40 minutes.
Ship memory
into your agent.
Welcome to the Beta Fund × EverMind One Person Company Hackathon. This workshop skips the story — it's pure flow: from zero to EverOS, all the way to a working demo.
Press → for step one · F fullscreen · Esc exit
Today you only do 4 things.
No ML degree, no GPU. A browser, an editor, and a cup of coffee.
Create an account — hackathon credit is auto-granted.
Local and SDK calls both run on this key.
Pick curl, Python, or Node — see a response and you're through.
Fork a ready use case → change 30% → submit.
Sign up for EverOS Cloud.
EverMind is your runtime and AI capability source for today. Sign up and your hackathon credit drops automatically — enough to last the whole day.
What you'll get
- $50 hackathon credit Enough to run every demo and retry 5+ times on errors
- Access to mainline LLM + agent orchestration APIs reasoning / tools / memory — the full set
- Private fork access to the EverOS template library 20+ use cases, clone and go
- Access to the Discord
#hackathon-may30channel Stuck? @ a mentor here
Create your account
3 key moves during sign-up.
- Sign in with GitHub Fastest path — auto-links your commit history, no re-login when forking templates
- Enter invite code
HACK0530This code triggers credit issuance — without it, you only get the $5 default trial - Skip the onboarding survey Top right corner — "Skip for now". No time during the workshop; fill it out later this week.
- Check your credit balance in the dashboard Top right should show $50.00. If you don't see it, @ a mentor immediately.
Welcome back
Grab your developer key.
The API Key is the one credential your code and SDK use to talk to EverMind. 30 seconds in the console — this key opens every door that follows.
The path
- Dashboard → click your avatar (top right) → Developer
- Left sidebar → API Keys
- Top right → Create new key
- Name it
hackathon-may30 - Copy it immediately — once you leave the page, you'll never see it again
API Keys
Put the API Key in the right place.
This is the single most common way hackathon teams crash — key gets committed to a public GitHub repo, a bot scrapes it, credit zeroes out overnight.
✓ The right way
- Put it in a
.envfile at your project root Format: EVEROS_API_KEY=sk-em-xxxx - Add
.envas the first line of.gitignore - Read it in code via
os.getenv("EVEROS_API_KEY") - Redact or use placeholders before sharing code screenshots
EVEROS_API_KEY=sk-em-your-real-key-here # matches `pip install everos` SDK · see docs.evermind.ai/cookbook/quickstart
.env .env.local node_modules __pycache__/
git status before every commit.
Two APIs. Just these two.
EverOS makes "memory" into CRUD — POST /memories to store · GET /memories/search to query. 99% of what you'll use the whole hackathon is these two endpoints.
# Real EverOS API · from github.com/EverMind-AI/EverOS README import requests API_BASE = "http://localhost:1995/api/v1" # OSS local — for Cloud, swap in the endpoint from everos.evermind.ai # 1) Store a memory requests.post(f"{API_BASE}/memories", json={ "message_id": "msg_001", "create_time": "2026-05-30T11:15:00+00:00", "sender": "user_001", "content": "I love playing soccer on weekends", }) # 2) Search it back with natural language res = requests.get(f"{API_BASE}/memories/search", json={ "query": "What sports does the user like?", "user_id": "user_001", "memory_types": ["episodic_memory"], "retrieve_method": "hybrid", }) print(res.json()["result"]["memories"])
# Real EverOS API · run this after the OSS deploy; for Cloud, use the URL from everos.evermind.ai # 1) Store a memory curl -X POST http://localhost:1995/api/v1/memories \ -H "Content-Type: application/json" \ -d '{ "message_id": "msg_001", "create_time": "2026-05-30T11:15:00+00:00", "sender": "user_001", "content": "I love playing soccer on weekends" }' # 2) Search with natural language curl http://localhost:1995/api/v1/memories/search \ -H "Content-Type: application/json" \ -d '{ "query": "What sports does the user like?", "user_id": "user_001", "memory_types": ["episodic_memory"], "retrieve_method": "hybrid" }'
// Real EverOS API · Node 18+ has fetch built in const API_BASE = "http://localhost:1995/api/v1"; // 1) Store a memory await fetch(`${API_BASE}/memories`, { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ message_id: "msg_001", create_time: "2026-05-30T11:15:00+00:00", sender: "user_001", content: "I love playing soccer on weekends", }), }); // 2) Search const res = await fetch(`${API_BASE}/memories/search`, { method: "GET", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ query: "What sports does the user like?", user_id: "user_001", memory_types: ["episodic_memory"], retrieve_method: "hybrid", }), }); console.log(await res.json());
curl http://localhost:1995/health to confirm the server is up — if it's not, go back to Step 2 and check docker compose / uv run python src/run.py.
This is what a working memory looks like.
EverOS isn't chat completion — it extracts raw content into structured memory with episodic / semantic / timestamps. Below is the real shape of a search response.
$ curl -X POST http://localhost:1995/api/v1/memories \ -d '{"message_id":"msg_001","sender":"user_001", "content":"I love playing soccer on weekends", "create_time":"2026-05-30T11:15:00+00:00"}' {"status":"ok","memory_id":"mem_8f3a..."} $ curl http://localhost:1995/api/v1/memories/search \ -d '{"query":"What sports does the user like?", "user_id":"user_001","retrieve_method":"hybrid"}' { "result": { "memories": [ { "memory_id": "mem_8f3a...", "type": "episodic_memory", "content": "I love playing soccer on weekends", "score": 0.91, "create_time": "2026-05-30T11:15:00+00:00" } ] } }
✓ Seeing this means
- Docker stack is up (Mongo / Elasticsearch / Milvus / Redis — all 4 services healthy)
- LLM_API_KEY + VECTORIZE_API_KEY are both wired up
- You're clear to start stacking use cases — see Step 04
✗ If you don't see it
Connection refused→ server isn't running. Runuv run python src/run.pyOr confirm all 4 docker compose services are healthy500 + vectorize error→ VECTORIZE_API_KEY not set or wrong provider- Empty memories array in the response → wait 5 seconds and search again; extraction has async lag
Stand on the shoulders of a SOTA memory stack.
