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dify-docs/en/use-dify/knowledge/create-knowledge/import-text-data/readme.mdx
Riskey 5d7556d5f2 Refine docs based on readability, usability, and enterprise PM feedback (#619)
* Refine docs based on internal feedback

* update the zh and ja docs

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Co-authored-by: Riskey <riskey47@dify.ai>
2025-12-16 19:37:13 +08:00

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---
title: Upload Local Files
---
<Note>
Once a knowledge base is created, its data source cannot be changed later.
</Note>
When quick-creating a knowledge base, you can upload local files as its data source:
1. Click **Knowledge** > **Create Knowledge**.
2. Select **Import from file** as the data source, then upload your files.
- Maximum number of files per upload: 5
<Info>
On Dify Cloud, **batch uploading** (up to 50 files per upload) is only available on [paid plans](https://dify.ai/pricing).
</Info>
- Maximum file size: 15 MB
<Tip>
For self-hosted deployments, you can adjust these two limits via the environment variables `UPLOAD_FILE_SIZE_LIMIT` and `UPLOAD_FILE_BATCH_LIMIT`.
</Tip>
---
**For Images in Uploaded Files**
JPG, JPEG, PNG, and GIF images under 2 MB are automatically extracted as attachments to their corresponding chunks. These images can be managed independently and are returned alongside their chunks during retrieval.
Each chunk supports up to 10 image attachments; images beyond this limit will not be extracted.
<Tip>
For self-hosted deployments, you can adjust the following limits via environment variables:
- Maximum image size: `ATTACHMENT_IMAGE_FILE_SIZE_LIMIT`
- Maximum number of attachments per chunk: `SINGLE_CHUNK_ATTACHMENT_LIMIT`
</Tip>
The above extraction rule applies to:
- Images embedded in DOCX files
<Note>
Images embedded in other file types (e.g., PDF) can only be extracted by using appropriate document extraction plugins in [knowledge pipelines](/en/use-dify/knowledge/knowledge-pipeline/readme).
</Note>
- Images referenced via accessible URLs using the following Markdown syntax in any file type:
- `![alt text](image_url)`
- `![alt text](image_url "optional title")`
<Tip>
If you select a multimodal embedding model (indicated by the **Vision** icon) in subsequent index settings, the extracted images will be embedded and indexed for retrieval.
</Tip>