fofr
/
aura-flow
Largest completely open sourced flow-based generation model that is capable of text-to-image generation
Prediction
fofr/aura-flow:ae5ab66aIDrnedc45525rgg0cgms38da3avmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- cfg
- 3.5
- shift
- 1.73
- steps
- 25
- width
- 1024
- height
- 1024
- prompt
- a close-up portrait photo of a cute cat sitting on a purple armchair
- sampler
- uni_pc
- scheduler
- normal
- output_format
- webp
- output_quality
- 80
- negative_prompt
- ugly, broken
- number_of_images
- 1
{ "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "a close-up portrait photo of a cute cat sitting on a purple armchair", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/aura-flow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/aura-flow:ae5ab66a7d1ca7ee44cf8c50265d3bafdef23734d03d66063d1c8fcf82f0c17b", { input: { cfg: 3.5, shift: 1.73, steps: 25, width: 1024, height: 1024, prompt: "a close-up portrait photo of a cute cat sitting on a purple armchair", sampler: "uni_pc", scheduler: "normal", output_format: "webp", output_quality: 80, negative_prompt: "ugly, broken", number_of_images: 1 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/aura-flow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/aura-flow:ae5ab66a7d1ca7ee44cf8c50265d3bafdef23734d03d66063d1c8fcf82f0c17b", input={ "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "a close-up portrait photo of a cute cat sitting on a purple armchair", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/aura-flow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "ae5ab66a7d1ca7ee44cf8c50265d3bafdef23734d03d66063d1c8fcf82f0c17b", "input": { "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "a close-up portrait photo of a cute cat sitting on a purple armchair", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-07-12T09:29:51.167596Z", "created_at": "2024-07-12T09:29:26.033000Z", "data_removed": false, "error": null, "id": "rnedc45525rgg0cgms38da3avm", "input": { "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "a close-up portrait photo of a cute cat sitting on a purple armchair", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 }, "logs": "Random seed set to: 3117986007\nRunning workflow\ngot prompt\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 3, title: KSampler, class type: KSampler\n 0%| | 0/25 [00:00<?, ?it/s]\n 4%|▍ | 1/25 [00:00<00:04, 5.31it/s]\n 8%|▊ | 2/25 [00:01<00:14, 1.56it/s]\n 12%|█▏ | 3/25 [00:02<00:17, 1.27it/s]\n 16%|█▌ | 4/25 [00:03<00:17, 1.17it/s]\n 20%|██ | 5/25 [00:04<00:17, 1.12it/s]\n 24%|██▍ | 6/25 [00:04<00:17, 1.10it/s]\n 28%|██▊ | 7/25 [00:05<00:16, 1.08it/s]\n 32%|███▏ | 8/25 [00:06<00:15, 1.07it/s]\n 36%|███▌ | 9/25 [00:07<00:15, 1.06it/s]\n 40%|████ | 10/25 [00:08<00:14, 1.05it/s]\n 44%|████▍ | 11/25 [00:09<00:13, 1.05it/s]\n 48%|████▊ | 12/25 [00:10<00:12, 1.05it/s]\n 52%|█████▏ | 13/25 [00:11<00:11, 1.05it/s]\n 56%|█████▌ | 14/25 [00:12<00:10, 1.05it/s]\n 60%|██████ | 15/25 [00:13<00:09, 1.05it/s]\n 64%|██████▍ | 16/25 [00:14<00:08, 1.04it/s]\n 68%|██████▊ | 17/25 [00:15<00:07, 1.04it/s]\n 72%|███████▏ | 18/25 [00:16<00:06, 1.04it/s]\n 76%|███████▌ | 19/25 [00:17<00:05, 1.04it/s]\n 80%|████████ | 20/25 [00:18<00:04, 1.04it/s]\n 84%|████████▍ | 21/25 [00:19<00:03, 1.04it/s]\n 88%|████████▊ | 22/25 [00:20<00:02, 1.04it/s]\n 92%|█████████▏| 23/25 [00:21<00:01, 1.04it/s]\n 96%|█████████▌| 24/25 [00:22<00:00, 1.04it/s]\n100%|██████████| 25/25 [00:23<00:00, 1.19s/it]\n100%|██████████| 25/25 [00:23<00:00, 1.04it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 24.41 seconds\noutputs: {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nComfyUI_00001_.png", "metrics": { "predict_time": 25.12559834, "total_time": 25.134596 }, "output": [ "https://replicate.delivery/pbxt/bep7lY6J7l2TdqUtxk3BuLkbseHXdFGdNnRvvuN7eFxdMVPmA/ComfyUI_00001_.webp" ], "started_at": "2024-07-12T09:29:26.041998Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/rnedc45525rgg0cgms38da3avm", "cancel": "https://api.replicate.com/v1/predictions/rnedc45525rgg0cgms38da3avm/cancel" }, "version": "2f38ca7d2e0e84f05bef7980cf8c7c1c36ba2b9416eee3d57e73b67c338eaff0" }
