Skip to main content

Lightweight launcher for local AI agent workflows

Project description

aop_launcher

Agent Orchestration Platform Launcher.

aop_launcher is a tiny terminal runner for local AI agent workflows. It reads a YAML file, runs agents in sequence, optionally runs local shell tools for each agent, sends the prompt to either a local command or an OpenAI-compatible chat completion endpoint, and streams the result to the terminal.

This first 0.0.1.dev0 release is intentionally small. It does not provide remote execution, scheduling, retries, memory stores, or a hosted service.

Install

pip install aop-launcher

OpenAI-compatible workflow

Use this with local or hosted inference servers that expose /v1/chat/completions:

llm:
  provider: openai-compatible
  base_url: "http://localhost:8000/v1"
  api_key_env: "OPENAI_API_KEY"
  model: "local-model"
  temperature: 0.2
  max_tokens: 800

agents:
  - name: assistant
    system: "You are a concise, practical assistant."
    prompt: |
      Answer this request:
      {input}

Run it:

aop-launcher workflow.yml "Draft a release checklist"

Common endpoint settings can be overridden from the terminal:

aop-launcher workflow.yml "hello" \
  --base-url http://localhost:8000/v1 \
  --model local-model \
  --api-key-env OPENAI_API_KEY

If neither api_key nor api_key_env is configured, no Authorization header is sent.

Command workflow

llm:
  command: "ollama run llama3.2"

tools:
  now: "date"

agents:
  - name: planner
    tools: ["now"]
    prompt: |
      Create a short plan for this task:
      {input}

      Tool results:
      {tool_results}

  - name: writer
    prompt: |
      Write the final answer from this plan:
      {input}

Run it:

aop-launcher workflow.yml "Draft a release checklist"

You can also pass the LLM command from the terminal:

aop-launcher workflow.yml "hello" --llm-command "ollama run llama3.2"

Prompt variables

Agent system and prompt templates can use:

  • {input}: previous agent output, or the initial terminal input for the first agent.
  • {initial_input}: original terminal input.
  • {tool_results}: output from shell tools configured on the current agent.
  • {history}: prior agent outputs with agent names.

Examples

Sample workflows live in examples/:

  • openai_basic.yml
  • research_brief.yml
  • code_review.yml
  • shell_tools.yml

Tool safety

Workflow tools are raw local shell commands. Only run workflows you trust.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aop_launcher-0.0.2.dev0.tar.gz (8.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aop_launcher-0.0.2.dev0-py3-none-any.whl (6.8 kB view details)

Uploaded Python 3

File details

Details for the file aop_launcher-0.0.2.dev0.tar.gz.

File metadata

  • Download URL: aop_launcher-0.0.2.dev0.tar.gz
  • Upload date:
  • Size: 8.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.15

File hashes

Hashes for aop_launcher-0.0.2.dev0.tar.gz
Algorithm Hash digest
SHA256 c2a894e30897bc950a03e793dfde6315cb4074f8f51ef2e0ebdc102282e672ac
MD5 b506c58a3c75474d2f2b70cf2688856c
BLAKE2b-256 e51d011933ec285ecbc1ea2a9c468147af8c596aca24e42f4003f280efa9163b

See more details on using hashes here.

File details

Details for the file aop_launcher-0.0.2.dev0-py3-none-any.whl.

File metadata

File hashes

Hashes for aop_launcher-0.0.2.dev0-py3-none-any.whl
Algorithm Hash digest
SHA256 f06cbedb75cbc6db3f61e5b55a0c21d3ffcb1b9fd15a975f9c532435a9deeb25
MD5 36c7472d968ce378efbd37b3d3dc4981
BLAKE2b-256 79d2bb6fc94453ba5977882891d34ece599934477cec55d99b90e152b48b8ac4

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page