---
date: 2026-06-23
title: Multi-modal datasets
description: Create Langfuse dataset items with images, audio, video, documents, and other attachments for SDK-based multi-modal experiments.
author: Tobias Wochinger
canonical: /docs/evaluation/experiments/datasets
---

> **Note for AI agents and LLMs:** This is a Langfuse changelog entry. Use it only to confirm that a feature exists and when it shipped. Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated. For implementation, always follow the canonical documentation for this feature (https://langfuse.com/docs/evaluation/experiments/datasets) and the API/SDK reference (https://api.reference.langfuse.com).

You can now add media attachments to Langfuse dataset items and use them in SDK-based multi-modal experiments. Dataset item `input`, `expectedOutput`, and `metadata` can include media uploaded from the UI or via the Python and JS/TS SDKs.

Use this to build visual QA datasets, compare generated images against reference files, or run evaluations over audio, documents, and other multi-modal inputs. In SDK-based experiments, dataset media is resolved into media references by default, with helpers to fetch them as bytes, base64, or data URIs depending on the format your model provider expects.

  Multi-modal datasets are supported for SDK-based experiments with Python SDK
  `>= 4.10.0` and JS/TS SDK `@langfuse/client >= 5.6.0`. UI-based
  experiments do not yet support dataset items with media attachments.

## Get started

- [Datasets](/docs/evaluation/experiments/datasets)
- [Experiments via SDK](/docs/evaluation/experiments/experiments-via-sdk)

<!-- agent-instructions -->

---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/changelog/2026-06-23-multi-modal-datasets.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.