license: cc-by-nc-4.0
language:
- en
pretty_name: EchoSim Synthetic Compatibility Dialogues (Sample)
tags:
- synthetic
- dialogue
- dating
- conversational
- personas
task_categories:
- text-generation
size_categories:
- n<1K
configs:
- config_name: default
data_files: synthetic_dating_dataset_sample.jsonl
EchoSim Synthetic Compatibility Dialogues (Sample)
A fully synthetic corpus of AI-simulated first-contact dialogues between two dating personas. Each record pairs two personas (MBTI, attachment style, interests, age range) with a short conversation. Current release: 200 sessions.
This is a public research / schema sample released by EchoSim.AI. It is meant to illustrate the shape of the data used to study conversational compatibility — not to expose any production system.
Links: Official site · GitHub specs & whitepaper · Hugging Face org · Demo Space
⚠️ Synthetic data. Every record is generated by LLM simulation from sampled persona attributes. There are no real users, no real conversations, and no PII. No persona corresponds to a real person.
Why synthetic?
EchoSim simulates AI "Echoes" dating on a user's behalf. To share research artifacts without touching real user data, we publish synthetic samples generated by the same kind of pipeline. What is intentionally not included: the production matching algorithm, scoring logic, the internal signal taxonomy, and any user-derived data.
Dataset structure
One JSON object per line (synthetic_dating_dataset_sample.jsonl).
| Field | Type | Description |
|---|---|---|
session_id |
string | Stable id for the simulated session |
personas |
object | user_A / user_B, each with mbti, attachment_style, interests[], age_range |
dialogue |
array | Ordered turns of {role, message} |
Example
{
"session_id": "sim_001",
"personas": {
"user_A": {"mbti": "INTJ", "attachment_style": "Dismissive-Avoidant", "interests": ["Tech", "Reading", "Chess"], "age_range": "28-32"},
"user_B": {"mbti": "ENFP", "attachment_style": "Secure", "interests": ["Travel", "Photography", "Live Music"], "age_range": "25-29"}
},
"dialogue": [{"role": "user_B", "message": "..."}]
}
How it was generated
- Persona sampling — combinatorial sampling across MBTI type, adult attachment style, an interest set, and a coarse age range.
- Dialogue generation — an LLM role-plays both personas through a short first-contact exchange.
Usage
from datasets import load_dataset
ds = load_dataset("json", data_files="synthetic_dating_dataset_sample.jsonl", split="train")
print(ds[0])
Limitations & intended use
- Small corpus (200 records). Intended for schema illustration, prototyping, and smoke tests rather than large-scale training.
- Content is English-only and may carry the biases of the generating LLM.
- Persona frameworks (MBTI, attachment style) are used as descriptive tags, not scientific claims.
- Do not use for real-world relationship, psychological, or hiring decisions.
License
Released under CC-BY-NC-4.0. Attribution: EchoSim.AI (https://echosim.ai).