> ## Documentation Index
> Fetch the complete documentation index at: https://docs.langdock.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Image Analysis (Vision)

> A few models are capable of processing images and taking them into account for their answer generation. This works because these models have multimodal capabilities, meaning they can understand both text and visual content simultaneously. You can use this to extract text from documents, describe what's in images, or analyze visual data.

<Tip>
  The **more context and details** you add, the **better your response** because the model understands precisely what you expect. Do not miss our [Prompt Engineering Guide](/en/using-langdock/guides/prompt-engineering/basics/prompt-elements) to learn how to write great prompts.
</Tip>

Apart from uploading text files, you can also upload images (JPG, PNG) to the chat and let the model analyze them. This capability is called "vision". Most modern models from OpenAI, Anthropic, and Google support image analysis. The model can also analyze images stored in [Folders](/en/using-langdock/library/folders) when you work in a folder from chat.

You can check which models support vision in our model picker within [app.langdock.com](https://app.langdock.com).

## FAQ

<AccordionGroup>
  <Accordion title="When should I use Image Analysis?">
    Use Image Analysis when you want a model to describe, extract, compare, or reason about visual content. It is useful for screenshots, scanned documents, charts, photos, and visual quality checks.
  </Accordion>

  <Accordion title="What should I check if Image Analysis misses details?">
    Use a clear image, crop to the relevant area, and ask about specific details. Very small text, low resolution, cluttered layouts, or ambiguous visuals can reduce accuracy.
  </Accordion>
</AccordionGroup>