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

# Custom Prompts

> Learn how to create and manage custom prompts in the Canvas feature to enhance chatbot behavior.

The **Custom Prompts** feature allows you to define specific instructions for your chatbot at a node level. This enables greater control over how the chatbot interacts with users by tailoring its responses to specific scenarios or tasks.

***

## What Are Custom Prompts?

Custom prompts are node-specific instructions that modify the chatbot's behavior and responses. By creating custom prompts, you can:

* Define specific tones, styles, or objectives for each node.
* Tailor responses to match the context of a conversation.
* Combine prompts with tools and variables to make interactions dynamic.

***

## Creating Custom Prompts

### 1. Using the Text Editor

Custom prompts are written directly in the **Text Editor** of a node. The Text Editor allows you to:

* Write instructions for the chatbot in plain text.
* Insert variables and tools dynamically using the `{` shortcut.

#### Steps:

1. Open the node's settings and go to the **Overview** tab.
2. In the **Instructions** field, write the prompt for that node.
3. Use `{` to insert variables or tools dynamically.

**Example**:

```plaintext theme={null}
Hello {user_name}, I see you’re interested in {product_name}. How can I assist you further?
```

***

### 2. Combining with LLM Configuration

Enhance your custom prompts by adjusting the **LLM Configuration** for the node:

* **Temperature**: Adjust creativity or randomness in responses.
* **Max Tokens**: Limit the length of responses.
* **Rewind Level**: Allow the chatbot to recall context from previous nodes.

#### Example:

* Set a custom prompt: “Provide concise and fact-based responses.”
* Adjust the **Temperature** to `0.3` for precise, non-creative answers.

**Visual Placeholder**:\
<img src="https://mintlify.s3.us-west-1.amazonaws.com/convocore/canvas/features/PLACEHOLDER_FOR_IMAGE" alt="Custom Prompt with LLM Configuration" />\
*Image showing LLM settings paired with a custom prompt.*

***

## Examples of Custom Prompts

1. **Customer Support**:

   ```plaintext theme={null}
   Hi {user_name}, how can I assist you today? Please be as specific as possible.
   ```

2. **FAQ Assistance**:

   ```plaintext theme={null}
   Based on our knowledge base, here is what I found for {query_topic}.
   ```

3. **Appointment Scheduling**:

   ```plaintext theme={null}
   Let’s schedule your appointment. What date and time works best for you?
   ```

4. **E-Commerce Recommendation**:
   ```plaintext theme={null}
   I recommend {product_name} for your needs. Would you like to add it to your cart?
   ```

***

## Testing Custom Prompts

Once created, test your custom prompts to ensure they generate the desired responses:

1. Use the **Test Tool** in the **Canvas Workspace**.
2. Input sample user queries and observe the chatbot’s response.
3. Adjust prompts or configurations as needed for better results.

***

## Best Practices for Custom Prompts

* **Be Specific**: Write clear and concise instructions for the chatbot.
* **Use Variables**: Incorporate dynamic data for personalized responses.
* **Adjust LLM Settings**: Pair prompts with appropriate temperature and token limits for optimal behavior.
* **Test Thoroughly**: Simulate various user scenarios to refine prompts.

***

### Example Flow with Custom Prompts

**Scenario**: An e-commerce chatbot flow:

1. **Start Node**: Greets the user with a custom welcome prompt.
2. **Product Node**: Recommends products based on user input.
3. **FAQ Node**: Provides detailed answers from the knowledge base.
4. **End Node**: Thanks the user and summarizes the session.

***

Ready to optimize your chatbot further? Explore [Models Configuration](features/models-configuration) to fine-tune your AI's performance.