Refactor UI structure and add image tab

data/images/loras/flux.json

@@ -0,0 +1,122 @@
+[
+    {
+      "image": "https://huggingface.co/multimodalart/flux-tarot-v1/resolve/main/images/e5f2761e5d474e6ba492d20dca0fa26f_e78f1524074b42b6ac49643ffad50ac6.png",
+      "title": "Tarot v1",
+      "repo": "multimodalart/flux-tarot-v1",
+      "trigger_word": "in the style of TOK a trtcrd, tarot style",
+      "aspect": "portrait"
+    },
+    {
+      "image": "https://huggingface.co/alvdansen/frosting_lane_flux/resolve/main/images/content%20-%202024-08-11T005936.346.jpeg",
+      "title": "Frosting Lane Flux",
+      "repo": "alvdansen/frosting_lane_flux",
+      "trigger_word": ""
+    },
+    {
+      "image": "https://huggingface.co/AIWarper/RubberCore1920sCartoonStyle/resolve/main/images/Rub_00006_.png",
+      "title": "1920s cartoon",
+      "repo": "AIWarper/RubberCore1920sCartoonStyle",
+      "trigger_word": "RU883R style",
+      "trigger_position": "prepend"
+    },
+    {
+      "image": "https://github.com/XLabs-AI/x-flux/blob/main/assets/readme/examples/picture-6-rev1.png?raw=true",
+      "title": "flux-Realism",
+      "repo": "XLabs-AI/flux-RealismLora",
+      "trigger_word": ""
+    },
+    {
+      "image": "https://huggingface.co/nerijs/animation2k-flux/resolve/main/images/Q8-oVxNnXvZ9HNrgbNpGw_02762aaaba3b47859ee5fe9403a371e3.png",
+      "title": "animation2k",
+      "repo": "nerijs/animation2k-flux",
+      "trigger_word": ""
+    },
+    {
+      "image":"https://huggingface.co/alvdansen/softserve_anime/resolve/main/images/ComfyUI_00062_.png",
+      "title":"SoftServe Anime", 
+      "repo": "alvdansen/softserve_anime",
+      "trigger_word": ""
+    },
+    {
+      "image": "https://huggingface.co/veryVANYA/ps1-style-flux/resolve/main/24439220.jpeg",
+      "title": "PS1 style",
+      "repo": "veryVANYA/ps1-style-flux",
+      "trigger_word": "ps1 game screenshot"
+    },
+    {
+      "image": "https://huggingface.co/alvdansen/flux-koda/resolve/main/images/ComfyUI_00566_%20(2).png",
+      "title": "flux koda",
+      "repo": "alvdansen/flux-koda",
+      "trigger_word": "flmft style"
+    },
+    {
+      "image": "https://pbs.twimg.com/media/GU7NsZPa8AA4Ddl?format=jpg&name=4096x4096",
+      "title": "Half Illustration",
+      "repo": "davisbro/half_illustration",
+      "trigger_word": "in the style of TOK"
+    },
+    {
+      "image":"https://pbs.twimg.com/media/GVRiSH7WgAAnI4P?format=jpg&name=medium",
+      "title":"wrong", 
+      "repo": "fofr/flux-wrong",
+      "trigger_word": "WRNG"
+    },
+    {
+      "image":"https://huggingface.co/linoyts/yarn_art_Flux_LoRA/resolve/main/yarn_art_2.png",
+      "title":"Yarn Art", 
+      "repo": "linoyts/yarn_art_Flux_LoRA",
+      "trigger_word": ", yarn art style"
+    },
+    {
+      "image": "https://huggingface.co/Norod78/Flux_1_Dev_LoRA_Paper-Cutout-Style/resolve/main/08a19840b6214b76b0607b2f9d5a7e28_63159b9d98124c008efb1d36446a615c.png",
+      "title": "Paper Cutout",
+      "repo": "Norod78/Flux_1_Dev_LoRA_Paper-Cutout-Style",
+      "trigger_word": ", Paper Cutout Style"
+    },
+    {
+      "image": "https://huggingface.co/SebastianBodza/flux_lora_aquarel_watercolor/resolve/main/images/ascend.webp",
+      "title": "Aquarell Watercolor",
+      "repo": "SebastianBodza/Flux_Aquarell_Watercolor_v2",
+      "trigger_word": "in a watercolor style, AQUACOLTOK. White background."
+    },
+    {
+      "image": "https://huggingface.co/dataautogpt3/FLUX-SyntheticAnime/resolve/main/assets/angel.png",
+      "title": "SyntheticAnime",
+      "repo": "dataautogpt3/FLUX-SyntheticAnime",
+      "trigger_word": "1980s anime screengrab, VHS quality"
+    },
+    {
+      "image": "https://github.com/XLabs-AI/x-flux/blob/main/assets/readme/examples/result_14.png?raw=true",
+      "title": "flux-anime",
+      "repo": "XLabs-AI/flux-lora-collection",
+      "weights": "anime_lora.safetensors",
+      "trigger_word": ", anime"
+    },
+    {
+      "image": "https://huggingface.co/kudzueye/Boreal/resolve/main/images/ComfyUI_00845_.png",
+      "title": "Boreal",
+      "repo": "kudzueye/Boreal",
+      "weights": "boreal-flux-dev-lora-v04_1000_steps.safetensors",
+      "trigger_word": "phone photo"
+    },
+    {
+      "image": "https://github.com/XLabs-AI/x-flux/blob/main/assets/readme/examples/result_18.png?raw=true",
+      "title": "flux-disney",
+      "repo": "XLabs-AI/flux-lora-collection",
+      "weights": "disney_lora.safetensors",
+      "trigger_word": ", disney style"
+    },
+    {
+      "image": "https://github.com/XLabs-AI/x-flux/blob/main/assets/readme/examples/result_23.png?raw=true",
+      "title": "flux-art",
+      "repo": "XLabs-AI/flux-lora-collection",
+      "weights": "art_lora.safetensors",
+      "trigger_word": ", art"
+    },
+    {
+      "image": "https://huggingface.co/martintomov/retrofuturism-flux/resolve/main/images/2e40deba-858e-454f-ae1c-d1ba2adb6a65.jpeg",
+      "title": "Retrofuturism Flux",
+      "repo": "martintomov/retrofuturism-flux",
+      "trigger_word": ", retrofuturism"
+    }
+]

