Quickstart

This guide makes one authenticated request end to end so you can see the shape of a Humalike call: how you send your token, what a request body looks like, and how to read the response. It uses the Social Learning API as the example — every other API follows the same pattern.

1. Get a token

You authenticate with a bearer token tied to your account. See Authentication for how to obtain and send it. In the examples below, set it as an environment variable:

export HUMALIKE_TOKEN="your-token"

2. Send a transcript

POST /v1/social-learning/actions/extract with a JSON body containing a transcript whose messages array has at least one message.

curl https://api.humalike.com/v1/social-learning/actions/extract \
  -H "Authorization: Bearer $HUMALIKE_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "transcript": {
      "messages": [
        {"id": "m1", "speaker": "ada", "text": "yo we still on for tonight"},
        {"id": "m2", "speaker": "max", "text": "ye 8pm same spot"}
      ]
    }
  }'

import os
import httpx

resp = httpx.post(
    "https://api.humalike.com/v1/social-learning/actions/extract",
    headers={"Authorization": f"Bearer {os.environ['HUMALIKE_TOKEN']}"},
    json={
        "transcript": {
            "messages": [
                {"id": "m1", "speaker": "ada", "text": "yo we still on for tonight"},
                {"id": "m2", "speaker": "max", "text": "ye 8pm same spot"},
            ]
        }
    },
)
resp.raise_for_status()
print(resp.json()["prompt_block"])

const res = await fetch("https://api.humalike.com/v1/social-learning/actions/extract", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.HUMALIKE_TOKEN}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    transcript: {
      messages: [
        { id: "m1", speaker: "ada", text: "yo we still on for tonight" },
        { id: "m2", speaker: "max", text: "ye 8pm same spot" },
      ],
    },
  }),
});

if (!res.ok) throw new Error(`Request failed: ${res.status}`);
const data = await res.json();
console.log(data.prompt_block);

3. Read the response

A successful call returns 200 with a structured profile and a ready-to-use prompt_block:

{
  "profile": { "summary": "casual, lowercase, terse group chat", "...": "..." },
  "prompt_block": "Match this group's voice. Write in lowercase; keep messages to one or two short lines; ..."
}

Drop prompt_block straight into your agent’s prompt, or read individual profile fields if you want finer control.

That’s it — one authenticated POST is the whole flow. Every Humalike API works this way: a bearer token, a JSON body, a JSON response.

Social Learning — the full request and response schema for the call above.
Persona — generate a lifelike population from a prompt.
Theory of Mind — predict how a reply will land before you send it.
Turn-taking — decide when an agent speaks and pace its reply.
Social Memory and Social Observability — remember a conversation, and measure how your agent is landing.

Get started

Turn-taking API

Persona API

Social Learning API

Social Observability API

Social Memory API

Theory of Mind API

Account

1. Get a token

2. Send a transcript

3. Read the response

Next

​1. Get a token

​2. Send a transcript

​3. Read the response

​Next

1. Get a token

2. Send a transcript

3. Read the response

Next