Generated inRandom seed set to: 3117986007 Running workflow got prompt Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode Executing node 3, title: KSampler, class type: KSampler 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:04, 5.31it/s] 8%|▊ | 2/25 [00:01<00:14, 1.56it/s] 12%|█▏ | 3/25 [00:02<00:17, 1.27it/s] 16%|█▌ | 4/25 [00:03<00:17, 1.17it/s] 20%|██ | 5/25 [00:04<00:17, 1.12it/s] 24%|██▍ | 6/25 [00:04<00:17, 1.10it/s] 28%|██▊ | 7/25 [00:05<00:16, 1.08it/s] 32%|███▏ | 8/25 [00:06<00:15, 1.07it/s] 36%|███▌ | 9/25 [00:07<00:15, 1.06it/s] 40%|████ | 10/25 [00:08<00:14, 1.05it/s] 44%|████▍ | 11/25 [00:09<00:13, 1.05it/s] 48%|████▊ | 12/25 [00:10<00:12, 1.05it/s] 52%|█████▏ | 13/25 [00:11<00:11, 1.05it/s] 56%|█████▌ | 14/25 [00:12<00:10, 1.05it/s] 60%|██████ | 15/25 [00:13<00:09, 1.05it/s] 64%|██████▍ | 16/25 [00:14<00:08, 1.04it/s] 68%|██████▊ | 17/25 [00:15<00:07, 1.04it/s] 72%|███████▏ | 18/25 [00:16<00:06, 1.04it/s] 76%|███████▌ | 19/25 [00:17<00:05, 1.04it/s] 80%|████████ | 20/25 [00:18<00:04, 1.04it/s] 84%|████████▍ | 21/25 [00:19<00:03, 1.04it/s] 88%|████████▊ | 22/25 [00:20<00:02, 1.04it/s] 92%|█████████▏| 23/25 [00:21<00:01, 1.04it/s] 96%|█████████▌| 24/25 [00:22<00:00, 1.04it/s] 100%|██████████| 25/25 [00:23<00:00, 1.19s/it] 100%|██████████| 25/25 [00:23<00:00, 1.04it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 9, title: Save Image, class type: SaveImage Prompt executed in 24.41 seconds outputs: {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== ComfyUI_00001_.png
Prediction
fofr/aura-flow:ae5ab66aIDtf0mz49w5hrgm0cgms4byp74grStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- cfg
- 3.5
- shift
- 1.73
- steps
- 25
- width
- 1024
- height
- 1024
- prompt
- a stylized cartoon image, yellow background, a smiling turtle holding a pizza, the turtle is wearing a white and brown cap, large eyes and a friendly expression, the turtle is standing on its hind legs, the pizza is held in both of its front legs, small clouds and trees on either side of the turtle, the text "Turtle Pizza" is in large brown letters at the top, the text "No More Hungry" at the bottom in brown, the overall style is retro with halftone shading
- sampler
- uni_pc
- scheduler
- normal
- output_format
- webp
- output_quality
- 80
- negative_prompt
- ugly, broken
- number_of_images
- 1
{ "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "a stylized cartoon image, yellow background, a smiling turtle holding a pizza, the turtle is wearing a white and brown cap, large eyes and a friendly expression, the turtle is standing on its hind legs, the pizza is held in both of its front legs, small clouds and trees on either side of the turtle, the text \"Turtle Pizza\" is in large brown letters at the top, the text \"No More Hungry\" at the bottom in brown, the overall style is retro with halftone shading", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/aura-flow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/aura-flow:ae5ab66a7d1ca7ee44cf8c50265d3bafdef23734d03d66063d1c8fcf82f0c17b", { input: { cfg: 3.5, shift: 1.73, steps: 25, width: 1024, height: 1024, prompt: "a stylized cartoon image, yellow background, a smiling turtle holding a pizza, the turtle is wearing a white and brown cap, large eyes and a friendly expression, the turtle is standing on its hind legs, the pizza is held in both of its front legs, small clouds and trees on either side of the turtle, the text \"Turtle Pizza\" is in large brown letters at the top, the text \"No More Hungry\" at the bottom in brown, the overall style is retro with halftone shading", sampler: "uni_pc", scheduler: "normal", output_format: "webp", output_quality: 80, negative_prompt: "ugly, broken", number_of_images: 1 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/aura-flow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/aura-flow:ae5ab66a7d1ca7ee44cf8c50265d3bafdef23734d03d66063d1c8fcf82f0c17b", input={ "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "a stylized cartoon image, yellow background, a smiling turtle holding a pizza, the turtle is wearing a white and brown cap, large eyes and a friendly expression, the turtle is standing on its hind legs, the pizza is held in both of its front legs, small clouds and trees on either side of the turtle, the text \"Turtle Pizza\" is in large brown letters at the top, the text \"No More Hungry\" at the bottom in brown, the overall style is retro with halftone shading", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/aura-flow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "ae5ab66a7d1ca7ee44cf8c50265d3bafdef23734d03d66063d1c8fcf82f0c17b", "input": { "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "a stylized cartoon image, yellow background, a smiling turtle holding a pizza, the turtle is wearing a white and brown cap, large eyes and a friendly expression, the turtle is standing on its hind legs, the pizza is held in both of its front legs, small clouds and trees on either side of the turtle, the text \\"Turtle Pizza\\" is in large brown letters at the top, the text \\"No More Hungry\\" at the bottom in brown, the overall style is retro with halftone shading", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-07-12T09:31:35.354499Z", "created_at": "2024-07-12T09:31:10.252000Z", "data_removed": false, "error": null, "id": "tf0mz49w5hrgm0cgms4byp74gr", "input": { "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "a stylized cartoon image, yellow background, a smiling turtle holding a pizza, the turtle is wearing a white and brown cap, large eyes and a friendly expression, the turtle is standing on its hind legs, the pizza is held in both of its front legs, small clouds and trees on either side of the turtle, the text \"Turtle Pizza\" is in large brown letters at the top, the text \"No More Hungry\" at the bottom in brown, the overall style is retro with halftone shading", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 }, "logs": "Random seed set to: 4198727867\nRunning workflow\ngot prompt\nExecuting node 3, title: KSampler, class type: KSampler\n 0%| | 0/25 [00:00<?, ?it/s]\n 4%|▍ | 1/25 [00:00<00:04, 5.30it/s]\n 8%|▊ | 2/25 [00:01<00:14, 1.56it/s]\n 12%|█▏ | 3/25 [00:02<00:17, 1.27it/s]\n 16%|█▌ | 4/25 [00:03<00:17, 1.17it/s]\n 20%|██ | 5/25 [00:04<00:17, 1.12it/s]\n 24%|██▍ | 6/25 [00:04<00:17, 1.09it/s]\n 28%|██▊ | 7/25 [00:05<00:16, 1.07it/s]\n 32%|███▏ | 8/25 [00:06<00:15, 1.06it/s]\n 36%|███▌ | 9/25 [00:07<00:15, 1.06it/s]\n 40%|████ | 10/25 [00:08<00:14, 1.05it/s]\n 44%|████▍ | 11/25 [00:09<00:13, 1.05it/s]\n 48%|████▊ | 12/25 [00:10<00:12, 1.05it/s]\n 52%|█████▏ | 13/25 [00:11<00:11, 1.05it/s]\n 56%|█████▌ | 14/25 [00:12<00:10, 1.04it/s]\n 60%|██████ | 15/25 [00:13<00:09, 1.04it/s]\n 64%|██████▍ | 16/25 [00:14<00:08, 1.04it/s]\n 68%|██████▊ | 17/25 [00:15<00:07, 1.04it/s]\n 72%|███████▏ | 18/25 [00:16<00:06, 1.04it/s]\n 76%|███████▌ | 19/25 [00:17<00:05, 1.04it/s]\n 80%|████████ | 20/25 [00:18<00:04, 1.04it/s]\n 84%|████████▍ | 21/25 [00:19<00:03, 1.04it/s]\n 88%|████████▊ | 22/25 [00:20<00:02, 1.04it/s]\n 92%|█████████▏| 23/25 [00:21<00:01, 1.04it/s]\n 96%|█████████▌| 24/25 [00:22<00:00, 1.04it/s]\n100%|██████████| 25/25 [00:24<00:00, 1.19s/it]\n100%|██████████| 25/25 [00:24<00:00, 1.04it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 24.38 seconds\noutputs: {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nComfyUI_00001_.png", "metrics": { "predict_time": 25.089343742, "total_time": 25.102499 }, "output": [ "https://replicate.delivery/pbxt/FB6BVEL8rUaaKpR6oCfd2wepBKgXyb3ay93qo7WuCequPVPmA/ComfyUI_00001_.webp" ], "started_at": "2024-07-12T09:31:10.265155Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tf0mz49w5hrgm0cgms4byp74gr", "cancel": "https://api.replicate.com/v1/predictions/tf0mz49w5hrgm0cgms4byp74gr/cancel" }, "version": "2f38ca7d2e0e84f05bef7980cf8c7c1c36ba2b9416eee3d57e73b67c338eaff0" }
Generated inRandom seed set to: 4198727867 Running workflow got prompt Executing node 3, title: KSampler, class type: KSampler 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:04, 5.30it/s] 8%|▊ | 2/25 [00:01<00:14, 1.56it/s] 12%|█▏ | 3/25 [00:02<00:17, 1.27it/s] 16%|█▌ | 4/25 [00:03<00:17, 1.17it/s] 20%|██ | 5/25 [00:04<00:17, 1.12it/s] 24%|██▍ | 6/25 [00:04<00:17, 1.09it/s] 28%|██▊ | 7/25 [00:05<00:16, 1.07it/s] 32%|███▏ | 8/25 [00:06<00:15, 1.06it/s] 36%|███▌ | 9/25 [00:07<00:15, 1.06it/s] 40%|████ | 10/25 [00:08<00:14, 1.05it/s] 44%|████▍ | 11/25 [00:09<00:13, 1.05it/s] 48%|████▊ | 12/25 [00:10<00:12, 1.05it/s] 52%|█████▏ | 13/25 [00:11<00:11, 1.05it/s] 56%|█████▌ | 14/25 [00:12<00:10, 1.04it/s] 60%|██████ | 15/25 [00:13<00:09, 1.04it/s] 64%|██████▍ | 16/25 [00:14<00:08, 1.04it/s] 68%|██████▊ | 17/25 [00:15<00:07, 1.04it/s] 72%|███████▏ | 18/25 [00:16<00:06, 1.04it/s] 76%|███████▌ | 19/25 [00:17<00:05, 1.04it/s] 80%|████████ | 20/25 [00:18<00:04, 1.04it/s] 84%|████████▍ | 21/25 [00:19<00:03, 1.04it/s] 88%|████████▊ | 22/25 [00:20<00:02, 1.04it/s] 92%|█████████▏| 23/25 [00:21<00:01, 1.04it/s] 96%|█████████▌| 24/25 [00:22<00:00, 1.04it/s] 100%|██████████| 25/25 [00:24<00:00, 1.19s/it] 100%|██████████| 25/25 [00:24<00:00, 1.04it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 9, title: Save Image, class type: SaveImage Prompt executed in 24.38 seconds outputs: {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== ComfyUI_00001_.png
Prediction
fofr/aura-flow:ae5ab66aIDy3dqh83hr5rgp0cgms5r1mgxd4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- cfg
- 3.5
- shift
- 1.73
- steps
- 25
- width
- 1024
- height
- 1024
- prompt
- A stylized cartoon image, pastel pink background, a grinning penguin holding an ice cream cone, the penguin is wearing a colorful striped scarf, large eyes and an excited expression, the penguin is waddling on its feet, the ice cream cone is held in one flipper, small icebergs and snowflakes on either side of the penguin, the text "Penguin Scoops" is in large blue letters at the top, the text "Chill Out & Enjoy" at the bottom in blue, the overall style is retro with halftone shading
- sampler
- uni_pc
- scheduler
- normal
- output_format
- webp
- output_quality
- 80
- negative_prompt
- ugly, broken
- number_of_images
- 1
