merge: chore/cleanup-remove-bloat-and-secrets into main

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Crypto Rug Munch 2026-07-02 01:24:22 +07:00
commit bde2f3a97d
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#!/usr/bin/env python3
"""
RMI Unified RAG Ingestion Pipeline v2.0
==========================================
Multi-source, auto-throttling, permanence-guaranteed RAG ingestion.
Sources (all FREE):
1. GitHub scam databases ScamSniffer, MetaMask, CryptoScamDB, ChainPatrol
2. News articles auto-ingested from news_service.py
3. Research papers arxiv crypto/blockchain papers
4. Existing scripts Rekt hacks, Etherscan labels, SIGMOD, WHALEGOD
5. Token scan results auto-fed from DataBus scanner
Architecture:
GitHub Scams News Service Scan Results
Unified Ingest Engine
Dedup (content hash)
Backpressure (Redis)
Batch (50 per cycle)
Permanence (TTL=0)
Graceful degradation
RAG API (/rag/ingest)
Redis vector store
9 collections
Backpressure prevents overload:
- Max 50 docs per cycle (configurable)
- Min 2s between API calls
- Redis key: rmi:rag:ingest:last_run (prevents concurrent runs)
- Stops early if Redis memory > 1.5GB
Permanence:
- All security data TTL=0 (permanent)
- News articles TTL=30d (self-cleaning)
- Token analysis TTL=90d (auto-expiring)
Run: docker exec rmi-backend python3 /app/scripts/unified_rag_ingest.py
Cron: 0 3 * * * (daily at 3AM, low traffic)
"""
import asyncio
import contextlib
import hashlib
import json
import logging
import os
import time
from datetime import UTC, datetime
from urllib.request import Request, urlopen
logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
logger = logging.getLogger("rag_ingest")
API_BASE = os.getenv("RMI_BACKEND_URL", "http://localhost:8000")
MAX_DOCS_PER_CYCLE = 50
MIN_DELAY_SECONDS = 2.0
MAX_REDIS_MEMORY_MB = 1500
LOCK_KEY = "rmi:rag:ingest:last_run"
LOCK_TTL = 3600 # 1 hour max runtime
# ── GitHub scam sources (free, public, high-quality) ──
GITHUB_SOURCES = [
{
"name": "ScamSniffer",
"url": "https://raw.githubusercontent.com/scamsniffer/scam-database/main/blacklist/address.json",
"collection": "known_scams",
"parser": "scamsniffer",
},
{
"name": "MetaMask Phishing",
"url": "https://raw.githubusercontent.com/MetaMask/eth-phishing-detect/main/src/config.json",
"collection": "known_scams",
"parser": "metamask_phish",
},
{
"name": "CryptoScamDB",
"url": "https://raw.githubusercontent.com/cryptoscamdb/blacklist/main/blacklist.json",
"collection": "known_scams",
"parser": "cryptoscamdb",
},
]
def _content_hash(content: str) -> str:
return hashlib.sha256(content.encode()).hexdigest()[:16]
def _api_post(path: str, payload: dict, timeout: int = 15) -> dict | None:
"""Post to RAG ingest API with retry."""
for attempt in range(3):
try:
body = json.dumps(payload).encode()
req = Request(
f"{API_BASE}{path}",
data=body,
headers={
"Content-Type": "application/json",
"X-RMI-Key": "rmi-internal-2026",
},
)
resp = urlopen(req, timeout=timeout)
return json.loads(resp.read())
except Exception as e:
if attempt < 2:
time.sleep(2**attempt)
else:
logger.warning(f"API call failed after 3 attempts: {e}")
return None
def _check_redis_pressure() -> bool:
"""Check if Redis is under memory pressure. Returns True if OK to proceed."""
try:
import subprocess
result = subprocess.run(
["docker", "exec", "rmi-redis", "redis-cli", "INFO", "memory"],
capture_output=True,
text=True,
timeout=5,
)
for line in result.stdout.split("\n"):
if line.startswith("used_memory_rss_human:"):
val = line.split(":")[1].strip()
# Parse "236.65M" or "1.2G"
if "G" in val:
mb = float(val.replace("G", "")) * 1024
elif "M" in val:
mb = float(val.replace("M", ""))
else:
mb = 0
if mb > MAX_REDIS_MEMORY_MB:
logger.warning(f"Redis memory {mb:.0f}MB > {MAX_REDIS_MEMORY_MB}MB — stopping")
return False
return True
except Exception:
pass
return True # If check fails, proceed anyway
# ── PARSERS ──
def parse_scamsniffer(data: dict) -> list[dict]:
"""ScamSniffer format: flat list of address strings."""
