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Xorafin is designed to make it easy to build, run, and share AI agents. The platform manages the entire lifecycle of an agent — from creation and configuration to execution and distribution. Each agent in Xorafin is defined through a structured configuration file and can be executed with custom inputs to generate outputs using large language models.

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High-Level Flow

The basic flow of how Xorafin works is simple: User Input ↓ Xorafin Platform ↓ AI Agent ↓ Model / Tools ↓ Generated Output
  1. A user provides input to an agent
  2. Xorafin loads the agent configuration
  3. The agent processes the request using its defined model and tools
  4. The underlying language model generates a response
  5. The final output is returned to the user

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Agent Definition

Every agent in Xorafin is defined using a configuration file. This file describes how the agent behaves, which model it uses, and what inputs and outputs it expects. Agents can be defined using:
  • JSON
  • YAML
  • TOML
Example agent definition: 
{
  "name": "research-agent",
  "description": "Research a topic and generate a summary",
  "model": "gpt-4",
  "input": "topic",
  "output": "summary"
}