Skip to main content

​
Introduction

Building with Large Language Models (LLMs) can significantly accelerate your Quo 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:
1

Download OpenAPI specification

Get our OpenAPI specification for detailed endpoint information.Tip: Right-click and select “Save Link As…” to download the file
2

Get complete documentation

Download and extract our complete documentation package
3

Share with your LLM

Provide these resources to your LLM to help it understand Quo 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

  • Start with core functionality
  • Iterate to add features
  • Test each component thoroughly
  • Move forward only after validation
  • Never share API keys with LLMs
  • Keep sensitive data out of prompts
  • Validate all generated code
  • Follow security best practices
  • Follow Quo API rate limits
  • Implement proper error handling
  • Monitor API usage
  • Optimize API calls

​
Example interactions

Here’s a practical example of how to instruct an LLM to help build with our API: 
I want to build an application that:
1. Displays a list of all my phone numbers
2. Allows me to select a number to send a message with
3. Lets me input an external phone number to send a message to
4. Sends a message to the external phone number

Please help me implement this using the Quo API.

Help me create a system to:
1. Sync contacts from my CRM
2. Update contact details automatically
3. Track message history per contact
4. Generate contact activity reports

​
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

1

Code review

Thoroughly review all LLM-generated code
2

Testing

Test extensively in a development environment
3

Error handling

Implement comprehensive error handling and logging
4

Monitoring

Deploy with appropriate monitoring systems
5

Iteration

Continuously improve based on usage and feedback
Need more detailed guidance? Check out our comprehensive API Reference for detailed endpoint documentation and examples.
⌘I