# TwelveLabs + Weaviate

<!-- Note: for images, use https://docs.google.com/presentation/d/15opIcJuaIjEEcs_1Zm8B6pccox2p7_MHSjCnRv4dPfU/edit?usp=sharing -->

TwelveLabs builds multimodal understanding models. Weaviate integrates with the TwelveLabs embedding API, so you can vectorize your data and your queries with a TwelveLabs model without leaving the Weaviate Database.

:::callout{intent="warning" title="Text and images only"}
TwelveLabs is best known for video understanding, but this Weaviate integration works with **text and images only**. Video and audio are not supported.
:::

## Integrations with TwelveLabs

### Embedding models for vector search

![Embedding integration illustration](/assets/docs/weaviate/model-providers/_includes/integration_twelvelabs_embedding.png)

TwelveLabs' embedding models place text and images in a shared vector space, so that a text query can retrieve images and vice versa.

[Weaviate integrates with TwelveLabs' embedding models](twelvelabs-embeddings-multimodal.md) to enable seamless vectorization of data. This integration allows users to perform semantic and hybrid search operations without the need for additional preprocessing or data transformation steps.

[TwelveLabs multimodal embedding integration page](twelvelabs-embeddings-multimodal.md)

## Summary

This integration enables developers to use TwelveLabs' multimodal embedding models within Weaviate.

In turn, it simplifies the process of building AI-driven applications to speed up your development process, so that you can focus on creating innovative solutions.

## Get started

You must provide a valid TwelveLabs API key to Weaviate for this integration. Go to [TwelveLabs](https://www.twelvelabs.io/) to sign up and obtain an API key.

Then, go to the relevant integration page to learn how to configure Weaviate with the TwelveLabs models and start using them in your applications.

- [Multimodal Embeddings](twelvelabs-embeddings-multimodal.md)

## Questions and feedback

Have a question or feedback? Here's how to reach us.

::::card-grid
:::card{title="Community Forum" href="https://forum.weaviate.io/c/support" icon="messages-square"}
Ask questions and connect with other developers on our **Community forum**.
:::

:::card{title="Support" href="/guides/support-overview" icon="life-buoy"}
Weaviate Cloud user or customer? Find the right channel on the **Support page**.
:::
::::

## Related pages

- [Agents](./agents-index.md)
- [AI-assisted Weaviate code generation](./ai-assisted-vibe-coding-index.md)
- [APIs](./apis-index.md)
- [Authorization and authentication](./authorization-and-authentication-index.md)
- [Benchmarks](./benchmarks-index.md)
- [Best practices](./best-practices-index.md)
- [Client libraries](./clients-index.md)
- [Client Libraries / SDKs](./client-libraries-index.md)
- [Cloud](./cloud-index.md)
- [Cloud account management](./cloud-account-management-index.md)

# Agent Instructions

This portal answers questions programmatically. To receive a synthesized,
source-cited answer instead of crawling page by page, append the `?ask=`
query parameter to any page URL on this site:

    /guides/quickstart?ask=how+do+I+authenticate

Optional parameters:

- `&goal=<what-you-are-trying-to-do>` steers the answer toward your
  objective (e.g. `&goal=write+a+python+client`).
- `&version=<label>` scopes the answer to a mounted version when the
  portal publishes more than one.

The response is `text/markdown`: the answer followed by a `# Sources` list
of the portal pages it was grounded in. Status codes are the contract:

- `200` — the answer; `402` — the portal owner’s plan or answer credits are
  exhausted (surface this to your operator; do NOT retry); `429` — you are
  rate-limited; back off for the `Retry-After` seconds; `503` — the answer
  lane is temporarily unavailable; fall back to crawling the `.md` pages.

For the full corpus map read `llms.txt` at the site root; for the tool
surface (search + page fetch as MCP tools) see `/mcp`.