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

# Uploading Documents

> Add documents to your Knowledge Base datasets.

Upload documents to your datasets to make them searchable and available to Stella AI.

### Supported File Types

| Format   | Extensions      | Notes                            |
| -------- | --------------- | -------------------------------- |
| PDF      | `.pdf`          | Text is extracted from all pages |
| Word     | `.docx`, `.doc` | Full document content extracted  |
| Text     | `.txt`          | Plain text files                 |
| Markdown | `.md`           | Markdown formatting preserved    |

**File Size Limit:** 10 MB per file

### Upload a Document

<Note>
  Uploading documents requires Admin access.
</Note>

1. Navigate to **Knowledge Base**

2. Open the dataset where you want to add documents

3. Click **Upload Documents**

4. Either:
   * **Drag and drop** files into the upload area, or
   * Click **Browse** to select files from your computer

5. Click **Upload**

The document will be queued for processing and appear in your dataset.

### Document Processing

After upload, documents go through automatic processing:

| Status         | Meaning                                        |
| -------------- | ---------------------------------------------- |
| **Pending**    | Queued for processing                          |
| **Processing** | Being indexed (chunking, embedding generation) |
| **Completed**  | Ready for search                               |
| **Failed**     | Error during processing (check file format)    |

<Note>
  Processing typically completes within a few minutes. Larger documents may take longer.
</Note>

### What Happens During Processing

1. **Text Extraction**: Content is extracted from the document

2. **Semantic Chunking**: Content is split into meaningful segments (up to 2000 characters each)

3. **Embedding Generation**: Each chunk is converted to a vector embedding using AI

4. **Indexing**: Embeddings are stored in the database for fast similarity search

Once complete, the document is searchable by Stella AI (if the dataset has "Searchable in Stella" enabled).

### Delete a Document

1. Open the dataset containing the document

2. Find the document in the table

3. Click the **trash** icon

4. Confirm the deletion

**Bulk Delete:**

1. Select multiple documents using the checkboxes
2. Click **Delete** in the action bar
3. Confirm the deletion

### Troubleshooting

<Accordion title="Document stuck in 'Processing'">
  Processing usually completes within minutes. If a document stays in "Processing" for an extended period:

  * The document may contain complex formatting
  * Try re-uploading the document
  * Contact support if the issue persists
</Accordion>

<Accordion title="Document shows 'Failed' status">
  Common causes:

  * **Corrupted file**: Try opening the file locally to verify it's readable
  * **Unsupported format**: Ensure the file is a supported type (PDF, DOCX, TXT, MD)
  * **Password protection**: Remove password protection and re-upload
  * **Scanned PDF without OCR**: PDFs must contain extractable text, not just images
</Accordion>

<Accordion title="File exceeds size limit">
  If your file is larger than 10 MB:

  * Split large documents into smaller sections
  * Remove embedded images or unnecessary formatting
  * Compress the file before uploading
</Accordion>

### Best Practices

<Tip>
  **Use descriptive file names** - Document names appear in search results and help users identify content.
</Tip>

* Keep documents focused on single topics when possible
* Update documents by deleting the old version and uploading the new one
* Review document status to ensure processing completed successfully
* Organize related documents in the same dataset