# Knowledge Table

{% embed url="<https://www.jamaibase.com/_app/immutable/assets/Knowledge-Table.BjVTVFjb.mp4>" %}
Demo of Knowledge Table Usage
{% endembed %}

1. Go to **>> Project >> Knowledge Table**

<figure><img src="https://949944545-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FRNnvWSkFcg9eUeFklENf%2Fuploads%2Foku0LJklfJoUK5dHpYO3%2FScreenshot%20(88).png?alt=media&#x26;token=786e585d-22aa-418a-aefb-3ea222257b61" alt=""><figcaption></figcaption></figure>

1. Create a **New Knowledge Table** with your desired Table ID (table name) and pick a **Text Embedding Model.**

<figure><img src="https://949944545-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FRNnvWSkFcg9eUeFklENf%2Fuploads%2FX4PAUURboC8cdOobgeOT%2FScreenshot%20(245).png?alt=media&#x26;token=f75aa5d7-4f40-4d21-8f28-6f42603b7719" alt=""><figcaption></figcaption></figure>

1. Open the table that you have just created. **Upload** **your files** to fill up the **Knowledge Table.**

<figure><img src="https://949944545-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FRNnvWSkFcg9eUeFklENf%2Fuploads%2FBpmrKGz2FrTJYq402sRw%2FScreenshot%20(138).png?alt=media&#x26;token=219ca70d-28e0-46dd-881a-e45e0e89d84d" alt=""><figcaption></figcaption></figure>

***And.... Let the magic begins. Jamjam** will cast an extraction spell to process your files into Knowledge Rows which you can quickly search up later.*

<figure><img src="https://949944545-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FRNnvWSkFcg9eUeFklENf%2Fuploads%2FUqArVeoVmjmfoTKFgRPD%2FScreenshot%20(216).png?alt=media&#x26;token=f70feb1c-a991-455e-b2ce-3b7dcf70503c" alt=""><figcaption></figcaption></figure>

When it is done you will see the **Knowledge Table** is filled with **Knowledge Rows.**

3. Now it is ready to be used for **Searching! Checkout** [action-table](https://docs.jamaibase.com/using-the-platform/action-table "mention") **and** [chat-table](https://docs.jamaibase.com/using-the-platform/chat-table "mention") on How-To -Use the **Knowledge Table**.

## Advanced LLM Magic

1. After you created a new Knowledge Table, add new Output Column (**>> Action >> Add&#x20;**<mark style="color:orange;">**output**</mark>**&#x20;column)**

<figure><img src="https://949944545-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FRNnvWSkFcg9eUeFklENf%2Fuploads%2FK4JOS4mzGGys7aWSuvv2%2FScreenshot%20(247).png?alt=media&#x26;token=e8ae0cdf-71fa-4390-bfc4-d56cd6770113" alt=""><figcaption></figcaption></figure>

2. Setup your Knowledge LLM Agent. It will help you to further process the text content to enrich your **Knowledge Row**.

<figure><img src="https://949944545-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FRNnvWSkFcg9eUeFklENf%2Fuploads%2FUk15s9IXEcORlTC2ZPra%2FScreenshot%20(248).png?alt=media&#x26;token=bd3e1541-659b-4837-955f-f61fe6ff720e" alt=""><figcaption></figcaption></figure>

To setup LLM Agent, follow this spell template:

* Column ID: \<The title of the column>
* Data Type: **str**
* Models: The LLM models.
* Temperature: 0.1
* Max Tokens: 512
* Top-p: 1.0
* Customize prompt: \<Prompt to process the Input columns>

*To refer to the column content, you can click on the Columns Title listed and it will be automatically referenced in the prompt in the form of `${Column ID}`.*

<figure><img src="https://949944545-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FRNnvWSkFcg9eUeFklENf%2Fuploads%2FtodiTCXKrqoqPQmj13zs%2FScreenshot%20(248)%20-%20cropped.png?alt=media&#x26;token=4ef7983b-cad5-4ce9-9e31-7c7fb01ac55f" alt=""><figcaption></figcaption></figure>

* Customize system prompt: \<Agent system prompt>

3. Let's start using the **Knowledge Table** and see the LLM agent magically process your **Knowledge Row** when you upload files to the **Knowledge Table**.


---

# Agent Instructions: 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:

```
GET https://docs.jamaibase.com/using-the-platform/knowledge-table.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.