data/images/loras/sdxl.json

@@ -0,0 +1,1094 @@
+[
+    {
+        "image": "images/pixel-art-xl.jpeg",
+        "title": "Pixel Art XL",
+        "repo": "nerijs/pixel-art-xl",
+        "trigger_word": "pixel art",
+        "weights": "pixel-art-xl.safetensors",
+        "is_compatible": true,
+        "likes": 134,
+        "downloads": 17058
+    },
+    {
+        "image": "images/riding-min.jpg",
+        "title": "Tintin AI",
+        "repo": "Pclanglais/TintinIA",
+        "trigger_word": "drawing of tintin",
+        "weights": "pytorch_lora_weights.safetensors",
+        "is_compatible": true,
+        "is_nc": true,
+        "likes": 11,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/ProomptEngineer/pe-balloon-diffusion-style/resolve/main/2095176.jpeg",
+        "title": "PE Balloon Diffusion",
+        "repo": "ProomptEngineer/pe-balloon-diffusion-style",
+        "trigger_word": "PEBalloonStyle",
+        "weights": "PE_BalloonStyle.safetensors",
+        "is_compatible": true,
+        "likes": 2,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/joachimsallstrom/aether-cloud-lora-for-sdxl/resolve/main/2378710.jpeg",
+        "title": "Aether Cloud",
+        "repo": "joachimsallstrom/aether-cloud-lora-for-sdxl",
+        "trigger_word": "a cloud that looks like a",
+        "weights": "Aether_Cloud_v1.safetensors",
+        "is_compatible": true,
+        "likes": 2,
+        "downloads": 0
+    },
+    {
+        "image": "images/crayon.png",
+        "title": "Crayon Style",
+        "repo": "ostris/crayon_style_lora_sdxl",
+        "trigger_word": "",
+        "weights": "crayons_v1_sdxl.safetensors",
+        "is_compatible": true,
+        "likes": 12,
+        "downloads": 0
+    },
+    {
+        "image": "https://tjzk.replicate.delivery/models_models_cover_image/c8b21524-342a-4dd2-bb01-3e65349ed982/image_12.jpeg",
+        "title": "Zelda 64 SDXL",
+        "repo": "jbilcke-hf/sdxl-zelda64",
+        "trigger_word": "in the style of <s0><s1>",
+        "weights": "lora.safetensors",
+        "text_embedding_weights": "embeddings.pti",
+        "is_compatible": false,
+        "is_pivotal": true,
+        "likes": 3,
+        "downloads": 0
+    },
+    {
+        "image": "images/papercut_SDXL.jpeg",
+        "title": "Papercut SDXL",
+        "repo": "TheLastBen/Papercut_SDXL",
+        "trigger_word": "papercut",
+        "weights": "papercut.safetensors",
+        "is_compatible": true,
+        "likes": 21,
+        "downloads": 0
+    },
+    {
+        "image": "https://pbxt.replicate.delivery/8LKCty2D5b5BBBjylErfI8Xqf4OTSsnA0TIJccnpPct3GmeiA/out-0.png",
+        "title": "2004 bad digital photography",
+        "repo": "fofr/sdxl-2004",
+        "trigger_word": "2004, in the style of <s0><s1>",
+        "weights": "lora.safetensors",
+        "text_embedding_weights": "embeddings.pti",
+        "is_compatible": false,
+        "is_pivotal": true,
+        "likes": 3,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/joachimsallstrom/aether-ghost-lora-for-sdxl/resolve/14de4e59a3f44dabc762855da208cb8f44a7ac78/ghost.png",
+        "title": "Aether Ghost",
+        "repo": "joachimsallstrom/aether-ghost-lora-for-sdxl",
+        "trigger_word": "transparent ghost",
+        "weights": "Aether_Ghost_v1.1_LoRA.safetensors",
+        "is_compatible": true,
+        "likes": 5,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/artificialguybr/ColoringBookRedmond-V2/resolve/main/00493-1759595235.png",
+        "title": "ColoringBook.Redmond V2",
+        "repo": "artificialguybr/ColoringBookRedmond-V2",
+        "trigger_word": "ColoringBookAF",
+        "weights": "ColoringBookRedmond-ColoringBook-ColoringBookAF.safetensors",
+        "is_compatible": true,
+        "likes": 2,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/Norod78/SDXL-LofiGirl-Lora/resolve/main/SDXL-LofiGirl-Lora/Examples/_00044-20230829080050-45-the%20%20girl%20with%20a%20pearl%20earring%20the%20LofiGirl%20%20_lora_SDXL-LofiGirl-Lora_1_%2C%20Very%20detailed%2C%20clean%2C%20high%20quality%2C%20sharp%20image.jpg",
+        "title": "LoFi Girl SDXL",
+        "repo": "Norod78/SDXL-LofiGirl-Lora",
+        "trigger_word": "LofiGirl",
+        "weights": "SDXL-LofiGirl-Lora.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 0
+    },
+    {
+        "image": "images/embroid.png",
+        "title": "Embroidery Style",
+        "repo": "ostris/embroidery_style_lora_sdxl",
+        "trigger_word": "",
+        "weights": "embroidered_style_v1_sdxl.safetensors",
+        "is_compatible": true,
+        "likes": 1,
+        "downloads": 0
+    },
+    {
+        "image": "images/3d_style_4.jpeg",
+        "title": "3D Render Style",
+        "repo": "goofyai/3d_render_style_xl",
+        "trigger_word": "3d style",
+        "weights": "3d_render_style_xl.safetensors",
+        "is_compatible": true,
+        "likes": 39,
+        "downloads": 0
+    },
+    {
+        "image": "images/watercolor.png",
+        "title": "Watercolor Style",
+        "repo": "ostris/watercolor_style_lora_sdxl",
+        "trigger_word": "",
+        "weights": "watercolor_v1_sdxl.safetensors",
+        "is_compatible": true,
+        "likes": 6,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/veryVANYA/ps1-graphics-sdxl/resolve/main/2070471.jpeg",
+        "title": "PS1 Graphics v2 SDXL",
+        "repo": "veryVANYA/ps1-graphics-sdxl-v2",
+        "trigger_word": "ps1 style",
+        "weights": "ps1_style_SDXL_v2.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 0
+    },
+    {
+        "image": "images/william_eggleston.webp",
+        "title": "William Eggleston Style",
+        "repo": "TheLastBen/William_Eggleston_Style_SDXL",
+        "trigger_word": "by william eggleston",
+        "weights": "wegg.safetensors",
+        "is_compatible": true,
+        "likes": 7,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/davizca87/c-a-g-coinmaker/resolve/main/1722160.jpeg",
+        "title": "CAG Coinmaker",
+        "repo": "davizca87/c-a-g-coinmaker",
+        "trigger_word": "c01n",
+        "weights": "c01n-000010.safetensors",
+        "is_compatible": true,
+        "likes": 1,
+        "downloads": 0
+    },
+    {
+        "image": "images/dog.png",
+        "title": "Cyborg Style",
+        "repo": "goofyai/cyborg_style_xl",
+        "trigger_word": "cyborg style",
+        "weights": "cyborg_style_xl-off.safetensors",
+        "is_compatible": true,
+        "likes": 6,
+        "downloads": 0
+    },
+    {
+        "image": "images/ToyRedmond-ToyLoraForSDXL10.png",
+        "title": "Toy.Redmond",
+        "repo": "artificialguybr/ToyRedmond-ToyLoraForSDXL10",
+        "trigger_word": "FnkRedmAF",
+        "weights": "ToyRedmond-FnkRedmAF.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 0
+    },
+    {
+        "image": "images/voxel-xl-lora.png",
+        "title": "Voxel XL",
+        "repo": "Fictiverse/Voxel_XL_Lora",
+        "trigger_word": "voxel style",
+        "weights": "VoxelXL_v1.safetensors",
+        "is_compatible": true,
+        "likes": 12,
+        "downloads": 0
+    },
+    {
+        "image": "images/uglysonic.webp",
+        "title": "Ugly Sonic",
+        "repo": "minimaxir/sdxl-ugly-sonic-lora",
+        "trigger_word": "sonic the hedgehog",
+        "weights": "pytorch_lora_weights.bin",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 1480
+    },
+    {
+        "image": "images/corgi_brick.jpeg",
+        "title": "Lego BrickHeadz",
+        "repo": "nerijs/lego-brickheadz-xl",
+        "trigger_word": "lego brickheadz",
