Prompt Files

What is a Prompt File?

A prompt file is a structured, serialized format for defining and managing prompts used in AI systems, particularly those powered by large language models (LLMs). Designed to be human-readable and easy to integrate into version control systems like Git, prompt files allow technical teams to treat prompts as first-class artifacts in their development workflow.

The format is heavily inspired by MDX, combining YAML headers for configuration with JSX-like syntax for defining chat templates, multi-modal interactions, and tool integrations. This approach makes it simple to manage everything from basic text-based prompts to complex workflows involving images and external tools.

Why do you Need a Prompt File?

Prompt Files let developers store prompts alongside their source code in a human-readable format that integrates seamlessly with version control systems like Git. This means prompts remain consistent across environments and are easily accessible for collaboration, debugging, iteration.

How Does a Prompt File Work?

A prompt file works by combining structured configuration with dynamic templating to create reproducible, version-controlled interactions with large language models (LLMs). At its core, the format uses a YAML header for model settings and a JSX-inspired syntax to define:

• Chat templates
• Multi-modal inputs
• Tool integrations

Prompt File Format

The prompt file format is a structured approach to managing AI prompts, combining YAML configurations with JSX-inspired templating.

A prompt file has two main sections:

1. YAML header: Configuration for model parameters and tools
2. Body: Chat templates using XML-like syntax

---  
model: gpt-4o  
temperature: 0.7  
max_tokens: -1  
provider: openai  
endpoint: chat  
---  
<system>  
  You are a friendly assistant.  
</system>  

Multi-Modality and Images

Prompt files natively support multi-modal interactions through structured XML-like tags. Developers can combine text and images in a single prompt while maintaining strict schema validation:

---  
model: gpt-4o  
temperature: 0.7  
max_tokens: -1  
provider: openai  
endpoint: chat  
tools: []  
---  
<system>  
  You are a friendly assistant.  
</system>

<user>  
  <text>  
    What is in this image?  
  </text>  
  <image url="https://upload.wikimedia.org/wikipedia/commons/8/89/Antidorcas_marsupialis%2C_male_%28Etosha%2C_2012%29.jpg" />
</user>  

Tools, Tool Calls, and Tool Responses

Prompt files let developers specify tools that an AI model can use during its interactions. These tools are defined in the YAML header as a JSON list, including attributes such as:

• Tool name
• Description
• Parameters
• Required fields

The assistant can invoke these tools using <tool> tags within its message, passing arguments in JSON format. The tool's response is then returned in a corresponding <tool> tag.

1: Tool Definition in YAML Header

These definitions declare available tools and their specifications:

tools: [  
  {  
    "name": "get_current_weather",  
    "description": "Get the current weather in a given location",  
    "parameters": {  
      "type": "object",  
      "properties": {  
        "location": {"type": "string", "name": "Location", "description": "The city and state"},  
        "unit": {"type": "string", "name": "Unit", "enum": ["celsius", "fahrenheit"]}  
      },  
      "required": ["location"]  
    }  
  }  
]  

2: Tool Call

Using the defined tool, we can initiate the LLM:

<assistant>  
  <tool name="get_current_weather" id="call_1ZUCTfyeDnpqiZbIwpF6fLGt">  
    {"location": "San Francisco, CA"}  
  </tool>  
</assistant>  

3: Tool Response

The response then provides tool execution results back to the LLM:

<tool name="get_current_weather" id="call\_1ZUCTfyeDnpqiZbIwpF6fLGt">  
  Cloudy with a chance of meatballs.  
</tool>  

Learn More About Prompt Files

Prompt files let teams unlock new levels of consistency, collaboration, and control in their AI development workflows.

At Humanloop, we empower enterprises to implement production-grade prompt management solutions, including support for prompt files, multi-modal interactions, and tool-augmented workflows. Our platform provides the tools enterprises need to simplify development and optimize LLM performance across complex applications.

To find out more about how prompt files and Humanloop’s enterprise-grade AI development platform can accelerate your team’s workflow, book a demo today.