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1.9.0 - S3 Storage Backend, Instance Deletion Cost Management (#52)
* update dependencies * set deletion cost to queue length when on salad * start working on s3 features * add support for s3 * add test for b64 jpeg * tests for s3 functionality * update readme * clarify title * more clarity * update for claude 4 * Update copyright year * update imports in example workflows * ignore some directories in tsc * missed a claude 4 * fix test * fix test * build an image with a model to test in the wild * more info in readme * more readme * more readme * don't need imds sdk. * don't need that log * testing deletion cost logic * bump default comfy to 0.3.38
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.github/workflows/build-docker-images.yml

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- name: Build Docker images for 50xx
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working-directory: ./docker
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run: ./build-api-images 0.3.35 2.7.0 12.8
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run: ./build-api-images 0.3.38 2.7.0 12.8
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- name: Build Docker images for pre-50xx
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working-directory: ./docker
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run: ./build-api-images 0.3.35 2.7.0 12.6
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run: ./build-api-images 0.3.38 2.7.0 12.6
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.gitignore

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*.safetensors
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*.ckpt
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*.pth
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test/docker-image/models
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test/docker-image/models
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scratch
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test/output/*.png

LICENSE

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MIT License
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Copyright (c) 2024 Salad Technologies
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Copyright (c) 2025 Salad Technologies
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal

README.md

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claude-endpoint-creation-prompt.md

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# Instructions
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Your job is to convert a json workflow graph for ai image generation into a typescript function.
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- You should define a type for the input, using Zod for validation.
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- You should use `.describe` to describe each parameter to the best of your ability.
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- LoadImage inputs will always be accepted as either a url or base64 encoded string
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- Only output the typescript, with no additional commentary.
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Here is an example output:
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```typescript
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# Example Output
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import { z } from "zod";
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import config from "../config";
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description: "Generate an image from a text prompt",
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};
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export default workflow;
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```
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export default workflow;

docker-compose.yml

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services:
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comfyui:
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image: ghcr.io/saladtechnologies/comfyui-api:comfy0.3.35-test-image
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image: ghcr.io/saladtechnologies/comfyui-api:comfy0.3.38-test-image
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volumes:
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- type: bind
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source: ./bin
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context: ./test/docker-image
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dockerfile: Dockerfile
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args:
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- comfy_version=0.3.35
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- comfy_version=0.3.38
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ports:
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- "3000:3000"
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- "8188:8188"
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environment:
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LOG_LEVEL: "debug"
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AWS_ENDPOINT_URL: "http://localstack:4566"
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AWS_ACCESS_KEY_ID: "test"
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AWS_SECRET_ACCESS_KEY: "test"
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AWS_REGION: "us-east-1"
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# ALWAYS_RESTART_COMFYUI: "true"
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# SYSTEM_WEBHOOK_URL: "http://host.docker.internal:1234/system"
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# SYSTEM_WEBHOOK_EVENTS: all
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- driver: nvidia
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capabilities: [ gpu ]
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count: all
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localstack:
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image: localstack/localstack
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ports:
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- "4566:4566" # LocalStack Gateway
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- "4510-4559:4510-4559" # External services
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environment:
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- SERVICES=s3
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volumes:
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- "/var/run/docker.sock:/var/run/docker.sock"

docker/api.dockerfile

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ARG base=runtime
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ARG comfy_version=0.3.35
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ARG comfy_version=0.3.38
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ARG pytorch_version=2.7.0
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ARG cuda_version=12.6
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docker/build-api-images

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usage="Usage: $0 [comfy_version] [torch_version] [cuda_version] [api_version]"
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comfy_version=${1:-0.3.35}
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comfy_version=${1:-0.3.38}
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torch_version=${2:-2.7.0}
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cuda_version=${3:-12.6}
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docker/build-comfy-base-images

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#! /usr/bin/bash
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comfy_version=${1:-0.3.35}
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comfy_version=${1:-0.3.38}
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torch_version=${2:-2.7.0}
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cuda_version=${3:-12.6}
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bases=("devel" "runtime")

docker/comfyui.dockerfile

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WORKDIR /opt
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ARG comfy_version=0.3.35
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ARG comfy_version=0.3.38
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RUN git clone --depth 1 --branch v${comfy_version} https://github.com/comfyanonymous/ComfyUI.git
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