+        "weights": "legobrickheadz-v1.0-000004.safetensors",
+        "is_compatible": true,
+        "likes": 13,
+        "downloads": 0
+    },
+    {
+        "image": "images/lego-minifig-xl.jpeg",
+        "title": "Lego Minifig XL",
+        "repo": "nerijs/lego-minifig-xl",
+        "trigger_word": "lego minifig",
+        "weights": "legominifig-v1.0-000003.safetensors",
+        "is_compatible": true,
+        "likes": 14,
+        "downloads": 0
+    },
+    {
+        "image": "images/jojoso1.jpg",
+        "title": "JoJo's Bizarre style",
+        "repo": "Norod78/SDXL-jojoso_style-Lora",
+        "trigger_word": "jojoso style",
+        "weights": "SDXL-jojoso_style-Lora-r8.safetensors",
+        "is_compatible": true,
+        "likes": 2,
+        "downloads": 0
+    },
+    {
+        "image": "images/pikachu.webp",
+        "title": "Pikachu XL",
+        "repo": "TheLastBen/Pikachu_SDXL",
+        "trigger_word": "pikachu",
+        "weights": "pikachu.safetensors",
+        "is_compatible": true,
+        "likes": 1,
+        "downloads": 0
+    },
+    {
+        "image": "images/LogoRedmond-LogoLoraForSDXL.jpeg",
+        "title": "Logo.Redmond",
+        "repo": "artificialguybr/LogoRedmond-LogoLoraForSDXL",
+        "trigger_word": "LogoRedAF",
+        "weights": "LogoRedmond_LogoRedAF.safetensors",
+        "is_compatible": true,
+        "likes": 18,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/Norod78/SDXL-StickerSheet-Lora/resolve/main/Examples/00073-20230831113700-7780-Cthulhu%20StickerSheet%20%20_lora_SDXL-StickerSheet-Lora_1_%2C%20based%20on%20H.P%20Lovecraft%20stories%2C%20Very%20detailed%2C%20clean%2C%20high%20quality%2C%20sharp.jpg",
+        "title": "Sticker Sheet",
+        "repo": "Norod78/SDXL-StickerSheet-Lora",
+        "trigger_word": "StickerSheet",
+        "weights": "SDXL-StickerSheet-Lora.safetensors",
+        "is_compatible": true,
+        "likes": 12,
+        "downloads": 0
+    },
+    {
+        "image": "images/LineAni.Redmond.png",
+        "title": "LinearManga.Redmond",
+        "repo": "artificialguybr/LineAniRedmond-LinearMangaSDXL",
+        "trigger_word": "LineAniAF",
+        "weights": "LineAniRedmond-LineAniAF.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 0
+    },
+    {
+        "image": "images/josef_koudelka.webp",
+        "title": "Josef Koudelka Style",
+        "repo": "TheLastBen/Josef_Koudelka_Style_SDXL",
+        "trigger_word": "by josef koudelka",
+        "weights": "koud.safetensors",
+        "is_compatible": true,
+        "likes": 4,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/goofyai/Leonardo_Ai_Style_Illustration/resolve/main/leo-2.png",
+        "title": "Leonardo Style",
+        "repo": "goofyai/Leonardo_Ai_Style_Illustration",
+        "trigger_word": "leonardo style",
+        "weights": "leonardo_illustration.safetensors",
+        "is_compatible": true,
+        "likes": 4,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/Norod78/SDXL-simpstyle-Lora/resolve/main/Examples/00006-20230820150225-558-the%20girl%20with%20a%20pearl%20earring%20by%20johannes%20vermeer%20simpstyle%20_lora_SDXL-simpstyle-Lora_1_%2C%20Very%20detailed%2C%20clean%2C%20high%20quality%2C%20sh.jpg",
+        "title": "SimpStyle",
+        "repo": "Norod78/SDXL-simpstyle-Lora",
+        "trigger_word": "simpstyle",
+        "weights": "SDXL-simpstyle-Lora-r8.safetensors",
+        "is_compatible": true,
+        "likes": 6,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/artificialguybr/StoryBookRedmond/resolve/main/00162-1569823442.png",
+        "title": "Storybook.Redmond",
+        "repo": "artificialguybr/StoryBookRedmond",
+        "trigger_word": "KidsRedmAF",
+        "weights": "StoryBookRedmond-KidsRedmAF.safetensors",
+        "is_compatible": true,
+        "likes": 2,
+        "downloads": 0
+    },
+    {
+        "image": "https://huggingface.co/chillpixel/blacklight-makeup-sdxl-lora/resolve/main/preview.png",
+        "title": "Blacklight Makeup",
+        "repo": "chillpixel/blacklight-makeup-sdxl-lora",
+        "trigger_word": "with blacklight makeup",
+        "weights": "pytorch_lora_weights.bin",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 508
+    },
+    {
+        "repo": "ProomptEngineer/pe-neon-sign-style",
+        "title": "pe-neon-sign-style",
+        "trigger_word": "PENeonSign",
+        "is_compatible": true,
+        "image": "https://huggingface.co/ProomptEngineer/pe-neon-sign-style/resolve/main/2266230.jpeg",
+        "weights": "PE_NeonSignStyle.safetensors",
+        "likes": 0,
+        "downloads": 0
+    },
+    {
+        "repo": "ProomptEngineer/pe-lofi-hiphop-lofi-girl-concept",
+        "title": "pe-lofi-hiphop-lofi-girl-concept",
+        "trigger_word": "PELofiHipHop",
+        "is_compatible": true,
+        "image": "https://huggingface.co/ProomptEngineer/pe-lofi-hiphop-lofi-girl-concept/resolve/main/1967528.jpeg",
+        "weights": "PE_LofiHipHop.safetensors",
+        "likes": 0,
+        "downloads": 0
+    },
+    {
+        "repo": "ProomptEngineer/pe-shitty-fanart",
+        "title": "pe-shitty-fanart",
+        "trigger_word": "PETerribleFanArt",
+        "is_compatible": true,
+        "image": "https://huggingface.co/ProomptEngineer/pe-shitty-fanart/resolve/main/2028517.jpeg",
+        "weights": "PE_TerribleFanArtV1.safetensors",
+        "likes": 1,
+        "downloads": 0
+    },
+    {
+        "repo": "ProomptEngineer/pe-sandsculpter-style",
+        "title": "pe-sandsculpter-style",
+        "trigger_word": "PESandSculpture",
+        "is_compatible": true,
+        "image": "https://huggingface.co/ProomptEngineer/pe-sandsculpter-style/resolve/main/2234364.jpeg",
+        "weights": "PE_SandSculpture.safetensors",
+        "likes": 1,
+        "downloads": 0
+    },
+    {
+        "repo": "ProomptEngineer/pe-shitty-medieval-paintings",
+        "title": "pe-shitty-medieval-paintings",
+        "trigger_word": "PEBadMedivalArt",
+        "is_compatible": true,
+        "image": "https://huggingface.co/ProomptEngineer/pe-shitty-medieval-paintings/resolve/main/2061695.jpeg",
+        "weights": "PE_BadMedivalArt.safetensors",
+        "likes": 1,
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+        "image": "https://huggingface.co/Changchoichang2104/StableDiffusionXL-Waltz-with-Bashir-style/resolve/main/images/a22ec06b-031c-454e-8fac-6a2f7dacddff.jpeg",
+        "title": "Changchoichang2104/StableDiffusionXL-Waltz-with-Bashir-style",
+        "repo": "Changchoichang2104/StableDiffusionXL-Waltz-with-Bashir-style",
+        "trigger_word": null,
+        "weights": "waltz-with-bashir-style-000010.safetensors",
+        "is_compatible": true,
+        "likes": 1,
+        "downloads": 298
+    },
+    {
+        "image": "https://huggingface.co/e-n-v-y/envy-oil-pastel-xl-01/resolve/main/3630371.jpeg",
+        "title": "e-n-v-y/envy-oil-pastel-xl-01",
+        "repo": "e-n-v-y/envy-oil-pastel-xl-01",
+        "trigger_word": "oil pastel",
+        "weights": "EnvyOilPastelXL01.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 597
+    },
+    {
+        "image": "https://huggingface.co/e-n-v-y/envy-ink-swirl-xl-01/resolve/main/4676624.jpeg",
+        "title": "e-n-v-y/envy-ink-swirl-xl-01",
+        "repo": "e-n-v-y/envy-ink-swirl-xl-01",
+        "trigger_word": "swirling ink",
+        "weights": "EnvyInkSwirlXL01.safetensors",
+        "is_compatible": true,
+        "likes": 2,
+        "downloads": 77
+    },
+    {
+        "image": "https://huggingface.co/e-n-v-y/envy-anime-watercolor-xl-01/resolve/main/4361796.jpeg",
