Publish Models

ReplicateOfficialPublished by Replicate

Skill
Tool integration
Cloud and DevOps
Apache-2.0
Low risk

From the author

Push and publish custom AI models to Replicate, and set up CI/CD for releasing new model versions safely. Use when running cog push, deploying a model to Replicate, releasing a new version, validating a model with cog-safe-push before publishing, configuring a Replicate deployment, setting up GitHub Actions for model releases, or porting a community model to an official one. Trigger on phrases like "push a model to Replicate", "publish a model", "deploy a model", "release a new version", "cog push", "cog-safe-push", "model CI", "r8.im", or "schema compatibility", and when referencing github.com/replicate/cog-safe-push or github.com/replicate/model-ci-template. Covers cog push, the full cog-safe-push config (test cases, fuzz, deployment, official_model), GitHub Actions patterns, multi-model matrix pushes, and post-publish monitoring. Assumes you already have a working Cog project; see build-models if you need to package one first.

— the description by Replicate

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a comprehensive framework for managing the lifecycle of AI models on Replicate. It covers the transition from local development to production deployment, emphasizing the use of cog-safe-push to validate schema compatibility, run prediction comparisons, and perform input fuzzing. It also details how to integrate these processes into GitHub Actions for automated, reliable model releases, including support for multi-model matrix builds and canary monitoring.

What it does

Publishes custom AI models to the Replicate registry.
Validates model schema compatibility to prevent breaking changes.
Automates testing through prediction comparisons and input fuzzing.
Configures CI/CD pipelines using GitHub Actions for automated releases.
Manages multi-model deployments and proxy/official model updates.
Sets up automated canary checks for production-critical models.

When to use it

When you have a working Cog project ready for deployment.
When you need to release new versions of a model without breaking existing user integrations.
When setting up a professional CI/CD pipeline for AI model releases.
When managing multiple model variants within a single repository.
When you need to ensure consistent performance across different hardware targets.

Advantages

Reduces the risk of breaking changes with automated schema and prediction checks.
Streamlines deployment through standardized CI/CD templates.
Supports complex workflows like multi-model matrix pushes.
Provides robust testing tools including AI-judged output similarity.
Enables automated monitoring of production model health.

Usage examples

“How do I push my model to Replicate safely?”: The agent will guide you through installing cog-safe-push, configuring your cog-safe-push.yaml file, and running the push command to validate and deploy your model.
“Set up a GitHub Action to deploy my model on merge.”: The agent will provide a YAML configuration for a GitHub Actions workflow that uses the Replicate CI template to automate testing and deployment.
“How can I test my stochastic model before publishing?”: The agent will explain how to configure test cases in cog-safe-push.yaml with compare_outputs set to false and how to use match_prompt for VLM-based output validation.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/replicate/publish-models/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip publish-models.zip -d .agents/skills

Documentation by Replicate

Docs

Cog reference: https://cog.run/llms.txt
cog push reference: https://cog.run/cli#cog-push
cog-safe-push: https://github.com/replicate/cog-safe-push
Model CI template: https://github.com/replicate/model-ci-template
Continuous deployment guide: https://replicate.com/docs/guides/continuous-model-deployment

When to use this skill

You have a working Cog project (see build-models if you don't yet).
You want to publish a private or public model on Replicate.
You're releasing a new version of an existing model and want to avoid breaking changes.
You're setting up CI/CD for model releases.

Prerequisites

Cog installed and cog login against r8.im (or echo $TOKEN | cog login --token-stdin).
A model created at replicate.com/{owner}/{name} via the API, web UI, or r8-model CLI.
REPLICATE_API_TOKEN set in your environment.

Plain `cog push`

The simplest path. Build and upload a new version:

cog push r8.im/owner/my-model

Or set image: r8.im/owner/my-model in cog.yaml and run a bare:

cog push

Useful flags:

--separate-weights — store weights in a separate layer; faster cold boots and pushes for models with > 1GB of weights.
--x-fast — faster pushes during iteration (skips some validation).
--secret id=hf,src=$HOME/.hf_token — pass build-time secrets without baking them into image history.

cog-safe-push (recommended for any model with users)

cog-safe-push pushes to a private -test model first, checks schema compatibility against the live version, runs prediction comparisons, and fuzzes inputs. Catches breaking changes before they reach users.

