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What is datamatic?

craftingcodegig/datamatic — explained in plain English

Analysis updated 2026-05-18

12GoAudience · developerComplexity · 3/5Setup · moderate

In one sentence

A command line tool for building multi-step AI pipelines that generate, transform, and chain structured data between model calls.

Mindmap

mindmap
  root((datamatic))
    What it does
      Multi step AI pipelines
      Schema guided reasoning
      Chains model outputs
    Tech stack
      Go CLI
      Ollama and cloud providers
      Embedded jq
    Use cases
      Generate synthetic data
      Chain structured reasoning
      Batch document analysis
    Audience
      Developers
      Data engineers

Code map

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What do people build with it?

USE CASE 1

Generate synthetic training data for fine-tuning other AI models.

USE CASE 2

Chain multiple AI model calls together, feeding each step's structured output into the next.

USE CASE 3

Classify or analyze a batch of documents using schema-guided reasoning steps.

What is it built with?

GoOllamaOpenAI APIjq

How does it compare?

craftingcodegig/datamaticaaronrzh/llm-gatewayizzzzzi/agent-assh
Stars121212
LanguageGoGoGo
Setup difficultymoderatemoderateeasy
Complexity3/54/53/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Local models need Ollama or LM Studio running, cloud providers need an API key set as an environment variable.

So what is it?

datamatic is a command line tool for building multi step pipelines that call AI language models and pass structured data between the steps. Instead of writing custom code to call a model, check its output, and feed that output into another call, you describe the whole pipeline in a single configuration file, and datamatic runs it for you. Each step in a pipeline can call a different AI model, and datamatic works with several providers, including locally run models through Ollama or LM Studio, as well as cloud services like OpenAI, OpenRouter, and Google's Gemini. A step can ask a model to generate a fixed number of items, or it can repeat once for every item produced by an earlier step, referencing that item's fields directly inside its prompt. Steps can require the model to return data matching a defined structure, called a JSON schema, so the output is predictable and can be checked automatically rather than being free form text. Beyond calling models, datamatic can also run any command line tool as a step, load existing datasets from Hugging Face, and reshape or filter data between steps using an embedded version of the jq data processing language, so no separate jq installation is needed. Pipelines can also read values from environment variables, letting the same configuration file be reused with different models or settings. Typical uses described in the README include generating synthetic training data for fine-tuning other models, classifying documents through a structured multi step reasoning process, generating and reasoning about complex database queries, and combining image analysis with text generation. Output is written as structured JSON lines, with each line recording the prompt used, the model's response, and any values carried over from earlier steps for traceability. Installation is available through Homebrew, the Go install command, or by cloning the repository and building it from source. It requires Go to build from source, and an API key only if you choose a cloud based model provider.

Copy-paste prompts

Prompt 1
Help me write a datamatic config.yaml that generates titles and then analyzes their sentiment.
Prompt 2
Explain how forEach and count work differently in a datamatic pipeline step.
Prompt 3
Show me how to use a jq transform step in datamatic to filter and reshape data.
Prompt 4
Walk me through switching a datamatic pipeline from Ollama to OpenAI.

Frequently asked questions

What is datamatic?

A command line tool for building multi-step AI pipelines that generate, transform, and chain structured data between model calls.

What language is datamatic written in?

Mainly Go. The stack also includes Go, Ollama, OpenAI API.

How hard is datamatic to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is datamatic for?

Mainly developer.

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