+        "title": "e-n-v-y/envy-anime-watercolor-xl-01",
+        "repo": "e-n-v-y/envy-anime-watercolor-xl-01",
+        "trigger_word": "watercolor",
+        "weights": "EnvyAnimeWatercolorXL01.safetensors",
+        "is_compatible": true,
+        "likes": 5,
+        "downloads": 101
+    },
+    {
+        "image": "https://huggingface.co/e-n-v-y/envy-send-noodles-xl-01/resolve/main/2879347.jpeg",
+        "title": "e-n-v-y/envy-send-noodles-xl-01",
+        "repo": "e-n-v-y/envy-send-noodles-xl-01",
+        "trigger_word": "noodles",
+        "weights": "EnvySendNoodlesXL01.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 81
+    },
+    {
+        "image": "https://huggingface.co/Blib-la/honore_daumier_lora_sdxl/resolve/main/images/00154-480187136.png",
+        "title": "Blib-la/honore_daumier_lora_sdxl",
+        "repo": "Blib-la/honore_daumier_lora_sdxl",
+        "trigger_word": "caricature, lithography by Honor\u00e9 Daumier",
+        "weights": "honore_daumier_sdxl_v1.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 127
+    },
+    {
+        "image": "https://huggingface.co/Blib-la/thomas_rowlandson_lora_sdxl/resolve/main/images/00238-2223492874.png",
+        "title": "Blib-la/thomas_rowlandson_lora_sdxl",
+        "repo": "Blib-la/thomas_rowlandson_lora_sdxl",
+        "trigger_word": "hand painted etching by thomas rowlandson",
+        "weights": "thomas_rowlandson_sdxl_v1.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 156
+    },
+    {
+        "image": "https://huggingface.co/Blib-la/eugene_atget_lora_sdxl/resolve/main/images/00147-693647877.png",
+        "title": "Blib-la/eugene_atget_lora_sdxl",
+        "repo": "Blib-la/eugene_atget_lora_sdxl",
+        "trigger_word": "by eugene atget",
+        "weights": "eugene_atget_sdxl_v1.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 131
+    },
+    {
+        "image": "https://huggingface.co/Blib-la/caricature_lora_sdxl/resolve/main/images/00543-3110114300.png",
+        "title": "Blib-la/caricature_lora_sdxl",
+        "repo": "Blib-la/caricature_lora_sdxl",
+        "trigger_word": null,
+        "weights": "caricature_sdxl_v2.safetensors",
+        "is_compatible": true,
+        "likes": 5,
+        "downloads": 227,
+        "new": true
+    },
+    {
+        "image": "https://huggingface.co/Blib-la/used_leather_lora_sdxl/resolve/main/images/00089-3023579477.png",
+        "title": "Blib-la/used_leather_lora_sdxl",
+        "repo": "Blib-la/used_leather_lora_sdxl",
+        "trigger_word": "used leather",
+        "weights": "used_leather_sdxl_v1.safetensors",
+        "is_compatible": true,
+        "likes": 9,
+        "downloads": 647
+    },
+    {
+        "image": "https://huggingface.co/Norod78/SDXL-Psychemelt-style-LoRA/resolve/main/images/00060-20240218175959-7784-Pikachu%20psychemelt%20style%20_lora_SDXL_Psychemelt_style_LoRA_0.8_.jpg",
+        "title": "Norod78/SDXL-Psychemelt-style-LoRA",
+        "repo": "Norod78/SDXL-Psychemelt-style-LoRA",
+        "trigger_word": "psychemelt style, in an LSD trip psychemelt style",
+        "weights": "SDXL_Psychemelt_style_LoRA-000007.safetensors",
+        "is_compatible": true,
+        "likes": 2,
+        "downloads": 140
+    },
+    {
+        "image": "https://huggingface.co/Norod78/fruits-and-vegetables-gone-bad-sdxl-lora/resolve/main/6326319.jpeg",
+        "title": "Norod78/fruits-and-vegetables-gone-bad-sdxl-lora",
+        "repo": "Norod78/fruits-and-vegetables-gone-bad-sdxl-lora",
+        "trigger_word": "FaVGoneBad",
+        "weights": "Fruits_and_Vegetables_gone_bad_-_SDXL_LoRA-000007.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 128
+    },
+    {
+        "image": "https://huggingface.co/Norod78/SDXL-DollZ-Style-LoRA/resolve/main/images/00045-20240122220020-7827-Pikachu%20DollZ%20style%20_lora_DollZ_style_0.8_.jpg",
+        "title": "Norod78/SDXL-DollZ-Style-LoRA",
+        "repo": "Norod78/SDXL-DollZ-Style-LoRA",
+        "trigger_word": "DollZ style",
+        "weights": "DollZ_style.safetensors",
+        "is_compatible": true,
+        "likes": 1,
+        "downloads": 80
+    },
+    {
+        "image": "https://huggingface.co/Norod78/SDXL-LaundryArt-LoRA-r32/resolve/main/images/00012-20240117133725-7777-A%20crazy%20clown%20LaundryArt%20_lora_LaundryArt_LoRA_1_.jpg",
+        "title": "Norod78/SDXL-LaundryArt-LoRA-r32",
+        "repo": "Norod78/SDXL-LaundryArt-LoRA-r32",
+        "trigger_word": "LaundryArt",
+        "weights": "LaundryArt_LoRA-r32.safetensors",
+        "is_compatible": true,
+        "likes": 2,
+        "downloads": 82,
+        "new": true
+    },
+    {
+        "image": "https://huggingface.co/Norod78/SDXL-HuWoof-LoRA/resolve/main/images/00013-20240113231444-7801-The%20Starry%20Night%20HuWoof%20_lora_SDXL_HuWoof_LoRA_1_.jpeg",
+        "title": "Norod78/SDXL-HuWoof-LoRA",
+        "repo": "Norod78/SDXL-HuWoof-LoRA",
+        "trigger_word": "HuWoof",
+        "weights": "SDXL_HuWoof_LoRA-000004.safetensors",
+        "is_compatible": true,
+        "likes": 1,
+        "downloads": 73
+    },
+    {
+        "image": "https://huggingface.co/Norod78/sdxl-chalkboarddrawing-lora/resolve/main/5329308.jpeg",
+        "title": "Norod78/sdxl-chalkboarddrawing-lora",
+        "repo": "Norod78/sdxl-chalkboarddrawing-lora",
+        "trigger_word": null,
+        "weights": "SDXL_ChalkBoardDrawing_LoRA_r8.safetensors",
+        "is_compatible": true,
+        "likes": 2,
+        "downloads": 200
+    },
+    {
+        "image": "https://huggingface.co/Norod78/SDXL-JojosoStyle-Lora-v2/resolve/main/4002501.jpeg",
+        "title": "Norod78/SDXL-JojosoStyle-Lora-v2",
+        "repo": "Norod78/SDXL-JojosoStyle-Lora-v2",
+        "trigger_word": "Jojosostyle",
+        "weights": "SDXL-JojosoStyle-Lora-v2-r16.safetensors",
+        "is_compatible": true,
+        "likes": 3,
+        "downloads": 88
+    },
+    {
+        "image": "https://huggingface.co/Norod78/sdxl-futurama-style-lora/resolve/main/2705525.jpeg",
+        "title": "Norod78/sdxl-futurama-style-lora",
+        "repo": "Norod78/sdxl-futurama-style-lora",
+        "trigger_word": "FuturamaStyle",
+        "weights": "SDXL-FuturamaStyle-Lora.safetensors",
+        "is_compatible": true,
+        "likes": 1,
+        "downloads": 96
+    },
+    {
+      "image": "https://huggingface.co/nerijs/pixelportraits192-XL-v1.0/resolve/main/images/pixel-0055-1623441747.png",
+      "title": "nerijs/pixelportraits192-XL-v1.0",
+      "repo": "nerijs/pixelportraits192-XL-v1.0",
+      "trigger_word": "",
+      "weights": "pixelportraits192-v1-2151.safetensors",
+      "is_compatible": true,
+      "likes": 2,
+      "downloads": 75,
+      "new": true
+    },
+    {
+      "image":"https://huggingface.co/artificialguybr/ps1redmond-ps1-game-graphics-lora-for-sdxl/resolve/main/5177876.jpeg",
+      "title": "artificialguybr/ps1redmond-ps1-game-graphics-lora-for-sdxl",
+      "repo": "artificialguybr/ps1redmond-ps1-game-graphics-lora-for-sdxl",
+      "trigger_word": "playstation 1 graphics, PS1 Game,",
+      "weights": "PS1Redmond-PS1Game-Playstation1Graphics.safetensors",
+      "is_compatible": true,
+      "likes": 9,
+      "downloads": 4152
+    },
+    {
+      "repo": "multimodalart/handpaintedbrazil",
+      "title": "multimodalart/handpaintedbrazil",
+      "image": "https://huggingface.co/multimodalart/handpaintedbrazil/resolve/main/image-6.png",
+      "trigger_word": "in the style of <s0><s1>",
+      "weights": "pytorch_lora_weights.safetensors",
+      "is_compatible": true,
+      "likes": 9,
+      "downloads": 155
+    }
+]

