> For the complete documentation index, see [llms.txt](https://docs.trezalabs.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.trezalabs.com/pipelines/pipelines.md).

# Overview

A **pipeline** is a graph of nodes that turns one prompt into video, images, and text. You build it on a drag-and-drop canvas, wiring models, prompts, and guardrails together with no glue code between the pieces. When it works, you publish it behind one versioned API.

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## How it works

1. **Start with a prompt.** Type what you want to make, a product video, a campaign image, launch copy, or open a template like Product Demo Video and tweak the brief.
2. **Chain the models.** Wire Veo, Gemini Image, Llama, or any open model together on the canvas. One node refines your brief into a shot prompt, the next renders it. Swap models per node, no rewrites.
3. **Publish behind one API.** Every pipeline becomes a versioned endpoint. Generate from your product, scripts, or agents with the typed `/invoke` API or an OpenAI-compatible streaming endpoint.

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## What a pipeline is made of

* **Nodes** - the building blocks on the canvas. Input nodes accept values, model nodes generate media, prompt and transform nodes reshape data between steps, guardrail nodes handle sensitive data, and output nodes define the response.
* **Edges** - the connections that pass each node's output to the next.
* **Contract** - the input and output keys, derived from your input and output nodes, that define the pipeline's API surface.
* **Versions** - each publish snapshots the graph and assigns a version number that API traffic runs against.

See [Concepts](/getting-started/concepts.md) for the full model.

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## What you can build

* **Video** with Veo 3.1 and Sora 2.
* **Images** with Gemini image models.
* **Text** with open models like Llama, DeepSeek, and Qwen.
* **Audio and embeddings** for transcription and retrieval steps.

Because each generator is a node, a single prompt can drive several modalities in one pipeline: refine a brief, render a clip, draft a caption, and transcribe the result, all in one run.

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## In this section

* [**Build your first pipeline**](/pipelines/quickstart.md) - from a prompt to a published API in a few minutes.
* [**Models**](/pipelines/models.md) - the catalog and how to use any Hugging Face or OpenRouter model id.
* [**Publishing & versioning**](/pipelines/publishing.md) - publish, version, roll back, and read run history.

For calling a published pipeline from code, see the [Pipeline API](/api/pipeline-api.md).