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Workflow Ep29 Image Upscaler | Skills Pool

Skill File

Workflow Ep29 Image Upscaler

Workflow wrapper imported from `Ep29 Image Upscaler.json`.

steliosot0 starsMar 29, 2026

Occupation: Software Developers
Categories: Containers

Skill Content

workflow_ep29_image_upscaler

Imported workflow skill generated from Ep29 Image Upscaler.json.

Family

upscaling

Inputs

Optional runtime overrides supported by run(...):
- prompt
- negative_prompt
- width, height
- seed, steps, cfg
- sampler_name, scheduler, denoise
- server, headers, api_prefix

Outputs

Returns JSON with:
- status

Related Skills

Quick Install

Workflow Ep29 Image Upscaler

npx skillvault add steliosot/steliosot-comfy-agent-skills-workflows-upscaling-workflow-ep29-image-upscaler-skill-md

Download Skill Open repository

Author: steliosot
stars: 0
Updated: Mar 29, 2026
Occupation

On this page

01workflowep29imageupscaler

prompt_id

output_images

Model Requirements

clip: t5-v1_1-xxl-encoder-Q8_0.gguf -> models/clip
diffusion_model: flux1-dev-Q8_0.gguf -> models/diffusion_models
vae: ae.safetensors -> models/vae
upscale_model: 4x_NMKD-Siax_200k.pth -> models/upscale_models

Custom Node Requirements

None detected.

Links

None detected.

Routing Metadata

Family: upscaling
Input modalities: image, text_prompt
Output modalities: image/png
Model families: flux
Node count: 24
Complexity score: 3
Resource profile: medium
Estimated runtime: moderate (about 30-120s depending on server)
Max latent resolution hint: NonexNone
Max sampler steps hint: 20

Detected Models

clip: t5-v1_1-xxl-encoder-Q8_0.gguf -> models/clip
diffusion_model: flux1-dev-Q8_0.gguf -> models/diffusion_models
vae: ae.safetensors -> models/vae
upscale_model: 4x_NMKD-Siax_200k.pth -> models/upscale_models

Detected Custom Nodes

None detected.

Runtime Warnings

Large model(s) detected; ensure enough VRAM and disk space.

02

Family

05Model Requirements

06Custom Node Requirements

08Routing Metadata

09Detected Models

10Detected Custom Nodes

Helm Chart Scaffolding

Design, organize, and manage Helm charts for templating and packaging Kubernetes applications with reusable configurations. Use when creating Helm charts, packaging Kubernetes applications, or implementing templated deployments.

Architecture Patterns

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Python observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.

K8s Manifest Generator

Create production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.

Istio Traffic Management

Configure Istio traffic management including routing, load balancing, circuit breakers, and canary deployments. Use when implementing service mesh traffic policies, progressive delivery, or resilience patterns.

Secrets Management

Implement secure secrets management for CI/CD pipelines using Vault, AWS Secrets Manager, or native platform solutions. Use when handling sensitive credentials, rotating secrets, or securing CI/CD environments.

Gitops Workflow

Implement GitOps workflows with ArgoCD and Flux for automated, declarative Kubernetes deployments with continuous reconciliation. Use when implementing GitOps practices, automating Kubernetes deployments, or setting up declarative infrastructure management.

Software Developers