Install:

pip install git+https://github.com/replicate/cog-safe-push.git

Required env vars:

REPLICATE_API_TOKEN
ANTHROPIC_API_KEY (Claude judges output similarity for stochastic models)

Basic usage:

cog-safe-push --test-hardware=gpu-l40s owner/my-model

This will:

Lint predict.py with ruff.
Create a private test model owner/my-model-test if missing.
Push the local Cog model to the test model.
Lint the schema (descriptions, defaults, etc.).
Check schema compatibility against the live owner/my-model version.
Run prediction comparisons between live and test versions.
Fuzz the test model with AI-generated inputs.
If everything passes, push to owner/my-model.

cog-safe-push.yaml schema

Drop a cog-safe-push.yaml in your project root (or cog-safe-push-configs/<variant>.yaml for multi-model repos). All five test-case checker types in one example:

model: owner/my-model
test_model: owner/my-model-test
test_hardware: gpu-l40s

predict:
  compare_outputs: false              # set false for stochastic models
  predict_timeout: 600
  test_cases:
    - inputs:
        prompt: "a serene mountain landscape"
      match_prompt: "a landscape photo of mountains"   # AI-judged via Claude
    - inputs:
        prompt: "a cat"
      match_url: "https://example.com/reference-cat.png"   # binary/image match
    - inputs:
        prompt: ""
      error_contains: "prompt cannot be empty"           # negative test
    - inputs:
        mode: "json"
      jq_query: '.confidence > 0.8 and .status == "success"'   # JSON output
    - inputs:
        prompt: "echo this"
      exact_string: "echo this"                          # exact string match
  fuzz:
    fixed_inputs:
      seed: 42
    disabled_inputs:
      - debug
    iterations: 10
    prompt: "Generate creative and diverse prompts"

train:                                  # if your model has a trainer
  destination: owner/my-model-trained
  destination_hardware: gpu-l40s
  train_timeout: 1800
  test_cases:
    - inputs:
        input_images: "https://.../training.zip"
        steps: 10

deployment:                             # auto-create or update on push
  name: my-model
  owner: owner
  hardware: gpu-l40s

parallel: 4
fast_push: false
ignore_schema_compatibility: false
official_model: owner/my-model         # for proxy/wrapper models, see below

Test case checkers are mutually exclusive: pick exactly one of match_prompt, match_url, error_contains, jq_query, or exact_string per case. Use compare_outputs: false for any stochastic model (diffusion, LLMs); the default true is brittle.

CI/CD: GitHub Actions

Two paths, depending on how much glue you want.

Path A: roll your own

# .github/workflows/push.yaml
name: Push to Replicate
on:
  workflow_dispatch:
    inputs:
      no_push:
        type: boolean
        default: false

jobs:
  push:
    runs-on: ubuntu-latest-4-cores       # builds need disk + cores
    steps:
      - uses: actions/checkout@v4
      - uses: jlumbroso/[email protected]
        with:
          tool-cache: false
          docker-images: false
      - uses: replicate/setup-cog@v2
        with:
          token: ${{ secrets.REPLICATE_API_TOKEN }}
      - run: pip install git+https://github.com/replicate/cog-safe-push.git
      - env:
          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
          REPLICATE_API_TOKEN: ${{ secrets.REPLICATE_API_TOKEN }}
        run: |
          cog-safe-push -vv ${{ inputs.no_push && '--no-push' || '' }}

Add a concurrency: block so PR builds cancel each other while main-branch pushes queue:

concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}

Path B: reusable workflow from model-ci-template

For Replicate-style multi-model repos, drop in:

# .github/workflows/ci.yaml
name: CI
on:
  pull_request: { branches: [main] }
  push: { branches: [main] }
  workflow_dispatch:
    inputs:
      models: { type: string, default: "all" }
      ignore_schema_checks: { type: boolean, default: false }
      cog_version: { type: string, default: "latest" }
      test_only: { type: boolean, default: false }

jobs:
  ci:
    uses: replicate/model-ci-template/.github/workflows/template.yaml@main
    with:
      trigger_type: ${{ github.event_name }}
      models: ${{ inputs.models || 'all' }}
      ignore_schema_checks: ${{ inputs.ignore_schema_checks || false }}
      cog_version: ${{ inputs.cog_version || 'latest' }}
      test_only: ${{ inputs.test_only || false }}
    secrets: inherit

The reusable workflow expects:

cog-safe-push-configs/<model>.yaml — one per model variant.
script/select-model — bash file with if/elif [[ "$MODEL" == "..." ]] blocks listing valid model names.
Secrets: COG_TOKEN, REPLICATE_API_TOKEN, ANTHROPIC_API_KEY.

