Prompt Template

Estimated reading: 3 minutes 323 views

Use the Prompt Template core component to create a prompt that supplies instructions and context to an LLM or agent, separate from other input like chat messages and file uploads.

Prompts are structured input that use natural language, fixed values, and dynamic variables to provide baseline context for the LLM. For example:

1. Define a consistent structure for user queries, making it easier for the LLM to understand and respond appropriately.
2. Define a specific output format for the LLM, such as JSON or structured text.
3. Define a role for the LLM, such as You are a helpful assistant or You are an expert in microbiology.
4. Allow LLM to reference chat memory.

The Prompt Template component can also output variable instructions to other components later in the flow.

Prompt Template parameters

Name Display Name Description
template Template Input parameter. Create a prompt template with dynamic variables ({VARIABLE_NAME}).
prompt Prompt Message Output parameter. The built prompt message returned by the build_prompt method.

Define variables in prompts

Variables in a Prompt Template component dynamically add fields to the Prompt Template component so that your flow can receive definitions for those values from other components, Robility flow  global variables, or fixed input.

For example, with the Message History component, you can use a {memory} variable to pass chat history to the prompt. However, the Language Model and Agent components include built-in chat memory that is enabled by default. For more information, see Memory management options.

The following steps demonstrate how to add variables to a Prompt Template component:

1. Create a flow based on the Basic prompting template.

This template already has a Prompt Template component, but the template only contains natural language instructions: Answer the user as if you were a GenAI expert, enthusiastic about helping them get started building something fresh.

This prompt defines a role for the LLM’s chat interactions, but it doesn’t include variables that help you create prompts that adapt dynamically to changing contexts, such as different users and environments.

2. Click the Prompt Template component and then add some variables to the Template field.

Variables are declared by wrapping the variable name in curly braces, like {variable_name}. For example, the following template creates context and user_question variables:

Given the context:

{context}

Answer the question:

{user_question}

3. Click Check & Save to save the template.

After adding the variables to the template, new fields are added to the Prompt Template component for each variable.

4. Provide input for the variable fields:

a. Connect the fields to other components to pass the output from those components to the variables.
b. Use Robility flow global variables.
c. Enter fixed values directly into the fields.

You can add as many variables as you like in your template. For example, you could add variables for {references} and {instructions}, and then feed that information in from other components, such as Text InputURL, or File components.

Share this Doc

Prompt Template

Or copy link

CONTENTS