{ "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "A stylized cartoon image, pastel pink background, a grinning penguin holding an ice cream cone, the penguin is wearing a colorful striped scarf, large eyes and an excited expression, the penguin is waddling on its feet, the ice cream cone is held in one flipper, small icebergs and snowflakes on either side of the penguin, the text \"Penguin Scoops\" is in large blue letters at the top, the text \"Chill Out & Enjoy\" at the bottom in blue, the overall style is retro with halftone shading", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/aura-flow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/aura-flow:ae5ab66a7d1ca7ee44cf8c50265d3bafdef23734d03d66063d1c8fcf82f0c17b", { input: { cfg: 3.5, shift: 1.73, steps: 25, width: 1024, height: 1024, prompt: "A stylized cartoon image, pastel pink background, a grinning penguin holding an ice cream cone, the penguin is wearing a colorful striped scarf, large eyes and an excited expression, the penguin is waddling on its feet, the ice cream cone is held in one flipper, small icebergs and snowflakes on either side of the penguin, the text \"Penguin Scoops\" is in large blue letters at the top, the text \"Chill Out & Enjoy\" at the bottom in blue, the overall style is retro with halftone shading", sampler: "uni_pc", scheduler: "normal", output_format: "webp", output_quality: 80, negative_prompt: "ugly, broken", number_of_images: 1 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/aura-flow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/aura-flow:ae5ab66a7d1ca7ee44cf8c50265d3bafdef23734d03d66063d1c8fcf82f0c17b", input={ "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "A stylized cartoon image, pastel pink background, a grinning penguin holding an ice cream cone, the penguin is wearing a colorful striped scarf, large eyes and an excited expression, the penguin is waddling on its feet, the ice cream cone is held in one flipper, small icebergs and snowflakes on either side of the penguin, the text \"Penguin Scoops\" is in large blue letters at the top, the text \"Chill Out & Enjoy\" at the bottom in blue, the overall style is retro with halftone shading", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/aura-flow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "ae5ab66a7d1ca7ee44cf8c50265d3bafdef23734d03d66063d1c8fcf82f0c17b", "input": { "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "A stylized cartoon image, pastel pink background, a grinning penguin holding an ice cream cone, the penguin is wearing a colorful striped scarf, large eyes and an excited expression, the penguin is waddling on its feet, the ice cream cone is held in one flipper, small icebergs and snowflakes on either side of the penguin, the text \\"Penguin Scoops\\" is in large blue letters at the top, the text \\"Chill Out & Enjoy\\" at the bottom in blue, the overall style is retro with halftone shading", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-07-12T09:35:05.608938Z", "created_at": "2024-07-12T09:34:40.577000Z", "data_removed": false, "error": null, "id": "y3dqh83hr5rgp0cgms5r1mgxd4", "input": { "cfg": 3.5, "shift": 1.73, "steps": 25, "width": 1024, "height": 1024, "prompt": "A stylized cartoon image, pastel pink background, a grinning penguin holding an ice cream cone, the penguin is wearing a colorful striped scarf, large eyes and an excited expression, the penguin is waddling on its feet, the ice cream cone is held in one flipper, small icebergs and snowflakes on either side of the penguin, the text \"Penguin Scoops\" is in large blue letters at the top, the text \"Chill Out & Enjoy\" at the bottom in blue, the overall style is retro with halftone shading", "sampler": "uni_pc", "scheduler": "normal", "output_format": "webp", "output_quality": 