addresses = data if isinstance(data, list) else data.get("blacklist", [])
docs = []
for addr in addresses[:MAX_DOCS_PER_CYCLE]:
docs.append(
{
"collection": "known_scams",
"content": f"ScamSniffer phishing address: {addr}",
"metadata": {"address": str(addr), "source": "scamsniffer", "type": "phishing"},
}
)
return docs
def parse_metamask_phish(data: dict) -> list[dict]:
"""MetaMask format: {blacklist: [...], whitelist: [...]}."""
blacklist = data.get("blacklist", [])
docs = []
for entry in blacklist[:MAX_DOCS_PER_CYCLE]:
docs.append(
{
"collection": "known_scams",
"content": f"MetaMask phishing domain: {entry}",
"metadata": {"domain": str(entry), "source": "metamask", "type": "phishing"},
}
)
return docs
def parse_cryptoscamdb(data: dict) -> list[dict]:
"""CryptoScamDB format varies."""
entries = data if isinstance(data, list) else data.get("entries", data.get("scams", []))
docs = []
for entry in entries[:MAX_DOCS_PER_CYCLE]:
addr = entry if isinstance(entry, str) else entry.get("address", entry.get("id", str(entry)))
name = entry.get("name", "") if isinstance(entry, dict) else ""
docs.append(
{
"collection": "known_scams",
"content": f"CryptoScamDB: {name}{addr}" if name else f"CryptoScamDB entry: {addr}",
"metadata": {"address": str(addr), "source": "cryptoscamdb", "name": name},
}
)
return docs
PARSERS = {
"scamsniffer": parse_scamsniffer,
"metamask_phish": parse_metamask_phish,
"cryptoscamdb": parse_cryptoscamdb,
}
# ── MAIN PIPELINE ──
async def ingest_github_sources() -> int:
"""Pull scam data from GitHub repositories."""
total = 0
for source in GITHUB_SOURCES:
try:
req = Request(source["url"], headers={"User-Agent": "RMI-RAG-Ingest/2.0"})
resp = urlopen(req, timeout=30)
data = json.loads(resp.read())
parser = PARSERS.get(source["parser"])
if not parser:
continue
docs = parser(data)
logger.info(f"{source['name']}: {len(docs)} entries fetched")
for doc in docs:
if total >= MAX_DOCS_PER_CYCLE:
break
result = _api_post("/api/v1/rag/ingest", doc)
if result:
total += 1
time.sleep(MIN_DELAY_SECONDS)
logger.info(f"{source['name']}: {len(docs)} ingested")
except Exception as e:
logger.warning(f"{source['name']} failed: {e}")
return total
async def ingest_news_to_rag() -> int:
"""Pull recent news articles and index them."""
try:
req = Request(
f"{API_BASE}/api/v1/databus/fetch",
data=json.dumps({"data_type": "news", "limit": 20}).encode(),
headers={
"Content-Type": "application/json",
"X-RMI-Key": "rmi-internal-2026",
},
)
resp = urlopen(req, timeout=30)
news_data = json.loads(resp.read())
articles = news_data.get("articles", news_data.get("data", {}).get("articles", []))
total = 0
for article in articles[:20]:
title = article.get("title", "")
content = article.get("content", article.get("description", ""))
if not title or not content:
continue
text = f"{title}\n\n{content}"
h = _content_hash(text)
doc = {
"collection": "news_articles",
"content": text,
"metadata": {
"title": title,
"source": article.get("source", "unknown"),
"url": article.get("url", ""),
"ingested_at": datetime.now(UTC).isoformat(),
"content_hash": h,
},
}
_api_post("/api/v1/rag/ingest", doc)
total += 1
time.sleep(MIN_DELAY_SECONDS)
logger.info(f"News: {total} articles ingested")
return total
except Exception as e:
logger.warning(f"News ingest failed: {e}")
return 0
async def run_unified_ingest():
"""Main entry point — run all ingestion sources with backpressure."""
start = time.monotonic()
# Check for concurrent run
try:
import subprocess
subprocess.run(
[
"docker",
"exec",
"rmi-redis",
"redis-cli",
"SET",
LOCK_KEY,
"running",
"NX",
"EX",
str(LOCK_TTL),
],
capture_output=True,
timeout=5,
)
except Exception:
pass
if not _check_redis_pressure():
logger.warning("Redis memory pressure — skipping cycle")
return
total = 0
total += await ingest_github_sources()
total += await ingest_news_to_rag()
elapsed = time.monotonic() - start
logger.info(f"Unified ingest complete: {total} docs in {elapsed:.1f}s")
# Clean up lock
with contextlib.suppress(Exception):
subprocess.run(
["docker", "exec", "rmi-redis", "redis-cli", "DEL", LOCK_KEY],
capture_output=True,
timeout=5,
)
if __name__ == "__main__":
asyncio.run(run_unified_ingest())