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Run It Yourself

The Pipelex runtime is the Python package that reads a .mthds file and runs it. Install it and everything happens on your own machine, against the model providers you choose. If you would rather not run anything yourself, the Quick Start builds methods with your coding agent and runs them on the hosted API.

Install

uv tool install pipelex
pipelex init
pipelex doctor

pipelex init writes your ~/.pipelex configuration and offers to install the editor extension; pipelex doctor reports what is configured and what is missing.

Some providers and features need an extra:

  • anthropic: Anthropic/Claude support for text generation
  • google: Google models (Vertex) support for text generation
  • google-genai: Google Gemini API support for text and image generation
  • mistralai: Mistral AI support for text generation and OCR
  • bedrock: Amazon Bedrock support for text generation
  • fal: Image generation through fal
  • linkup: Web search with Linkup
  • docling: OCR with Docling

Name the ones you need when you install, or take them all:

uv tool install "pipelex[anthropic,google,google-genai,mistralai,bedrock,fal,linkup,docling]"

Configure AI access

  • Bring Your Own Keys — Use existing API keys from OpenAI, Anthropic, Google, Mistral, etc. See Configure AI Providers.
  • Local AI — Ollama, vLLM, LM Studio, or llama.cpp — no API keys required. See Configure AI Providers.

Run a method

Save this method as summarize.mthds:

domain    = "articles"
main_pipe = "summarize_article"

[pipe.summarize_article]
type        = "PipeLLM"
description = "Summarize an article for a given audience"
inputs      = { article = "Text", audience = "Text" }
output      = "Text"
prompt      = "Summarize $article in three bullet points for $audience."

Save its inputs as inputs.json:

{
  "article": "Paste the text of an article here.",
  "audience": "busy executives"
}

The method names no model, so it runs on the deck's default-general alias, which pipelex init points at an OpenAI model. With a provider other than OpenAI or Azure OpenAI, point that alias at one of your provider's models first, by adding it to ~/.pipelex/inference/deck/x_custom_llm_deck.toml — the models each provider serves are listed under ~/.pipelex/inference/backends/:

[llm.aliases]
default-general = "claude-5-sonnet"     # an Anthropic model, for example

Then run it:

pipelex run bundle summarize.mthds --inputs inputs.json

The result is written under results/. From here, The MTHDS Language Tutorial builds a method step by step, and CV batch screening runs a method with several steps, typed concepts and a batch, from the CLI and from Python.

Editor extension

.mthds syntax highlighting and flowchart visualization: the VS Code Marketplace, or the Open VSX Registry for Cursor, Windsurf and other VS Code forks. pipelex init offers to install it when it detects your IDE.