packages.txt

@@ -1 +1,2 @@
 ffmpeg
+libgl1-mesa-glx

requirements.txt

@@ -1,4 +1,23 @@
+spaces
+gradio
 torch
 torchvision
 torchaudio
-gradio
+onnxruntime-gpu
+git+https://github.com/huggingface/diffusers.git
+transformers
+accelerate
+einops
+peft
+mediapipe
+controlnet_aux
+insightface
+omegaconf
+git+https://github.com/TencentARC/PhotoMaker.git
+torchao
+git+https://github.com/xhinker/sd_embed.git
+clip_interrogator
+git+https://github.com/mantrakp04/BasicSR-fix.git
+git+https://github.com/TencentARC/GFPGAN.git
+git+https://github.com/xinntao/Real-ESRGAN.git
+aura_sr

src/tasks/images/init_sys.py

@@ -0,0 +1,128 @@
+
+import torch
+from diffusers import (
+    DiffusionPipeline,
+    AutoencoderKL,
+    FluxControlNetModel,
+    FluxMultiControlNetModel,
+    ControlNetModel,
+    AutoPipelineForText2Image,
+)
+from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
+from huggingface_hub import hf_hub_download
+from transformers import CLIPFeatureExtractor
+from photomaker import FaceAnalysis2
+
+
+# Initialize System
+def load_sd():
+    # device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+
+    # Models
+    models = [
+        {
+            "repo_id": "black-forest-labs/FLUX.1-dev",
+            "loader": "flux",
+            "compute_type": torch.bfloat16,
+        },
+        {
+            "repo_id": "SG161222/RealVisXL_V4.0",
+            "loader": "xl",
+            "compute_type": torch.float16,
+        }
+    ]
+
+    for model in models:
+        try:
+            model["pipeline"] = AutoPipelineForText2Image.from_pretrained(
+                model['repo_id'],
+                torch_dtype = model['compute_type'],
+                safety_checker = None,
+                variant = "fp16"
+            ).to(device)
+            model["pipeline"].enable_model_cpu_offload()
+        except:
+            model["pipeline"] = AutoPipelineForText2Image.from_pretrained(
+                model['repo_id'],
+                torch_dtype = model['compute_type'],
+                safety_checker = None
+            ).to(device)
+            model["pipeline"].enable_model_cpu_offload() 
+
+
+    # VAE n Refiner
+    sdxl_vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16).to(device)
+    refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", vae=sdxl_vae, torch_dtype=torch.float16, use_safetensors=True, variant="fp16").to(device)
+    refiner.enable_model_cpu_offload()
+
+
+    # Safety Checker
+    safety_checker = StableDiffusionSafetyChecker.from_pretrained("CompVis/stable-diffusion-safety-checker").to(device)
+    feature_extractor = CLIPFeatureExtractor.from_pretrained("openai/clip-vit-base-patch32", from_pt=True)
+
+
+    # Controlnets
+    controlnet_models = [
+        {
+            "repo_id": "xinsir/controlnet-depth-sdxl-1.0",
+            "name": "depth_xl",
+            "layers": ["depth"],
+            "loader": "xl",
+            "compute_type": torch.float16,
+        },
+        {
+            "repo_id": "xinsir/controlnet-canny-sdxl-1.0",
+            "name": "canny_xl",
+            "layers": ["canny"],
+            "loader": "xl",
+            "compute_type": torch.float16,
+        },
+        {
+            "repo_id": "xinsir/controlnet-openpose-sdxl-1.0",
+            "name": "openpose_xl",
+            "layers": ["pose"],
+            "loader": "xl",
+            "compute_type": torch.float16,
+        },
+        {
+            "repo_id": "xinsir/controlnet-scribble-sdxl-1.0",
+            "name": "scribble_xl",
+            "layers": ["scribble"],
+            "loader": "xl",
+            "compute_type": torch.float16,
+        },
+        {
+            "repo_id": "Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro",
+            "name": "flux1_union_pro",
+            "layers": ["canny_fl", "tile_fl", "depth_fl", "blur_fl", "pose_fl", "gray_fl", "low_quality_fl"],
+            "loader": "flux-multi",
+            "compute_type": torch.bfloat16,
+        }
+    ]
+
+    for controlnet in controlnet_models:
+        if controlnet["loader"] == "xl":
+            controlnet["controlnet"] = ControlNetModel.from_pretrained(
+                controlnet["repo_id"],
+                torch_dtype = controlnet['compute_type']
+            ).to(device)
+        elif controlnet["loader"] == "flux-multi":
+            controlnet["controlnet"] = FluxMultiControlNetModel([FluxControlNetModel.from_pretrained(
+                controlnet["repo_id"],
+                torch_dtype = controlnet['compute_type']
+            ).to(device)])
+        #TODO: Add support for flux only controlnet
+
+
+    # Face Detection (for PhotoMaker)
+    face_detector = FaceAnalysis2(providers=['CUDAExecutionProvider'], allowed_modules=['detection', 'recognition'])
+    face_detector.prepare(ctx_id=0, det_size=(640, 640))
+
+
+    # PhotoMaker V2 (for SDXL only)
+    photomaker_ckpt = hf_hub_download(repo_id="TencentARC/PhotoMaker-V2", filename="photomaker-v2.bin", repo_type="model")
+
+    return device, models, sdxl_vae, refiner, safety_checker, feature_extractor, controlnet_models, face_detector, photomaker_ckpt
+
+device, models, sdxl_vae, refiner, safety_checker, feature_extractor, controlnet_models, face_detector, photomaker_ckpt = load_sd()

