v0.1.7

Lacquer v0.1.7

• feat: add file function - useful to load prompts from external files.

v0.1.6

Lacquer v0.1.6

• feat: add support for anthropic model aliases
• fix: add script contents in body for bash block failure
• fix: missing license
• enhance: add helpful OPENAI_API_KEY env naming when key is not set

v0.1.5

Lacquer v0.1.5

• fix: truncate lines in terminal spinner
• fix: resolve q quiting early for init wizard

v0.1.4

Lacquer v0.1.4

Fixes bug with unarchived assets in update logic

v0.1.3

Lacquer v0.1.3

Fixes bug with go releaser not setting proper verison on release

v0.1.2

Lacquer v0.1.2

Fixes bug with update checking logic

v0.1.1

Lacquer v0.1.1

Small improvements to add gpt-5 support and max token warnings in the console spinners.

v0.1.0

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I'm pleased to announce the first release of Lacquer - a blazing-fast, code-first orchestration engine for AI agent workflows. Lacquer brings GitHub Actions-style workflows to AI, enabling developers to build sophisticated multi-agent systems using simple YAML configuration.

Where AI workflows get their shine ✨

🛠️ CLI Commands

laq init

Interactive wizard to create new workflows using AI assistance

laq init

laq run

Execute workflows with flexible input options

laq run workflow.laq.yml --input "name=John"
laq run workflow.laq.yml --input-file inputs.json
laq run workflow.laq.yml --output json

laq validate

Validate workflow syntax and dependencies

laq validate workflow.laq.yml

laq serve

Start HTTP server for workflow execution

laq serve workflow.laq.yml
laq serve --workflow-dir ./workflows --port 8080

📦 Installation

Quick Install:

curl -sSL https://lacquer.ai/install.sh | sh

Platform Support:

• Linux (amd64, arm64, 386)
• macOS (amd64, arm64)
• Windows (amd64, 386)

📋 REST API Endpoints

• GET /api/v1/workflows - List available workflows
• POST /api/v1/workflows/{id}/execute - Execute workflow
• GET /api/v1/executions/{runId} - Get execution status
• WebSocket /api/v1/workflows/{id}/stream - Real-time progress
• GET /health - Health check
• GET /metrics - Prometheus metrics

🧪 Example Workflow

version: "1.0"

agents:
  assistant:
    provider: openai
    model: gpt-4
    temperature: 0.7

inputs:
  topic:
    type: string
    description: Topic to explore
  
workflow:
  steps:
    - id: research
      agent: assistant
      prompt: "Tell me about ${{ inputs.topic }}"

    - id: summarize
      agent: assistant
      prompt: "Summarize this in 3 bullet points: ${{ steps.research.output }}"
  
  outputs:
    summary: "${{ steps.summarize.output }}"

📞 Get Involved

• Website: lacquer.ai
• Documentation: lacquer.ai/docs
• Issues: GitHub Issues
• Discussions: GitHub Discussions

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Happy Orchestrating! 🎼