Multi-model matrix pushes

Pattern from replicate/cog-flux: one repo, N variants, push them in parallel.

jobs:
  prepare:
    runs-on: ubuntu-latest
    outputs:
      matrix: ${{ steps.set.outputs.matrix }}
    steps:
      - id: set
        run: |
          if [ "${{ inputs.models }}" = "all" ]; then
            echo 'matrix={"model":["schnell","dev","krea-dev"]}' >> "$GITHUB_OUTPUT"
          else
            list=$(echo "${{ inputs.models }}" | jq -Rc 'split(",")')
            echo "matrix={\"model\":$list}" >> "$GITHUB_OUTPUT"
          fi

  push:
    needs: prepare
    runs-on: ubuntu-latest-4-cores
    strategy:
      fail-fast: false
      matrix: ${{ fromJson(needs.prepare.outputs.matrix) }}
    steps:
      - uses: actions/checkout@v4
      - run: ./script/select.sh ${{ matrix.model }}     # produces cog.yaml from a template
      - run: cog-safe-push --config cog-safe-push-configs/${{ matrix.model }}.yaml -vv

Two-pass push for proxy / official models

When you maintain a proxy that wraps a third-party API, you push to a private wrapper first, then update the public-facing official model card. Pattern from replicate/cog-official-template:

./script/write-api-key                                              # bake API key into config
cog-safe-push --config cog-safe-push-configs/${MODEL}.yaml -vv

./script/delete-api-key                                             # strip the key
cog-safe-push --push-official-model --config cog-safe-push-configs/${MODEL}.yaml -vv

Set official_model: owner/name in the config so --push-official-model knows where to publish.

Deployments

Add a deployment block to cog-safe-push.yaml to create or update a Replicate deployment automatically on each push:

deployment:
  name: my-model
  owner: owner
  hardware: gpu-l40s

Scaling defaults: CPU deployments scale 1-20 instances, GPU deployments scale 0-2. Adjust manually via the API or web UI when needed.

Monitoring published models

Run an hourly canary that exercises the registry path. Pattern from replicate/cog-pagerduty-check:

name: Hourly cog push check
on:
  schedule:
    - cron: "0 * * * *"
  workflow_dispatch:

jobs:
  check:
    runs-on: ubuntu-latest
    steps:
      - run: |
          # generate a tiny model with a unique uuid, push it, run a prediction
          # by digest, fail loudly if anything breaks.
          ./script/canary.sh

Worth doing for any production-critical model, especially when revenue depends on the registry being up.

Guidelines

Don't break schema compatibility unless you mean to. cog-safe-push catches it; --ignore-schema-compatibility is the opt-out.
Pin test_hardware so test pushes are reproducible.
Use --no-push for dry runs in PR CI; full push on merge to main or on version tags.
Push from CI rather than laptops once you have users.
Use compare_outputs: false for stochastic models. Use match_prompt: for image/video outputs (VLM judgment), match_url: for binary outputs you control, jq_query: for JSON, error_contains: for negative tests.
Never commit REPLICATE_API_TOKEN or ANTHROPIC_API_KEY. Use repo secrets.
For models with weights > 1GB, push with --separate-weights.

Production references

https://github.com/replicate/cog-safe-push — the tool itself, plus its config schema.
https://github.com/replicate/model-ci-template — reusable GitHub Actions workflow.
https://github.com/replicate/cog-official-template — proxy/official model template.
https://github.com/replicate/cog-flux/blob/main/.github/workflows/push.yaml — matrix push across FLUX variants.
https://github.com/replicate/cog-comfyui/blob/main/.github/workflows/ci.yaml — ComfyUI model CI with custom-node install step.
https://github.com/replicate/cog-pagerduty-check — hourly canary pattern.

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Python, Needs Node.js

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Attribution and licence

Published by

Replicate

Publisher

Replicate (Official)

Source

replicate/skills · skills/publish-models · commit 2f36e41

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LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

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2026-11-08

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