> For the complete documentation index, see [llms.txt](https://docs.botdistrikt.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.botdistrikt.com/features/sources/documents.md).

# Documents

### **Documents**

To view the documents dashboard, click **Sources --> Documents** (tab)

<figure><img src="/files/ADzMd2hZfUGGOBYOtPGi" alt=""><figcaption><p>Documents as Sources</p></figcaption></figure>

Click **New Source Document** to add a training document and title. BotDistrikt parses the document into the following information:

<figure><img src="/files/79auVE2NLDxrg9WzgevN" alt=""><figcaption><p>Uploaded Training Document</p></figcaption></figure>

1. Specifies **Document Type.**
2. Number of characters in the document.
3. Adjusting the **Chunk Size** changes the character count in a chunk. You can toggle chunk size from the slider or the **Use Recommended** button. A large chunk size retains more context while a small chunk size captures more granular semantic data.
4. **Chunk Overlap** from one chunk to another. You get improved context, a better training model for longer documents, and enhanced coherence. You can increase chunk size if the document consists of numerous unrelated topics.&#x20;
5. The Output shows the number of responses that will be generated based on the **Chunk Size** and **Chunk Overlap** settings.
6. Click **Show Example Responses** to view sample extracted responses.
7. Click **Train AI** to train your bot with the document.

The screen redirects to the main **Sources (Documents)** dashboard.&#x20;

<figure><img src="/files/6YM0MIGiPLiPHm5eLtSi" alt=""><figcaption><p>Uploaded Training Document Dashboard</p></figcaption></figure>

To ensure the embeddings are created, go to **Responses** --> **Text** and confirm whether the embeddings are created.&#x20;

The **Embeddings** column displays the LLM name (OpenAI, Vertex AI, etc.). A tick signifies successfully created embedding and a cross signifies no embedding creation for that response. The **Tags** column indicate the source (document/website)

<figure><img src="/files/KjyA9K3y5eYFranfi1Ut" alt=""><figcaption><p>Successful Embeddings as Response from OpenAI</p></figcaption></figure>

**Troubleshooting**:

* If a file is stuck at queued, ensure that your account has not exceeded the respective tier Response Repo limit.
* If a file is stuck at the training phase, click on **Resync Source** <img src="/files/psv4kOM4sjnjgLoPXlUo" alt="" data-size="line">
* If embeddings are not created, ensure that your AI integrated account has not exceeded its token limit.


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.botdistrikt.com/features/sources/documents.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
