# Chat Table {% embed url="" %} Demo of Chat Table Usage {% endembed %} ## Basic Usage 1. Every chat table needs a LLM Agent. Let's create our agent. **>> Chat Table >> Agents >> New Agent.**

2. Let's add and configure our LLM Agent.

Configuration Parameters: * Agent ID: Name of your agent. * Models: LLM Model. * Temperature: * Max tokens: * Top-p: * Customize system prompt (optional): Define the behaviour of your LLM Agent. * User message (optional): Set a first reply to your LLM Agent. * AI response (optional): Conversational opener by your LLM Agent. 3. Select the **LLM Agent** that you have created and create a **new conversation.**

4. You will be brought to the **Chat Table** interface.

5. Toggle between **Conversation Mode** and **Table Mode** using the toggle bar on the top right of the interface.

6. Start chatting with your LLM Agent.

## Advanced Usage: Chat with your Knowledge Table 1. After creating your LLM Agent, select it. Click on the LLM Agent. You will be brought to a **Table View**. 2. Update the LLM Agent configuration to use RAG. 1. If you are in **Table View. Click on the**

of **AI** (output column)and **open settings.** 2. If you are in **Conversation View. Click**

to bring up the Model setting. 3. There are a few settings to configure: * **k**: The number of maximum Knowledge Row that can be fetched as references during RAG. * **Reranking Model** (optional): Reranking the Knowledge Row retrieved before passing it into LLM Agent. * **Knowledge Table**: The table to search for Knowledge Rows as references.

4. Start chatting.