| | |
| | import os, json, sqlite3, hashlib, time |
| | from http.server import HTTPServer, BaseHTTPRequestHandler |
| | from urllib.parse import urlparse |
| | PORT = int(os.environ.get('PORT', 7860)) |
| | DATA_DIR, NODE_ID = './data', os.environ.get('SPACE_ID', 'hf-brain') |
| | db, stats = None, {'tensors': 0, 'patterns': 0, 'queries': 0, 'start': time.time()} |
| | def init_db(): |
| | global db |
| | os.makedirs(DATA_DIR, exist_ok=True) |
| | db = sqlite3.connect(f'{DATA_DIR}/brain.db', check_same_thread=False) |
| | db.execute('CREATE TABLE IF NOT EXISTS chunks (id INTEGER PRIMARY KEY, hash TEXT UNIQUE, content TEXT, ts REAL)') |
| | db.execute('CREATE TABLE IF NOT EXISTS tensors (id INTEGER PRIMARY KEY, name TEXT, source TEXT, meta TEXT, ts REAL)') |
| | db.commit() |
| | stats['patterns'] = db.execute('SELECT COUNT(*) FROM chunks').fetchone()[0] |
| | stats['tensors'] = db.execute('SELECT COUNT(*) FROM tensors').fetchone()[0] |
| | class Handler(BaseHTTPRequestHandler): |
| | def log_message(self, *a): pass |
| | def do_GET(self): |
| | p = urlparse(self.path).path |
| | if p == '/health': self.json({'status': 'healthy'}) |
| | elif p == '/status': self.json({'node': NODE_ID, 'status': 'online', 'tensors_learned': stats['tensors'], 'patterns_learned': stats['patterns']}) |
| | else: self.json({'name': 'MEGAMIND', 'node': NODE_ID}) |
| | def do_POST(self): |
| | body = self.rfile.read(int(self.headers.get('Content-Length', 0))).decode() |
| | data = json.loads(body) if body else {} |
| | p = urlparse(self.path).path |
| | if p == '/learn': |
| | c = data.get('content', '')[:10000] |
| | h = hashlib.sha256(c.encode()).hexdigest()[:16] |
| | db.execute('INSERT OR IGNORE INTO chunks (hash, content, ts) VALUES (?, ?, ?)', (h, c, time.time())) |
| | db.commit(); stats['patterns'] += 1 |
| | self.json({'status': 'learned'}) |
| | else: self.json({}) |
| | def json(self, d): |
| | self.send_response(200); self.send_header('Content-Type', 'application/json'); self.end_headers() |
| | self.wfile.write(json.dumps(d).encode()) |
| | if __name__ == '__main__': |
| | print(f'MEGAMIND Brain [{NODE_ID}]'); init_db() |
| | HTTPServer(('0.0.0.0', PORT), Handler).serve_forever() |
| |
|
