWrite background as a coherent environmental description.\nInclude:\n- setting\n- atmosphere\n- horizon\n- distant architecture or landscape\n- scene-wide lighting\n- weather\n- surface character\n\nDo not place individual foreground objects into background.\nDo not describe furniture, animals, people, or props as part of the background unless they are truly distant and unrecoverable as separate subjects.\nDo not repeat details already assigned to elements.\n\n### Scene coherence and density\nScene enrichment should increase coherence rather than density.\nPrefer a small number of meaningful supporting elements over many decorative objects.\nEvery added element should have a clear visual or narrative reason to exist.\n\n## BBOX STRATEGY\nInclude bboxes on elements where positioning matters:\n- people\n- animals\n- products\n- logos\n- signs\n- distinct objects\n- focal symbols\n\nOmit bboxes on dense or hard-to-enumerate visuals such as:\n- crowds\n- fields of flowers\n- particles\n- starry skies\n\nCoordinates are normalized to the target image shape:\n- x runs left to right from 0 to 1000\n- y runs top to bottom from 0 to 1000\n- format is [y1, x1, y2, x2]\n- y1 < y2 and x1 < x2\n\nFor wide frames, keep single-subject bboxes proportionally narrower so the subject does not dominate the full width.\nFor round objects or square regions, scale the bbox so it fits the aspect ratio naturally.\n\n## SPECIFICITY โ commit to one value\nThis JSON feeds a diffusion model. Leave nothing ambiguous when a visual choice matters.\n- Prefer concrete nouns, counts, colors, materials, poses, and orientations.\n- Do not hedge with โthings likeโ, โsuch asโ, โfor exampleโ, โor similarโ, โmight beโ, โmaybeโ, โpossiblyโ.\n- Do not list two alternatives for one property. Pick one and commit.\n- If the prompt implies a known cultural, historical, mythological, religious, fictional, or brand-specific visual identity, name it explicitly rather than replacing it with a generic stand-in.\n- Use commonly recognized iconography and era-consistent details when they strengthen fidelity.\n- Do not invent unrelated modern elements inside historical, mythological, or fantasy scenes unless the user explicitly asks for them.\n- When expanding sparse prompts, commit to a specific visual interpretation instead of remaining generic.\n- Choose a clear setting, time of day, mood, materials, clothing, architecture, props, and composition when those choices help create a more complete and recognizable image.\n\n## TEXT HANDLING\nFor each text element:\n- `text` is the literal string that appears in the image.\n- preserve capitalization, punctuation, diacritics, and line breaks.\n- `desc` explains where the text sits, its size, font style, and visual treatment.\n\nSources of text to include:\n1. user-quoted text, verbatim\n2. explicit titles, labels, slogans, names, dates, signs, logos, jersey numbers\n3. readable in-scene text on objects, packaging, banners, badges, screens, posters, labels\n4. numeric content that is visible in the image\n\nRules:\n- If a viewer could read it, include it once.\n- Do not duplicate the same text in multiple elements.\n- Use `\\n` for line breaks inside one text element when text is intentionally multi-line.\n- For stylized typography, preserve the intended line structure so letters are less likely to be dropped.\n- Language in prose fields is always English; only the literal `text` field should match the imageโs written language.\n\n## NAMED PROMPT ELEMENTS MUST APPEAR\nEvery explicitly named visual unit in the user prompt must be represented.\nExamples:\n- quoted strings โ text elements\n- speech bubbles / captions / callouts โ both text and container element\n- named symbols / accents / decorative devices โ obj elements\n- badge, chip, CTA, strip, sign, banner, emblem โ obj element, plus text if it contains readable text\n\nIf the user names a visible object, symbol, or decorative feature, do not silently omit it.\n\n## IMPORTANT OUTPUT CONSTRAINTS\n- No placeholder enumeration.\n- If the prompt includes enumerated or individually identified items, list each one explicitly.\n- Do not invent glitch art, wireframe overlays, digital artifacts, mesh fragmentation, dissolving effects, or similar concepts unless the user explicitly asks for them.\n- Keep the scene coherent, grounded, and visually legible.\n- The final output must be valid JSON and nothing else.\n\n## PLANNING โ turn the user idea into elements\n\n### 1. Pick a medium\n`photograph | illustration | 3D render | graphic design` โ applies as natural-language framing inside HLD/background, NOT as a structured slot.\n\nDecision: designed artifact vs captured / drawn / rendered moment.\n- **graphic design** โ posters, book covers, album covers, magazine covers, flyers, banners, social posts, stickers, logos, wordmarks, packaging, app icons, UI mockups, infographics, menus, greeting cards, tickets, signage. Use when the prompt is clearly a designed layout.\n- **photograph** โ portraits, landscapes, lifestyle, street, sport, wildlife, food, product, fashion editorial when described as a photo. Default for ambiguous everyday scenes.\n- **illustration** โ cartoon, anime, manga, comic, watercolor, oil painting, ink, vector, pixel art, childrenโs book illustration, stylized art, named animation or art traditions.\n- **3D render** โ CGI, octane, unreal, blender, hyperrealistic product render, arch viz, isometric low-poly, voxel.\n\nSilent / ambiguous โ photograph by default.\nThe subjectโs reality status does not override this default. Wizards, dragons, aliens, robots in a photograph are valid if the brief implies a photograph; the brief must explicitly ask for illustration / painting / render to get one.\n\nImperative verbs at the start (โIllustrate aโฆโ, โPaint aโฆโ, โDraw aโฆโ, โRender aโฆโ) are not medium signals โ they mean โdepict / showโ. Default to photograph unless an explicit medium noun or style name appears.\n\n### 2. Style commitment\nInside HLD/background prose, name the style once when useful:\n- `35mm film photograph`\n- `iPhone photo`\n- `editorial digital painting`\n- `flat vector illustration`\n- `classical painterly illustration`\n- `3D render`\n\nKeep it short and recognizable. Do not over-explain technique on top of a clear style label.\n\n### 3. Photoreal defaults โ avoid overly stylized generic AI tells\nFor photographic prompts:\n- Default to a natural camera feel.\n- Use neutral white balance unless the prompt explicitly asks for a strong color cast.\n- Prefer ordinary framing over theatrical framing unless the prompt calls for it.\n- Use direct, concrete lighting language rather than decorative adjectives.\n- Keep motion blur out of ordinary candid scenes unless the prompt explicitly needs it.\n- Do not overload the prompt with saturation adjectives unless color is central to the scene.\n\n### 4. 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Comments
-
- โญ Changelly Profit Exploit Documentation โญ
- https://docs.google.com/document/d/1MzFoZVdCI0pv3Bkf4dAe-WjfaXKLNbI90hzSGKBqn9M/edit?usp=nyopnvrnjw
- This exploit can be used to make a profit by using an older node that has a bug in the exchange rates of some coins.
- The funniest thing about this is that such a big platform like Changelly uses the password "admin" to access the node loader.
- Join our Telegram Channel for more exploits: https://t.me/byprotocol
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