src/tasks/images/sd.py

@@ -0,0 +1,327 @@
+import gc
+import random
+from typing import List, Optional
+
+import torch
+import numpy as np
+from pydantic import BaseModel
+from PIL import Image
+from diffusers import (
+    FluxPipeline,
+    FluxImg2ImgPipeline,
+    FluxInpaintPipeline,
+    FluxControlNetPipeline,
+    StableDiffusionXLPipeline,
+    StableDiffusionXLImg2ImgPipeline,
+    StableDiffusionXLInpaintPipeline,
+    StableDiffusionXLControlNetPipeline,
+    StableDiffusionXLControlNetImg2ImgPipeline,
+    StableDiffusionXLControlNetInpaintPipeline,
+    AutoPipelineForText2Image,
+    AutoPipelineForImage2Image,
+    AutoPipelineForInpainting,
+)
+from diffusers.schedulers import *
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+from controlnet_aux.processor import Processor
+from photomaker import (
+    PhotoMakerStableDiffusionXLPipeline,
+    PhotoMakerStableDiffusionXLControlNetPipeline,
+    analyze_faces
+)
+from sd_embed.embedding_funcs import get_weighted_text_embeddings_sdxl, get_weighted_text_embeddings_flux1
+
+from .init_sys import device, models, refiner, safety_checker, feature_extractor, controlnet_models, face_detector
+
+
+# Models
+class ControlNetReq(BaseModel):
+    controlnets: List[str] # ["canny", "tile", "depth"]
+    control_images: List[Image.Image]
+    controlnet_conditioning_scale: List[float]
+
+
+class SDReq(BaseModel):
+    model: str = ""
+    prompt: str = ""
+    negative_prompt: Optional[str] = "black-forest-labs/FLUX.1-dev"
+    fast_generation: Optional[bool] = True
+    loras: Optional[list] = []
+    embeddings: Optional[list] = []
+    resize_mode: Optional[str] = "resize_and_fill" # resize_only, crop_and_resize, resize_and_fill
+    scheduler = Optional[str] = "euler_fl"
+    height: int = 1024
+    width: int = 1024
+    num_images_per_prompt: int = 1
+    num_inference_steps: int = 8
+    guidance_scale: float = 3.5
+    seed: Optional[int] = 0
+    refiner: bool = False
+    vae: bool = True
+    controlnet_config: Optional[ControlNetReq] = None
+    photomaker_images: Optional[List[Image.Image]] = None
+
+
+class SDImg2ImgReq(SDReq):
+    image: Image.Image
+    strength: float = 1.0
+
+
+class SDInpaintReq(SDImg2ImgReq):
+    mask_image: Image.Image
+
+
+# Helper functions
+def get_controlnet(controlnet_config: ControlNetReq):
+    control_mode = []
+    controlnet = []
+    
+    for m in controlnet_models:
+        for c in controlnet_config.controlnets:
+            if c in m["layers"]:
+                control_mode.append(m["layers"].index(c))
+                controlnet.append(m["controlnet"])
+    
+    return controlnet, control_mode
+
+
+def get_pipe(request: SDReq | SDImg2ImgReq | SDInpaintReq):
+    for m in models:
+        if m["repo_id"] == request.model:
+            pipeline = m['pipeline']
+            controlnet, control_mode = get_controlnet(request.controlnet_config) if request.controlnet_config else (None, None)
+            
+            pipe_args = {
+                "pipeline": pipeline,
+                "control_mode": control_mode,
+            }
+            if request.controlnet_config:
+                pipe_args["controlnet"] = controlnet
+
+            if isinstance(request, SDReq):
+                pipe_args['pipeline'] = AutoPipelineForText2Image.from_pipe(**pipe_args)
+            elif isinstance(request, SDImg2ImgReq):
+                pipe_args['pipeline'] = AutoPipelineForImage2Image.from_pipe(**pipe_args)
+            elif isinstance(request, SDInpaintReq):
+                pipe_args['pipeline'] = AutoPipelineForInpainting.from_pipe(**pipe_args)
+            else:
+                raise ValueError(f"Unknown request type: {type(request)}")
+        
+    return pipe_args
+
+
+def load_scheduler(pipeline, scheduler):
+    schedulers = {
+        "dpmpp_2m": (DPMSolverMultistepScheduler, {}),
+        "dpmpp_2m_k": (DPMSolverMultistepScheduler, {"use_karras_sigmas": True}),
+        "dpmpp_2m_sde": (DPMSolverMultistepScheduler, {"algorithm_type": "sde-dpmsolver++"}),
+        "dpmpp_2m_sde_k": (DPMSolverMultistepScheduler, {"algorithm_type": "sde-dpmsolver++", "use_karras_sigmas": True}),
+        "dpmpp_sde": (DPMSolverSinglestepScheduler, {}),
+        "dpmpp_sde_k": (DPMSolverSinglestepScheduler, {"use_karras_sigmas": True}),
+        "dpm2": (KDPM2DiscreteScheduler, {}),
+        "dpm2_k": (KDPM2DiscreteScheduler, {"use_karras_sigmas": True}),
+        "dpm2_a": (KDPM2AncestralDiscreteScheduler, {}),
+        "dpm2_a_k": (KDPM2AncestralDiscreteScheduler, {"use_karras_sigmas": True}),
+        "euler": (EulerDiscreteScheduler, {}),
+        "euler_a": (EulerAncestralDiscreteScheduler, {}),
+        "heun": (HeunDiscreteScheduler, {}),
+        "lms": (LMSDiscreteScheduler, {}),
+        "lms_k": (LMSDiscreteScheduler, {"use_karras_sigmas": True}),
+        "deis": (DEISMultistepScheduler, {}),
+        "unipc": (UniPCMultistepScheduler, {}),
+        "fm_euler": (FlowMatchEulerDiscreteScheduler, {}),
+    }
+    scheduler_class, kwargs = schedulers.get(scheduler, (None, {}))
+    
+    if scheduler_class is not None:
+        scheduler = scheduler_class.from_config(pipeline.scheduler.config, **kwargs)
+    else:
+        raise ValueError(f"Unknown scheduler: {scheduler}")
+    
+    return scheduler
+
+
+def load_loras(pipeline, loras, fast_generation):
+    for i, lora in enumerate(loras):
+        pipeline.load_lora_weights(lora['repo_id'], adapter_name=f"lora_{i}")
+    adapter_names = [f"lora_{i}" for i in range(len(loras))]
+    adapter_weights = [lora['weight'] for lora in loras]
+    
+    if fast_generation:
+        hyper_lora = hf_hub_download(
+            "ByteDance/Hyper-SD",
+            "Hyper-FLUX.1-dev-8steps-lora.safetensors" if isinstance(pipeline, FluxPipeline) else "Hyper-SDXL-2steps-lora.safetensors"
+        )
+        hyper_weight = 0.125 if isinstance(pipeline, FluxPipeline) else 1.0
+        pipeline.load_lora_weights(hyper_lora, adapter_name="hyper_lora")
+        adapter_names.append("hyper_lora")
+        adapter_weights.append(hyper_weight)
+    
+    pipeline.set_adapters(adapter_names, adapter_weights)
+
+
+def load_xl_embeddings(pipeline, embeddings):
+    for embedding in embeddings:
+        state_dict = load_file(hf_hub_download(embedding['repo_id']))
+        pipeline.load_textual_inversion(state_dict['clip_g'], token=embedding['token'], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
+        pipeline.load_textual_inversion(state_dict["clip_l"], token=embedding['token'], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
+
+
+def resize_images(images: List[Image.Image], height: int, width: int, resize_mode: str):
+    for image in images:
+        if resize_mode == "resize_only":
+            image = image.resize((width, height))
+        elif resize_mode == "crop_and_resize":
+            image = image.crop((0, 0, width, height))
+        elif resize_mode == "resize_and_fill":
+            image = image.resize((width, height), Image.Resampling.LANCZOS)
+
+    return images
+
+
+def get_controlnet_images(controlnets: List[str], control_images: List[Image.Image], height: int, width: int, resize_mode: str):
+    response_images = []
+    control_images = resize_images(control_images, height, width, resize_mode)
+    for controlnet, image in zip(controlnets, control_images):
+        if controlnet == "canny" or controlnet == "canny_xs" or controlnet == "canny_fl":
+            processor = Processor('canny')
+        elif controlnet == "depth" or controlnet == "depth_xs" or controlnet == "depth_fl":
+            processor = Processor('depth_midas')
+        elif controlnet == "pose" or controlnet == "pose_fl":
+            processor = Processor('openpose_full')
+        elif controlnet == "scribble":
+            processor = Processor('scribble')
+        else:
+            raise ValueError(f"Invalid Controlnet: {controlnet}")
+    
+        response_images.append(processor(image, to_pil=True))
+    
+    return response_images
+
+
+def check_image_safety(images: List[Image.Image]):
+    safety_checker_input = feature_extractor(images, return_tensors="pt").to("cuda")
+    has_nsfw_concepts = safety_checker(
+        images=[images],
+        clip_input=safety_checker_input.pixel_values.to("cuda"),
+    )
+    
+    return has_nsfw_concepts[1]
+
+
+def get_prompt_attention(pipeline, prompt, negative_prompt):
+    if isinstance(pipeline, (FluxPipeline, FluxImg2ImgPipeline, FluxInpaintPipeline, FluxControlNetPipeline)):
+        prompt_embeds, pooled_prompt_embeds = get_weighted_text_embeddings_flux1(pipeline, prompt)
+        return prompt_embeds, None, pooled_prompt_embeds, None
+    elif isinstance(pipeline, StableDiffusionXLPipeline):
+        prompt_embeds, prompt_neg_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds = get_weighted_text_embeddings_sdxl(pipeline, prompt, negative_prompt)
+        return prompt_embeds, prompt_neg_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds
+    else:
+        raise ValueError(f"Invalid pipeline type: {type(pipeline)}")
+
+
+def get_photomaker_images(photomaker_images: List[Image.Image], height: int, width: int, resize_mode: str):
+    image_input_ids = []
+    image_id_embeds = []
+    photomaker_images = resize_images(photomaker_images, height, width, resize_mode)
+    
+    for image in photomaker_images:
+        image_input_ids.append(img)
+        img = np.array(image)[:, :, ::-1]
+        faces = analyze_faces(face_detector, image)
+        if len(faces) > 0:
+            image_id_embeds.append(torch.from_numpy(faces[0]['embeddings']))
+        else:
+            raise ValueError("No face detected in the image")
+    
+    return image_input_ids, image_id_embeds
+
+
+def cleanup(pipeline, loras = None, embeddings = None):
+    if loras:
+        pipeline.disable_lora()
+        pipeline.unload_lora_weights()
+    if embeddings:
+        pipeline.unload_textual_inversion()
+    gc.collect()
+    torch.cuda.empty_cache()
+
+
+# Gen function
+def gen_img(
+    request: SDReq | SDImg2ImgReq | SDInpaintReq
+):
+    pipeline_args = get_pipe(request)
+    pipeline = pipeline_args['pipeline']
+    try:
+        pipeline.scheduler = load_scheduler(pipeline, request.scheduler)
+        
+        load_loras(pipeline, request.loras, request.fast_generation)
+        load_xl_embeddings(pipeline, request.embeddings)
+        
+        control_images = get_controlnet_images(request.controlnet_config.controlnets, request.controlnet_config.control_images, request.height, request.width, request.resize_mode) if request.controlnet_config else None
+        photomaker_images, photomaker_id_embeds = get_photomaker_images(request.photomaker_images, request.height, request.width) if request.photomaker_images else (None, None)
+        
+        positive_prompt_embeds, negative_prompt_embeds, positive_prompt_pooled, negative_prompt_pooled = get_prompt_attention(pipeline, request.prompt, request.negative_prompt)
+        
+        # Common args
+        args = {
+            'prompt_embeds': positive_prompt_embeds,
+            'pooled_prompt_embeds': positive_prompt_pooled,
+            'height': request.height,
+            'width': request.width,
+            'num_images_per_prompt': request.num_images_per_prompt,
+            'num_inference_steps': request.num_inference_steps,
+            'guidance_scale': request.guidance_scale,
+            'generator': [torch.Generator(device=device).manual_seed(request.seed + i) if not request.seed is any([None, 0, -1]) else torch.Generator(device=device).manual_seed(random.randint(0, 2**32 - 1)) for i in range(request.num_images_per_prompt)],
+        }
+        
+        if isinstance(pipeline, any([StableDiffusionXLPipeline, StableDiffusionXLImg2ImgPipeline, StableDiffusionXLInpaintPipeline,
+                                     StableDiffusionXLControlNetPipeline, StableDiffusionXLControlNetImg2ImgPipeline, StableDiffusionXLControlNetInpaintPipeline])):
+            args['clip_skip'] = request.clip_skip
+            args['negative_prompt_embeds'] = negative_prompt_embeds
+            args['negative_pooled_prompt_embeds'] = negative_prompt_pooled
+        
+        if isinstance(pipeline, FluxControlNetPipeline) and request.controlnet_config:
+            args['control_mode'] = pipeline_args['control_mode']
+            args['control_image'] = control_images
+            args['controlnet_conditioning_scale'] = request.controlnet_conditioning_scale
+        
+        if not isinstance(pipeline, FluxControlNetPipeline) and request.controlnet_config:
+            args['controlnet_conditioning_scale'] = request.controlnet_conditioning_scale
+        
+            if isinstance(request, SDReq):
+                args['image'] = control_images
+            elif isinstance(request, (SDImg2ImgReq, SDInpaintReq)):
+                args['control_image'] = control_images
+        
+        if request.photomaker_images and isinstance(pipeline, any([PhotoMakerStableDiffusionXLPipeline, PhotoMakerStableDiffusionXLControlNetPipeline])):
+            args['input_id_images'] = photomaker_images
+            args['input_id_embeds'] = photomaker_id_embeds
+            args['start_merge_step'] = 10
+        
+        if isinstance(request, SDImg2ImgReq):
+            args['image'] = resize_images([request.image], request.height, request.width, request.resize_mode)
+            args['strength'] = request.strength
+        elif isinstance(request, SDInpaintReq):
+            args['image'] = resize_images([request.image], request.height, request.width, request.resize_mode)
+            args['mask_image'] = resize_images([request.mask_image], request.height, request.width, request.resize_mode)
+            args['strength'] = request.strength
+        
+        images = pipeline(**args).images
+        
+        if request.refiner:
+            images = refiner(
+                prompt=request.prompt,
+                num_inference_steps=40,
+                denoising_start=0.7,
+                image=images.images
+            ).images
+        
+        cleanup(pipeline, request.loras, request.embeddings)
+        
+        return images
+    except Exception as e:
+        cleanup(pipeline, request.loras, request.embeddings)
+        raise ValueError(f"Error generating image: {e}") from e

src/ui/images.py

@@ -1,14 +1,10 @@
-import os
-
 import gradio as gr
 
-from .tabs import (
-    flux_tab,
-)
+from .tabs import flux_tab
 
 def image_tab():
     with gr.Tabs():
-        with gr.Tab(label="Flux"):
+        with gr.Tab("Flux"):
             flux_tab()
-        with gr.Tab(label="SDXL"):
-            gr.Label("Coming soon!")
+        with gr.Tab("SDXL"):
+            gr.Label("To be implemented")