80, "negative_prompt": "ugly, broken", "number_of_images": 1 }, "logs": "Random seed set to: 3631042339\nRunning workflow\ngot prompt\nExecuting node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 3, title: KSampler, class type: KSampler\n 0%| | 0/25 [00:00<?, ?it/s]\n 4%|▍ | 1/25 [00:00<00:04, 5.31it/s]\n 8%|▊ | 2/25 [00:01<00:14, 1.57it/s]\n 12%|█▏ | 3/25 [00:02<00:17, 1.28it/s]\n 16%|█▌ | 4/25 [00:03<00:17, 1.18it/s]\n 20%|██ | 5/25 [00:03<00:17, 1.13it/s]\n 24%|██▍ | 6/25 [00:04<00:17, 1.10it/s]\n 28%|██▊ | 7/25 [00:05<00:16, 1.08it/s]\n 32%|███▏ | 8/25 [00:06<00:15, 1.07it/s]\n 36%|███▌ | 9/25 [00:07<00:15, 1.06it/s]\n 40%|████ | 10/25 [00:08<00:14, 1.06it/s]\n 44%|████▍ | 11/25 [00:09<00:13, 1.05it/s]\n 48%|████▊ | 12/25 [00:10<00:12, 1.05it/s]\n 52%|█████▏ | 13/25 [00:11<00:11, 1.05it/s]\n 56%|█████▌ | 14/25 [00:12<00:10, 1.05it/s]\n 60%|██████ | 15/25 [00:13<00:09, 1.05it/s]\n 64%|██████▍ | 16/25 [00:14<00:08, 1.04it/s]\n 68%|██████▊ | 17/25 [00:15<00:07, 1.04it/s]\n 72%|███████▏ | 18/25 [00:16<00:06, 1.04it/s]\n 76%|███████▌ | 19/25 [00:17<00:05, 1.04it/s]\n 80%|████████ | 20/25 [00:18<00:04, 1.04it/s]\n 84%|████████▍ | 21/25 [00:19<00:03, 1.04it/s]\n 88%|████████▊ | 22/25 [00:20<00:02, 1.04it/s]\n 92%|█████████▏| 23/25 [00:21<00:01, 1.04it/s]\n 96%|█████████▌| 24/25 [00:22<00:00, 1.04it/s]\n100%|██████████| 25/25 [00:23<00:00, 1.19s/it]\n100%|██████████| 25/25 [00:23<00:00, 1.04it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 24.35 seconds\noutputs: {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nComfyUI_00001_.png", "metrics": { "predict_time": 25.021758069, "total_time": 25.031938 }, "output": [ "https://replicate.delivery/pbxt/cuH3CEl05tpxPtld1kgv9awcLD6TZ3pIbcNkwpaete4JrqHTA/ComfyUI_00001_.webp" ], "started_at": "2024-07-12T09:34:40.587180Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/y3dqh83hr5rgp0cgms5r1mgxd4", "cancel": "https://api.replicate.com/v1/predictions/y3dqh83hr5rgp0cgms5r1mgxd4/cancel" }, "version": "2f38ca7d2e0e84f05bef7980cf8c7c1c36ba2b9416eee3d57e73b67c338eaff0" }
Generated inRandom seed set to: 3631042339 Running workflow got prompt Executing node 6, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode Executing node 3, title: KSampler, class type: KSampler 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:04, 5.31it/s] 8%|▊ | 2/25 [00:01<00:14, 1.57it/s] 12%|█▏ | 3/25 [00:02<00:17, 1.28it/s] 16%|█▌ | 4/25 [00:03<00:17, 1.18it/s] 20%|██ | 5/25 [00:03<00:17, 1.13it/s] 24%|██▍ | 6/25 [00:04<00:17, 1.10it/s] 28%|██▊ | 7/25 [00:05<00:16, 1.08it/s] 32%|███▏ | 8/25 [00:06<00:15, 1.07it/s] 36%|███▌ | 9/25 [00:07<00:15, 1.06it/s] 40%|████ | 10/25 [00:08<00:14, 1.06it/s] 44%|████▍ | 11/25 [00:09<00:13, 1.05it/s] 48%|████▊ | 12/25 [00:10<00:12, 1.05it/s] 52%|█████▏ | 13/25 [00:11<00:11, 1.05it/s] 56%|█████▌ | 14/25 [00:12<00:10, 1.05it/s] 60%|██████ | 15/25 [00:13<00:09, 1.05it/s] 64%|██████▍ | 16/25 [00:14<00:08, 1.04it/s] 68%|██████▊ | 17/25 [00:15<00:07, 1.04it/s] 72%|███████▏ | 18/25 [00:16<00:06, 1.04it/s] 76%|███████▌ | 19/25 [00:17<00:05, 1.04it/s] 80%|████████ | 20/25 [00:18<00:04, 1.04it/s] 84%|████████▍ | 21/25 [00:19<00:03, 1.04it/s] 88%|████████▊ | 22/25 [00:20<00:02, 1.04it/s] 92%|█████████▏| 23/25 [00:21<00:01, 1.04it/s] 96%|█████████▌| 24/25 [00:22<00:00, 1.04it/s] 100%|██████████| 25/25 [00:23<00:00, 1.19s/it] 100%|██████████| 25/25 [00:23<00:00, 1.04it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 9, title: Save Image, class type: SaveImage Prompt executed in 24.35 seconds outputs: {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== ComfyUI_00001_.png
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