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Deploy To Temps

Organization
gotempsh
deploy-to-temps

Deploy applications to the Temps platform with automatic framework detection, Dockerfile generation, and container orchestration. Supports Next.js, Vite, React, Node.js, Python, Go, Rust, Java, and C# applications. Use when the user wants to: (1) Deploy their app to Temps, (2) Set up CI/CD with Temps, (3) Configure deployment settings, (4) Create a Dockerfile for Temps, (5) Deploy a containerized application, (6) Set up automatic deployments from Git. Triggers: "deploy to temps", "temps deployment", "push to temps", "containerize for temps", "temps ci/cd".

Overview

Publishergotempsh
Repositorytemps
Skill namedeploy-to-temps
Stars
836
Forks
68
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by gotempsh on GitHub. Read the source before you install it.

Installation

Install the Deploy To Temps AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/gotempsh/temps/tree/main/skills/deploy-to-temps
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/gotempsh/temps.git /tmp/temps
mkdir -p .claude/skills
cp -r /tmp/temps/skills/deploy-to-temps .claude/skills/deploy-to-temps
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deploy To Temps in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Deploy To Temps on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Deploy To Temps is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Deploy to Temps

Deploy applications to Temps with automatic framework detection and optimized builds.

Supported Frameworks

FrameworkDetectionBuild Command
Next.jsnext.config.*next build
Vitevite.config.*vite build
Create React Appreact-scripts in package.jsonreact-scripts build
Remixremix.config.*remix build
Express/Node.jsexpress in dependenciesnpm run build (if exists)
NestJS@nestjs/core in dependenciesnest build
Python/Flaskrequirements.txt + app.py-
Python/Djangomanage.pypython manage.py collectstatic
Gogo.modgo build
RustCargo.tomlcargo build --release

Quick Deploy

Via Git Integration

  1. Connect your Git provider in Temps dashboard
  2. Select repository and branch
  3. Temps auto-detects framework and deploys

Via CLI

bash
# Install Temps CLI
npm install -g @temps-sdk/cli

# Login
temps login

# Deploy current directory
temps deploy

# Deploy with specific settings
temps deploy --project my-app --branch main

Dockerfile Generation

Temps auto-generates optimized Dockerfiles. For custom needs:

Next.js (Standalone)

dockerfile
FROM node:20-alpine AS base

FROM base AS deps
WORKDIR /app
COPY package*.json ./
RUN npm ci

FROM base AS builder
WORKDIR /app
COPY --from=deps /app/node_modules ./node_modules
COPY . .
RUN npm run build

FROM base AS runner
WORKDIR /app
ENV NODE_ENV=production
RUN addgroup --system --gid 1001 nodejs
RUN adduser --system --uid 1001 nextjs

COPY --from=builder /app/public ./public
COPY --from=builder --chown=nextjs:nodejs /app/.next/standalone ./
COPY --from=builder --chown=nextjs:nodejs /app/.next/static ./.next/static

USER nextjs
EXPOSE 3000
ENV PORT=3000
CMD ["node", "server.js"]

Node.js (Express/Fastify)

dockerfile
FROM node:20-alpine
WORKDIR /app

COPY package*.json ./
RUN npm ci --only=production

COPY . .

ENV NODE_ENV=production
USER node
EXPOSE 3000
CMD ["node", "dist/index.js"]

Python (Flask/FastAPI)

dockerfile
FROM python:3.11-slim
WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY . .

ENV PYTHONUNBUFFERED=1
EXPOSE 8000
CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:8000", "app:app"]

Go

dockerfile
FROM golang:1.21-alpine AS builder
WORKDIR /app

COPY go.mod go.sum ./
RUN go mod download

COPY . .
RUN CGO_ENABLED=0 GOOS=linux go build -o main .

FROM alpine:latest
RUN apk --no-cache add ca-certificates
WORKDIR /root/

COPY --from=builder /app/main .
EXPOSE 8080
CMD ["./main"]

Environment Variables

Configure in Temps dashboard or via CLI:

bash
# Set environment variable
temps env set DATABASE_URL="postgres://..."

# Set from .env file
temps env import .env

# List variables
temps env list

Build Configuration

Create temps.json in project root:

json
{
  "name": "my-app",
  "framework": "nextjs",
  "buildCommand": "npm run build",
  "installCommand": "npm ci",
  "outputDirectory": ".next",
  "nodeVersion": "20",
  "env": {
    "NODE_ENV": "production"
  }
}

Git-based Deployments

Auto-deploy on Push

  1. In Temps dashboard, enable "Auto-deploy"
  2. Select branches to auto-deploy
  3. Each push triggers a new deployment

Preview Deployments

Enable "Preview deployments" to create unique URLs for each PR.

Deploy Hooks

Create webhooks for custom CI/CD:

bash
curl -X POST https://your-temps.com/api/projects/123/deploy \
  -H "Authorization: Bearer $TEMPS_DEPLOY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"branch": "main", "commit": "abc123"}'

Rollbacks

bash
# List deployments
temps deployments list

# Rollback to specific deployment
temps rollback --deployment-id 456

# Rollback to previous
temps rollback --previous

Health Checks

Configure health checks in temps.json:

json
{
  "healthCheck": {
    "path": "/api/health",
    "interval": 30,
    "timeout": 10,
    "unhealthyThreshold": 3
  }
}

Resource Configuration

json
{
  "resources": {
    "cpu": "0.5",
    "memory": "512Mi",
    "replicas": {
      "min": 1,
      "max": 5
    }
  }
}

Troubleshooting

Build fails?

  • Check build logs in dashboard
  • Verify buildCommand is correct
  • Ensure all dependencies are in package.json

Container won't start?

  • Check PORT environment variable is used
  • Verify health check endpoint works
  • Review container logs

Deployment stuck?

  • Check resource limits aren't exceeded
  • Verify Docker image builds locally
  • Review deployment logs

Frequently asked questions

What does the Deploy To Temps AI skill do?

Deploy applications to the Temps platform with automatic framework detection, Dockerfile generation, and container orchestration. Supports Next.js, Vite, React, Node.js, Python, Go, Rust, Java, and C# applications. Use when the user wants to: (1) Deploy their app to Temps, (2) Set up CI/CD with Temps, (3) Configure deployment settings, (4) Create a Dockerfile for Temps, (5) Deploy a containerized application, (6) Set up automatic deployments from Git. Triggers: "deploy to temps", "temps deployment", "push to temps", "containerize for temps", "temps ci/cd".

Why use Deploy To Temps on TypingMind?

Because you install it once and use it with any model. Deploy To Temps is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Deploy To Temps in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gotempsh/temps/tree/main/skills/deploy-to-temps. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Deploy To Temps?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Deploy To Temps?

As many as you like. As long as a model supports skills, you can use Deploy To Temps with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Deploy To Temps AI skill free?

Yes. It is published on GitHub by gotempsh under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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