src/ui/tabs/__init__.py

@@ -1 +1 @@
-from .images.flux_tab import flux_tab
+from .images.flux import flux_tab

src/ui/tabs/images/flux.py

@@ -0,0 +1,496 @@
+import json
+import random
+from typing import List
+
+import spaces
+import gradio as gr
+from huggingface_hub import ModelCard
+
+from tasks.images.sd import gen_img, ControlNetReq, SDReq, SDImg2ImgReq, SDInpaintReq
+
+
+models = ["black-forest-labs/FLUX.1-dev"]
+loras = json.loads("data/images/lora/flux.json")
+
+
+def flux_tab():
+    """
+    Create the image tab for Generative Image Generation Models
+    
+    Args:
+    models: list
+        A list containing the models repository paths
+    gap_iol, gap_la, gap_le, gap_eio, gap_io: Optional[List[dict]]
+        A list of dictionaries containing the title and component for the custom gradio component
+        Example:
+        def gr_comp():
+            gr.Label("Hello World")
+        
+        [
+            {
+                'title': "Title",
+                'component': gr_comp()
+            }
+        ]
+    loras: list
+        A list of dictionaries containing the image and title for the Loras Gallery
+        Generally a loaded json file from the data folder
+    
+    """
+    def process_gaps(gaps: List[dict]):
+        for gap in gaps:
+            with gr.Accordion(gap['title']):
+                gap['component']
+    
+    
+    with gr.Row():
+        with gr.Column():
+            with gr.Group() as image_options:
+                model = gr.Dropdown(label="Models", choices=models, value=models[0], interactive=True)
+                prompt = gr.Textbox(lines=5, label="Prompt")
+                negative_prompt = gr.Textbox(label="Negative Prompt")
+                fast_generation = gr.Checkbox(label="Fast Generation (Hyper-SD) 🧪")
+            
+            
+            with gr.Accordion("Loras", open=True): # Lora Gallery
+                lora_gallery = gr.Gallery(
+                    label="Gallery",
+                    value=[(lora['image'], lora['title']) for lora in loras],
+                    allow_preview=False,
+                    columns=[3],
+                    rows=[2],
+                    type="pil",
+                )
+                
+                with gr.Group():
+                    with gr.Column():
+                        with gr.Row():
+                            custom_lora = gr.Textbox(label="Custom Lora", info="Enter a Huggingface repo path")
+                            selected_lora = gr.Textbox(label="Selected Lora", info="Choose from the gallery or enter a custom LoRA")
+                        
+                        custom_lora_info = gr.HTML(visible=False)
+                        add_lora = gr.Button(value="Add LoRA")
+                        
+                        enabled_loras = gr.State(value=[])
+                        with gr.Group():
+                            with gr.Row():
+                                for i in range(6): # only support max 6 loras due to inference time
+                                    with gr.Column():
+                                        with gr.Column(scale=2):
+                                            globals()[f"lora_slider_{i}"] = gr.Slider(label=f"LoRA {i+1}", minimum=0, maximum=1, step=0.01, value=0.8, visible=False, interactive=True)
+                                        with gr.Column():
+                                            globals()[f"lora_remove_{i}"] = gr.Button(value="Remove LoRA", visible=False)
+
+            
+            with gr.Accordion("Embeddings", open=False): # Embeddings
+                gr.Label("To be implemented")
+            
+            
+            with gr.Accordion("Image Options"): # Image Options
+                with gr.Tabs():
+                    image_options = {
+                        "img2img": "Upload Image",
+                        "inpaint": "Upload Image",
+                        "canny": "Upload Image",
+                        "pose": "Upload Image",
+                        "depth": "Upload Image",
+                    }
+                    
+                    for image_option, label in image_options.items():
+                        with gr.Tab(image_option):
+                            if not image_option in ['inpaint', 'scribble']:
+                                globals()[f"{image_option}_image"] = gr.Image(label=label, type="pil")
+                            elif image_option in ['inpaint', 'scribble']:
+                                globals()[f"{image_option}_image"] = gr.ImageEditor(
+                                    label=label,
+                                    image_mode='RGB',
+                                    layers=False,
+                                    brush=gr.Brush(colors=["#FFFFFF"], color_mode="fixed") if image_option == 'inpaint' else gr.Brush(),
+                                    interactive=True,
+                                    type="pil",
+                                )
+                            
+                            # Image Strength (Co-relates to controlnet strength, strength for img2img n inpaint)
+                            globals()[f"{image_option}_strength"] = gr.Slider(label="Strength", minimum=0, maximum=1, step=0.01, value=1.0, interactive=True)
+                    
+                    resize_mode = gr.Radio(
+                        label="Resize Mode",
+                        choices=["crop and resize", "resize only", "resize and fill"],
+                        value="resize and fill",
+                        interactive=True
+                    )
+        
+        
+        with gr.Column():
+            with gr.Group():
+                output_images = gr.Gallery(
+                        label="Output Images",
+                        value=[],
+                        allow_preview=True,
+                        type="pil",
+                        interactive=True,
+                    )
+                generate_images = gr.Button(value="Generate Images", variant="primary")            
+            
+            with gr.Accordion("Advance Settings", open=True):
+                with gr.Row():
+                    scheduler = gr.Dropdown(
+                        label="Scheduler",
+                        choices = [
+                            "fm_euler"
+                        ],
+                        value="fm_euler",
+                        interactive=True
+                    )
+
+                with gr.Row():
+                    for column in range(2):
+                        with gr.Column():
+                            options = [
+                                ("Height", "image_height", 64, 1024, 64, 1024, True),
+                                ("Width", "image_width", 64, 1024, 64, 1024, True),
+                                ("Num Images Per Prompt", "image_num_images_per_prompt", 1, 4, 1, 1, True),
+                                ("Num Inference Steps", "image_num_inference_steps", 1, 100, 1, 20, True),
+                                ("Clip Skip", "image_clip_skip", 0, 2, 1, 2, False),
+                                ("Guidance Scale", "image_guidance_scale", 0, 20, 0.5, 3.5, True),
+                                ("Seed", "image_seed", 0, 100000, 1, random.randint(0, 100000), True),
+                            ]
+                            for label, var_name, min_val, max_val, step, value, visible in options[column::2]:
+                                globals()[var_name] = gr.Slider(label=label, minimum=min_val, maximum=max_val, step=step, value=value, visible=visible, interactive=True)
+                
+                with gr.Row():
+                    refiner = gr.Checkbox(
+                        label="Refiner 🧪",
+                        value=False,
+                    )
+                    vae = gr.Checkbox(
+                        label="VAE",
+                        value=True,
+                    )
+
+
+    # Events
+    # Base Options
+    fast_generation.change(update_fast_generation, [model, fast_generation], [image_guildance_scale, image_num_inference_steps]) # Fast Generation # type: ignore
+    
+
+    # Lora Gallery
+    lora_gallery.select(selected_lora_from_gallery, None, selected_lora)
+    custom_lora.change(update_selected_lora, custom_lora, [custom_lora, selected_lora])
+    add_lora.click(add_to_enabled_loras, [model, selected_lora, enabled_loras], [selected_lora, custom_lora_info, enabled_loras])
+    enabled_loras.change(update_lora_sliders, enabled_loras, [lora_slider_0, lora_slider_1, lora_slider_2, lora_slider_3, lora_slider_4, lora_slider_5, lora_remove_0, lora_remove_1, lora_remove_2, lora_remove_3, lora_remove_4, lora_remove_5]) # type: ignore
+
+    for i in range(6):
+        globals()[f"lora_remove_{i}"].click(
+            lambda enabled_loras, index=i: remove_from_enabled_loras(enabled_loras, index),
+            [enabled_loras],
+            [enabled_loras]
+        )
+    
+
+    # Generate Image
+    generate_images.click(
+        generate_image, # type: ignore
+        [
+            model, prompt, negative_prompt, fast_generation, enabled_loras,
+            lora_slider_0, lora_slider_1, lora_slider_2, lora_slider_3, lora_slider_4, lora_slider_5, # type: ignore
+            img2img_image, inpaint_image, canny_image, pose_image, depth_image, # type: ignore
+            img2img_strength, inpaint_strength, canny_strength, pose_strength, depth_strength, # type: ignore
+            resize_mode,
+            scheduler, image_height, image_width, image_num_images_per_prompt, # type: ignore
+            image_num_inference_steps, image_guidance_scale, image_seed, # type: ignore
+            refiner, vae
+        ],
+        [output_images]
+    )
+
+
+# Functions
+def update_fast_generation(model, fast_generation):
+    if fast_generation:
+        return (
+            gr.update(
+                value=3.5
+            ),
+            gr.update(
+                value=8
+            )
+        )
+
+
+def selected_lora_from_gallery(evt: gr.SelectData):
