# 1) Store a memory
TS=$(($(date +%s)*1000))
curl -X POST http://127.0.0.1:8000/api/v1/memory/add \
  -H "Content-Type: application/json" \
  -d '{
    "session_id": "demo-001",
    "messages": [{
      "sender_id": "user_001",
      "role": "user",
      "timestamp": '"$TS"',
      "content": "I love playing soccer on weekends"
    }]
  }'
# → {"data":{"message_count":1,"status":"accumulated"}}

# 2) Flush to force extraction (boundary detector)
curl -X POST http://127.0.0.1:8000/api/v1/memory/flush \
  -H "Content-Type: application/json" \
  -d '{"session_id": "demo-001"}'
# → {"data":{"status":"extracted"}}

# 3) Search with natural language — hybrid retrieval (vector + BM25)
curl -X POST http://127.0.0.1:8000/api/v1/memory/search \
  -H "Content-Type: application/json" \
  -d '{
    "user_id": "user_001",
    "query": "What sports does the user like?",
    "method": "hybrid"
  }'

# EverOS 1.0.0 · local-first memory API
import httpx, time

API = "http://127.0.0.1:8000/api/v1"

# 1) Store a memory
httpx.post(f"{API}/memory/add", json={
    "session_id": "demo-001",
    "messages": [{
        "sender_id": "user_001",
        "role": "user",
        "timestamp": int(time.time() * 1000),
        "content": "I love playing soccer on weekends",
    }],
})

# 2) Flush to force extraction
httpx.post(f"{API}/memory/flush", json={"session_id": "demo-001"})

# 3) Search it back
res = httpx.post(f"{API}/memory/search", json={
    "user_id": "user_001",
    "query": "What sports does the user like?",
    "method": "hybrid",
})

print(res.json())

// EverOS 1.0.0 · Node 18+ · requires .mjs or "type":"module" in package.json
const API = "http://127.0.0.1:8000/api/v1";

// 1) Store a memory
await fetch(`${API}/memory/add`, {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    session_id: "demo-001",
    messages: [{
      sender_id: "user_001",
      role: "user",
      timestamp: Date.now(),
      content: "I love playing soccer on weekends",
    }],
  }),
});

// 2) Flush to force extraction
await fetch(`${API}/memory/flush`, {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({ session_id: "demo-001" }),
});

// 3) Search
const res = await fetch(`${API}/memory/search`, {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    user_id: "user_001",
    query: "What sports does the user like?",
    method: "hybrid",
  }),
});

console.log(await res.json());

curl -X POST http://127.0.0.1:8000/api/v1/memory/add \
  -H "Content-Type: application/json" \
  -d '{
    "session_id": "mm-001",
    "messages": [{
      "sender_id": "alice", "role": "user", "timestamp": 1748390400000,
      "content": [
        {"type": "text",  "text": "Here is the whiteboard from today."},
        {"type": "image", "uri": "https://example.com/whiteboard.png"}
      ]
    }]
  }'

# Skills extracted from agent usage:
$ ls ~/.everos/default_app/default_project/agents/*/skills/
skill-2026-06-12-git-workflow.md
skill-2026-06-12-api-patterns.md

# User profile (single-file rewrite, auto-clustered):
$ cat ~/.everos/default_app/default_project/users/user_001/user.md
---
kind: profile
---
# User Profile
- Prefers Python over JavaScript
- Works on web backend projects
- Usually codes in the evening