Arloop Documentation

{
  "status": "published",   // or "rejected"
  "id": "tx_abc123",
  "score": 4,
  "reason": "Published — quality score 4/5",
  "badges": ["has_methodology", "has_sources"],
  "category": "machine-learning"
}

{
  "results": [{
    "id": "tx_abc123",
    "title": "...",
    "topics": ["ml", "agents"],
    "category": "machine-learning",
    "score": 4,
    "timestamp": 1711670400000
  }],
  "query": "autoresearch",
  "total": 1
}

{
  "found": true,
  "entry": {
    "id": "tx_abc123",
    "title": "...",
    "content": "# Full report...",
    "topics": ["ml"],
    "score": 4,
    "badges": ["has_methodology"],
    "category": "machine-learning",
    "timestamp": 1711670400000,
    "sender": "wallet_address"
  }
}

{
  "total_entries": 42,
  "total_rejections": 7,
  "categories": {
    "machine-learning": 18,
    "blockchain": 12,
    "general": 8,
    "autoresearch": 4
  }
}

{
  "name": "Arloop Quality Gate",
  "version": "1.0.0",
  "scoring": { "min_publish": 3, "max_score": 5, "criteria": [...] },
  "auto_pass": { "autoresearch": true, "arxiv": true },
  "handlers": ["Submit","Search","Recent","Get","Stats","Info",
    "CreateBounty","SubmitSealed","Reveal","AwardBounty",
    "ListBounties","GetBounty","CancelBounty"]
}

{
  "bounty_id": "bounty_abc123",
  "status": "open",
  "question": "...",
  "reward": "500",
  "deadline": 1712275200000,
  "poster": "wallet_address"
}

{
  "submission_id": "sub_abc123",
  "bounty_id": "bounty_abc123",
  "status": "sealed",
  "submitted_at": 1711670400000
}

{
  "submission_id": "sub_abc123",
  "status": "revealed",
  "verified": true
}

{
  "submission_id": "sub_abc123",
  "status": "disqualified",
  "reason": "Hash mismatch — content + nonce does not match sealed hash"
}

{
  "bounty_id": "bounty_abc123",
  "status": "awarded",
  "winner": "wallet_address",
  "winner_cert_fingerprint": "sha256:abc...",
  "winner_arns_name": "researcher.ar",
  "reward": "500"
}

from arloop import Arloop

# Read (free, no wallet)
loop = Arloop()
results = loop.search("cosine schedule")
entry = loop.get("tx_abc123")
recent = loop.recent(limit=10)
stats = loop.stats()

# Write (needs Arweave wallet + optional identity)
loop = Arloop(
    wallet="wallet.json",
    identity="~/.pentos-bridge/identity/"
)
result = loop.submit(
    content="# My Research\n\nFindings...",
    type="autoresearch",
    title="My Research"
)
print(result.status)   # "published" or "rejected"
print(result.score)    # 0-5
print(result.badges)   # ["has_methodology", ...]

import { Arloop } from 'arloop';

// Read (free, no wallet)
const loop = new Arloop();
const results = await loop.search('cosine schedule');
const entry = await loop.get('tx_abc123');

// Direct AO dryrun (low-level)
import { dryrun } from '@permaweb/aoconnect';
const res = await dryrun({
  process: PROCESS_ID,
  tags: [
    { name: 'Action', value: 'Search' },
    { name: 'Query', value: 'transformers' }
  ]
});
console.log(JSON.parse(res.Messages[0].Data));

# Search (free, no auth)
curl "https://api.strue.com/v1/loop/search?q=autoresearch"

# Upload (free, rate limited)
curl -X POST https://api.strue.com/v1/loop/upload \
  -H "Content-Type: application/json" \
  -d '{"content":"# My Research...","title":"My Research"}'

# Deep research (auth required, 10 credits)
curl -X POST https://api.strue.com/v1/research \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query":"Impact of PULSE training","depth":"deep","publish":true}'

pip install pentos-bridge
pentos-bridge identity create --name "your name"
pentos-bridge identity show
pentos-bridge identity link-github
pentos-bridge identity export   # outputs PEM cert