EverOS isn't a wrapper — it's the memory OS itself. Apache 2.0, Docker up, 4 infra services auto-wired (MongoDB · Elasticsearch · Milvus · Redis). Fork a real demo today, change 30%, and that's your product.
$ git clone https://github.com/EverMind-AI/EverOS.git $ cd EverOS/methods/EverCore # the runnable method lives here, not at repo root $ docker compose up -d # spins up Mongo + ES + Milvus + Redis $ curl -LsSf https://astral.sh/uv/install.sh | sh && uv sync $ cp env.template .env # fill in LLM_API_KEY + VECTORIZE_API_KEY $ uv run python src/run.py # server starts on :1995 $ curl http://localhost:1995/health → {"status": "healthy", ...}
everos.evermind.ai — Cloud hands you a pre-wired endpoint + API key, and you skip straight past Steps 1–6 into the API.
Stand on 20 shoulders.
↑ All 20 from github.com/EverMind-AI/EverOS#use-cases · Click any tile to open the repo · Fork → 30% change → submit
From demo to your product.
EverOS ships runnable entry points like demo/simple_demo.py and demo/chat_with_memory.py. Pick the demo closest to your product, swap the prompts / sender / content, and you'll have a working version in 3 hours.
- 1. Fork the repo on GitHub github.com/EverMind-AI/EverOS → top-right Fork → your account
- 2. Get the local server running Step 04's 6-step quick-start · health endpoint returns healthy
- 3. Run a demo to verify uv run python src/bootstrap.py demo/simple_demo.py · watch a complete store-and-recall memory cycle
- 4. Modify the demo → your product Swap prompts · swap sender/user_id structure · plug in your frontend or data source
- 5. Record a 2:30 demo video Submit before 4pm · 2 slides + working product video (must show a working memory cycle)
# Terminal 1 · start the server $ uv run python src/run.py # Terminal 2 · run simple_demo $ uv run python src/bootstrap.py demo/simple_demo.py # Next level · interactive chat with memory $ uv run python src/bootstrap.py demo/chat_with_memory.py
5 lessons last year's teams paid in blood for.
Demo first, features later
By 11:30 you must have the ugliest possible version that runs. Reject every "just one more feature" temptation until you can demo.
Record the demo — don't go live
A 2:30 video can be cut and re-shot. Going live in front of judges on venue Wi-Fi = disaster. Finish recording before 3pm so you have time to edit.
Team–problem fit beats technical flash
"Why you're the one to build this" on slide 1 moves judges more than "which model we used."
Social Media King is real cash
Post on X / Jike / Xiaohongshu as you build, with #onepersoncompany and @evermind. 7 days later the cash actually lands.
Stuck? @ a mentor immediately — don't suffer silently
Mentors are on Discord #hackathon-may30 and on-site. Every mentor wants you to ship — asking for help isn't embarrassing, not shipping is.
You need these 3 things at submission.
- Slide 1 · Team Introduction Name / school or company / relevant experience / team–problem fit
- Slide 2 · Product Overview One-sentence pitch / the problem you're solving / the solution you built
- Slide 3 · Demo Video 2 minutes max · must show a working product · no mockups
- GitHub repo link Must be public (or add the hackathon org as a collaborator)
- Live URL (if you have one) A link judges can try themselves is a massive scoring boost
📅 Day timeline
#hackathon-may30 channel at 3:00 PM sharp — bookmark the channel and turn on notifications.
Three prize tiers — every detail matters.
🏆 Audience Favorite
🥈 $500
🥉 $400
4️⃣ $300
5️⃣ $200
Decided by audience vote · cash paid out at 5pm.
📱 Social Media King
🥈 $300
🥉 $200
Judged on the real reach of your demo / build log on social platforms over 7 days. Prizes paid via Discord.
⚡ Beta Fellowship
Direct admission to the Beta University 8-week accelerator — no standard application required.
On project completion, Beta Fund invests $25,000.
Real humans are waiting at every one of these.
Discord — two of them
Hackathon Discord (your home today)
team-formation · tech-support · submissions
EverMind Discord (official EverOS · long-term)
Biweekly AMA · talk directly with maintainers
On-site Mentor Desk
📍 South side of the Workshop area
👋 Anyone wearing a gold badge is a mentor
⏰ On-site all day, 09:30 — 16:00
On average, each mentor unblocks one team in 15 minutes.
Docs & code
docs.evermind.ai/introduction
API reference + both Cloud and Open Source paths
github.com/EverMind-AI/EverOS
5.6k stars · 593 forks · Apache 2.0
deepwiki.com/EverMind-AI/EverOS
AI Q&A, multilingual, covers setup → advanced
People
EverOS Maintainer:
X @elliotchen200 · GitHub @cyfyifanchen
Reddit: r/EverMindAI
Email: contact@evermind.ai
Biweekly Discord AMA — talk to a maintainer directly.
Keep
in Mind.
Evolve
over Time.
You only have today. Don't aim for perfect — aim for "ready to show a judge." Memory is your unfair advantage.
Workshop ends · Build time starts · See you at 4 PM demo round.