Human API - Add the right context/memories to any LLM

Let your LLM calls use improved user memory to increase performance and save tokens/$$

Human API is a memory-enhanced endpoint that automatically injects yours or Onairos user's context/memories that are relevant automatically to any LLM call

What is Human API?

Human API is a new addition to Oneiros's vision to make the personalised internet a reality.

It works with memory enhancement built-in:

- Compatible Interface: Use any OpenAI SDK - just change the base URL

- Memory Injection: Add {onairos_memory} to prompts for instant personalization

- Zero Infrastructure: No databases, embeddings, or RAG pipelines to manage

- Privacy Built-in: Automatic PII removal and isolated user data

Quick Example

// Standard OpenAI call
const response = await openai.chat.completions.create({
  model: 'gpt-4o',
  messages: [{
    role: 'user',
    content: 'What should I work out today?'
  }]
});
// Returns: Generic workout advice

// Just change these two lines in your existing code:
const onairos_client = new OpenAI({
  apiKey: 'your_app_api_key_here',           // Your developer key for the application
  baseURL: 'https://developer.onairos.uk/v1' // Our endpoint
});

// Human API call with memory
const response = await onairos_client.chat.completions.create({
  model: 'gpt-4o',
  messages: [{
    role: 'user',
    content: 'Based on {onairos_memory}, what should I work out today?'
  }]
});
// Returns: "Since you did legs yesterday and prefer morning cardio..."

Quick Setup

1. Get Your API Keys

Follow these steps to get started:

• Sign up at developer.onairos.uk

• Create an application (choose your type: fitness, dating, productivity, etc.)

• Generate your API key from the dashboard

1.5 Key descriptions:

• Developer API key beginning with 'ona_'

• User authorized JWT key, after the user authorized Onairos data access via the in app overlay

2. Update Your Code

import OpenAI from 'openai';

// Just change these two lines in your existing code:
const onairos_client = new OpenAI({
  apiKey: 'your_app_api_key_here',           // Your developer key for the application
  baseURL: 'https://developer.onairos.uk/v1' // Our endpoint
});

// Add user identification from "Sign in with Onairos"
onairos_client.defaultHeaders = {
  'x-jwt-token': onairosUserJWT  // JWT token from user's Onairos authentication
};

3. Add Memory to Prompts

// Before: Generic responses
'Help me plan my day'

// After: Personalized with memory
'Based on {onairos_memory}, help me plan my day'

// Onairos automatically injects relevant user context

Getting Started

1. Get Your API Key

• Sign up at developer.onairos.uk

• Create an application (choose your type: fitness, dating, productivity, etc.)

• Generate your API key from the dashboard

2. Update Your OpenAI Client

import OpenAI from 'openai';

const onairos_client = new OpenAI({
  apiKey: 'ona_your_api_key_here',
  baseURL: 'https://developer.onairos.uk/v1',
  defaultHeaders: {
    'x-jwt-token': onairosUserJWT  // JWT token from user's Onairos authentication
  }
});

3. Add Memory to Your Prompts

// Add {onairos_memory} anywhere you want personalization
const response = await onairos_client.chat.completions.create({
  model: 'gpt-4o',
  messages: [{
    role: 'user',
    content: 'Based on {onairos_memory}, suggest my workout for today'
  }]
});

4. Start Getting Personalized Responses

Your users immediately get responses that know their preferences, history, and context.

Real Example: Fitness App Integration

// FitTracker app wants to personalize workout recommendations
const response = await onairos_client.chat.completions.create({
  model: 'gpt-4o',
  messages: [{
    role: 'user',
    content: 'Based on {onairos_memory}, what should I focus on in my workout today?'
  }]
});

Without memory: "Try a full-body workout with cardio and strength training..."

With memory: "Your progress shows you've been consistent with cardio. Since you did legs yesterday and prefer 30-minute sessions, let's focus on upper body strength training today."

Dating App Example

// Dating app helping users with conversation starters
const response = await onairos_client.chat.completions.create({
  model: 'gpt-4o',
  messages: [{
    role: 'user',
    content: 'Based on {onairos_memory}, suggest conversation starters for my matches'
  }]
});

Without memory: "Try asking about their hobbies, favorite movies, or travel experiences."

With memory: "Based on your interest in jazz music and weekend hiking, try asking about their favorite concert or outdoor adventures."