Building with AI LLMs
Learn how to use AI Language Models to build applications with the OpenPhone API.
Introduction
Building with Large Language Models (LLMs) can significantly accelerate your OpenPhone API integration development. This guide will help you effectively use LLMs to create applications with our API.
While we provide examples using Claude, the principles and practices outlined here apply to any capable LLM platform.
Getting started
Documentation setup
Before beginning development with an LLM, gather and prepare the necessary documentation:
Download OpenAPI specification
Get our OpenAPI specification for detailed endpoint information.
Tip: Right-click and select “Save Link As…” to download the file
Get complete documentation
Download and extract our complete documentation package
Share with your LLM
Provide these resources to your LLM to help it understand OpenPhone API capabilities
Development process
Working with LLMs
Clear goals
Start by clearly describing your integration objectives to the LLM
Documentation
Share relevant API documentation and specifications
Step breakdown
Let the LLM help break complex features into manageable tasks
Iterative development
Generate and review code one step at a time
Best practices
Example interactions
Here’s a practical example of how to instruct an LLM to help build with our API:
Integration patterns
Message automation
Automate message handling and responses
Contact management
Sync and manage contact information
Call analytics
Process call summaries and recording data
Scheduling
Manage scheduling and reminders
Implementation checklist
Code review
Thoroughly review all LLM-generated code
Testing
Test extensively in a development environment
Error handling
Implement comprehensive error handling and logging
Monitoring
Deploy with appropriate monitoring systems
Iteration
Continuously improve based on usage and feedback
Need more detailed guidance? Check out our comprehensive API Reference for detailed endpoint documentation and examples.
Was this page helpful?