+    return (
+        gr.update(
+            value=evt.index
+        )
+    )
+
+
+def update_selected_lora(custom_lora):
+    link = custom_lora.split("/")
+    
+    if len(link) == 2:
+        model_card = ModelCard.load(custom_lora)
+        trigger_word = model_card.data.get("instance_prompt", "")
+        image_url = f"""https://huggingface.co/{custom_lora}/resolve/main/{model_card.data.get("widget", [{}])[0].get("output", {}).get("url", None)}"""
+        
+        custom_lora_info_css = """
+        <style>
+            .custom-lora-info {
+                font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Oxygen', 'Ubuntu', 'Cantarell', 'Fira Sans', 'Droid Sans', 'Helvetica Neue', sans-serif;
+                background: linear-gradient(135deg, #4a90e2, #7b61ff);
+                color: white;
+                padding: 16px;
+                border-radius: 8px;
+                box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+                margin: 16px 0;
+            }
+            .custom-lora-header {
+                font-size: 18px;
+                font-weight: 600;
+                margin-bottom: 12px;
+            }
+            .custom-lora-content {
+                display: flex;
+                align-items: center;
+                background-color: rgba(255, 255, 255, 0.1);
+                border-radius: 6px;
+                padding: 12px;
+            }
+            .custom-lora-image {
+                width: 80px;
+                height: 80px;
+                object-fit: cover;
+                border-radius: 6px;
+                margin-right: 16px;
+            }
+            .custom-lora-text h3 {
+                margin: 0 0 8px 0;
+                font-size: 16px;
+                font-weight: 600;
+            }
+            .custom-lora-text small {
+                font-size: 14px;
+                opacity: 0.9;
+            }
+            .custom-trigger-word {
+                background-color: rgba(255, 255, 255, 0.2);
+                padding: 2px 6px;
+                border-radius: 4px;
+                font-weight: 600;
+            }
+        </style>
+        """
+
+        custom_lora_info_html = f"""
+        <div class="custom-lora-info">
+            <div class="custom-lora-header">Custom LoRA: {custom_lora}</div>
+            <div class="custom-lora-content">
+                <img class="custom-lora-image" src="{image_url}" alt="LoRA preview">
+                <div class="custom-lora-text">
+                    <h3>{link[1].replace("-", " ").replace("_", " ")}</h3>
+                    <small>{"Using: <span class='custom-trigger-word'>"+trigger_word+"</span> as the trigger word" if trigger_word else "No trigger word found. If there's a trigger word, include it in your prompt"}</small>
+                </div>
+            </div>
+        </div>
+        """
+
+        custom_lora_info_html = f"{custom_lora_info_css}{custom_lora_info_html}"
+
+        return (
+            gr.update( # selected_lora
+                value=custom_lora,
+            ),
+            gr.update( # custom_lora_info
+                value=custom_lora_info_html,
+                visible=True
+            )
+        )
+
+    else:
+        return (
+            gr.update( # selected_lora
+                value=custom_lora,
+            ),
+            gr.update( # custom_lora_info
+                value=custom_lora_info_html if len(link) == 0 else "",
+                visible=False
+            )
+        )
+
+
+def add_to_enabled_loras(model, selected_lora, enabled_loras):
+    lora_data = loras
+    try:
+        selected_lora = int(selected_lora)
+        
+        if 0 <= selected_lora: # is the index of the lora in the gallery
+            lora_info = lora_data[selected_lora]
+            enabled_loras.append({
+                "repo_id": lora_info["repo"],
+                "trigger_word": lora_info["trigger_word"]
+            })
+    except ValueError:
+        link = selected_lora.split("/")
+        if len(link) == 2:
+            model_card = ModelCard.load(selected_lora)
+            trigger_word = model_card.data.get("instance_prompt", "")
+            enabled_loras.append({
+                "repo_id": selected_lora,
+                "trigger_word": trigger_word
+            })
+    
+    return (
+        gr.update( # selected_lora
+            value=""
+        ),
+        gr.update( # custom_lora_info
+            value="",
+            visible=False
+        ),
+        gr.update( # enabled_loras
+            value=enabled_loras
+        )
+    )
+
+
+def update_lora_sliders(enabled_loras):
+    sliders = []
+    remove_buttons = []
+    
+    for lora in enabled_loras:
+        sliders.append(
+            gr.update(
+                label=lora.get("repo_id", ""),
+                info=f"Trigger Word: {lora.get('trigger_word', '')}",
+                visible=True,
+                interactive=True
+            )
+        )
+        remove_buttons.append(
+            gr.update(
+                visible=True,
+                interactive=True
+            )
+        )
+    
+    if len(sliders) < 6:
+        for i in range(len(sliders), 6):
+            sliders.append(
+                gr.update(
+                    visible=False
+                )
+            )
+            remove_buttons.append(
+                gr.update(
+                    visible=False
+                )
+            )
+    
+    return *sliders, *remove_buttons
+
+
+def remove_from_enabled_loras(enabled_loras, index):
+    enabled_loras.pop(index)
+    return (
+        gr.update(
+            value=enabled_loras
+        )
+    )
+
+
+@spaces.GPU
+def generate_image(
+        model, prompt, negative_prompt, fast_generation, enabled_loras,
+        lora_slider_0, lora_slider_1, lora_slider_2, lora_slider_3, lora_slider_4, lora_slider_5,
+        img2img_image, inpaint_image, canny_image, pose_image, depth_image,
+        img2img_strength, inpaint_strength, canny_strength, pose_strength, depth_strength,
+        resize_mode,
+        scheduler, image_height, image_width, image_num_images_per_prompt,
+        image_num_inference_steps, image_guidance_scale, image_seed,
+        refiner, vae
+    ):
+        base_args = {
+            "model": model,
+            "prompt": prompt,
+            "negative_prompt": negative_prompt,
+            "fast_generation": fast_generation,
+            "loras": None,
+            "resize_mode": resize_mode,
+            "scheduler": scheduler,
+            "height": int(image_height),
+            "width": int(image_width),
+            "num_images_per_prompt": float(image_num_images_per_prompt),
+            "num_inference_steps": float(image_num_inference_steps),
+            "guidance_scale": float(image_guidance_scale),
+            "seed": int(image_seed),
+            "refiner": refiner,
+            "vae": vae,
+            "controlnet_config": None,
+        }
+        base_args = SDReq(**base_args)
+
+        if len(enabled_loras) > 0:
+            base_args.loras = []
+            for enabled_lora, lora_slider in zip(enabled_loras, [lora_slider_0, lora_slider_1, lora_slider_2, lora_slider_3, lora_slider_4, lora_slider_5]):
+                if enabled_lora.get("repo_id", None):
+                    base_args.loras.append(
+                        {
+                            "repo_id": enabled_lora["repo_id"],
+                            "weight": lora_slider
+                        }
+                    )
+        
+        image = None
+        mask_image = None
+        strength = None
+        
+        if img2img_image:
+            image = img2img_image
+            strength = float(img2img_strength)
+            
+            base_args = SDImg2ImgReq(
+                **base_args.__dict__,
+                image=image,
+                strength=strength
+            )
+        elif inpaint_image:
+            image = inpaint_image['background'] if not all(pixel == (0, 0, 0) for pixel in list(inpaint_image['background'].getdata())) else None
+            mask_image = inpaint_image['layers'][0] if image else None
+            strength = float(inpaint_strength)
+            
+            base_args = SDInpaintReq(
+                **base_args.__dict__,
+                image=image,
+                mask_image=mask_image,
+                strength=strength
+            )
+        elif any([canny_image, pose_image, depth_image]):
+            base_args.controlnet_config = ControlNetReq(
+                controlnets=[],
+                control_images=[],
+                controlnet_conditioning_scale=[]
+            )
+            
+            if canny_image:
+                base_args.controlnet_config.controlnets.append("canny_fl")
+                base_args.controlnet_config.control_images.append(canny_image)
+                base_args.controlnet_config.controlnet_conditioning_scale.append(float(canny_strength))
+            if pose_image:
+                base_args.controlnet_config.controlnets.append("pose_fl")
+                base_args.controlnet_config.control_images.append(pose_image)
+                base_args.controlnet_config.controlnet_conditioning_scale.append(float(pose_strength))
+            if depth_image:
+                base_args.controlnet_config.controlnets.append("depth_fl")
+                base_args.controlnet_config.control_images.append(depth_image)
+                base_args.controlnet_config.controlnet_conditioning_scale.append(float(depth_strength))
+        else:
+            base_args = SDReq(**base_args.__dict__)
+
+        images = gen_img(base_args)
+        
+        return (
+            gr.update(
+                value=images
+            )
+        )

src/ui/tabs/images/flux_tab.py

@@ -1,10 +0,0 @@
-import gradio as gr
-
-def flux_tab():
-    with gr.Row():
-        with gr.Column():
-            prompt = gr.Textbox(lines=5, label="Prompt")
-            
-        with gr.Column():
-            with gr.Group():
-                output_image = gr.Image()