# Documents

### **Documents**

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

<figure><img src="https://2535542804-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LirAdLo22OkAW9w3tvY%2Fuploads%2FWahAC0tMcvQn0oQlzRVH%2FSources%20--_%20D.png?alt=media&#x26;token=4d892566-c8a8-416d-8277-c700ffd838bd" 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="https://2535542804-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LirAdLo22OkAW9w3tvY%2Fuploads%2FDN31SK6g26na2KBGj7HL%2FUploaded%20Training%20Document.png?alt=media&#x26;token=c9e5fc90-eff6-4882-84cb-07391a5e0512" 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="https://2535542804-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LirAdLo22OkAW9w3tvY%2Fuploads%2FoLwIG6PDCVaPGTP0vDvO%2FUploaded%20Training%20Document%20Dashboard.png?alt=media&#x26;token=33b8c771-d3bd-473d-bc17-d9808d1b1aed" 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="https://2535542804-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LirAdLo22OkAW9w3tvY%2Fuploads%2F35zFYHjMQD9UcQ4vayqq%2FSuccessful%20Embeddings%20as%20Response%20from%20OpenAI%20.png?alt=media&#x26;token=7d19d809-c93a-45ea-ab82-90b0c4be7fec" 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="https://2535542804-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-LirAdLo22OkAW9w3tvY%2Fuploads%2FU41jarhBLhyl7dWei5H2%2FScreenshot%202024-05-27%20at%203.11.01%E2%80%AFPM.png?alt=media&#x26;token=7c0aa2e4-1580-435a-bc4e-31fe2e665edd" alt="" data-size="line">
* If embeddings are not created, ensure that your AI integrated account has not exceeded its token limit.
