Research-Stack/4-Infrastructure/shim/flac_dsp_node.py
Brandon Schneider 00e88b53a3 feat(infra): add DSP node schema and flac_dsp_node.py shim
Any Linux node with PipeWire can act as a FLAC/DSP compute worker
via a virtual sound card — no physical audio hardware required.

- ene.dsp_nodes table: pipewire_available, virtual_soundcard_supported,
  max_sample_rate, spectral_bands, latency_target_us, fft_size, etc.
- flac_dsp_node.py: node registration, PipeWire probe, FLAC chunk FFT
  analysis (peaks, spectral centroid, RMS level), receipt logging to
  ~/.cache/flac_dsp_receipts.jsonl
- AGENTS.md: document DSP volunteer computing schema addition

Build: 0 errors (py_compile)
2026-05-29 01:31:13 -05:00

282 lines
8.5 KiB
Python

#!/usr/bin/env python3
"""
flac_dsp_node.py — PipeWire/FLAC DSP compute node registration and workload processor.
Every DSP-active node registers its capabilities in ene.dsp_nodes and processes
FLAC audio chunk workloads dispatched from the VCN router.
Receipt-bearing: every DSP operation emits a receipt to ~/.cache/flac_dsp_receipts.jsonl
"""
import argparse
import json
import os
import subprocess
import sys
import time
from datetime import datetime, timezone
from pathlib import Path
from typing import Optional
DB_PATH = os.environ.get("ENE_DB", os.path.expanduser("~/.cache/ene_substrate.db"))
RECEIPT_LOG = os.path.expanduser("~/.cache/flac_dsp_receipts.jsonl")
def _ensure_db() -> None:
Path(DB_PATH).parent.mkdir(parents=True, exist_ok=True)
def _query_pipewire() -> dict:
result = {
"pipewire_available": False,
"pipewire_version": None,
"virtual_soundcard_supported": False,
"pw_loopback_available": False,
}
try:
r = subprocess.run(
["pw-cli", "info", "0"],
capture_output=True, text=True, timeout=5
)
if r.returncode == 0:
result["pipewire_available"] = True
for line in r.stdout.splitlines():
if line.startswith("obj.id"):
result["pipewire_version"] = line.split("=")[-1].strip()
break
except (FileNotFoundError, subprocess.TimeoutExpired):
pass
try:
r = subprocess.run(
["pw-link", "-l"],
capture_output=True, text=True, timeout=5
)
if "loopback" in r.stdout.lower():
result["pw_loopback_available"] = True
result["virtual_soundcard_supported"] = True
except (FileNotFoundError, subprocess.TimeoutExpired):
pass
return result
def _query_audio_hardware() -> dict:
result = {
"has_physical_audio": False,
"audio_devices": [],
}
for probe in ["/proc/asound/cards", "/dev/snd"]:
if Path(probe).exists():
result["has_physical_audio"] = True
break
try:
r = subprocess.run(
["cat", "/proc/asound/cards"],
capture_output=True, text=True, timeout=3
)
if r.returncode == 0:
result["audio_devices"] = [
l.strip() for l in r.stdout.splitlines() if l.strip()
]
except Exception:
pass
return result
def _get_max_sample_rate() -> int:
rates = [44100, 48000, 88200, 96000, 176400, 192000]
for rate in reversed(rates):
try:
r = subprocess.run(
["pw-link", "-o", f"alsa_output.null-@{rate}"],
capture_output=True, timeout=2
)
if r.returncode == 0:
return rate
except Exception:
pass
return 48000
def _read_snd_hw_params() -> int:
hw_params = Path("/proc/asound/card0/hw_params")
if hw_params.exists():
content = hw_params.read_text()
for line in content.splitlines():
if "rate" in line.lower():
parts = line.split()
for i, p in enumerate(parts):
if p.isdigit() and int(p) >= 44100:
return int(p)
return 48000
def register_node(node_id: str) -> dict:
_ensure_db()
pw = _query_pipewire()
hw = _query_audio_hardware()
max_rate = _get_max_sample_rate() if pw["pipewire_available"] else 48000
capabilities = {
"node_id": node_id,
"dsp_available": True,
"pipewire_available": pw["pipewire_available"],
"virtual_soundcard_supported": pw["virtual_soundcard_supported"],
"physical_soundcard": hw["has_physical_audio"],
"max_sample_rate": max_rate,
"spectral_bands": 2048,
"latency_target_us": 5120,
"fft_size": 4096,
"overlap_factor": 0.5,
"last_seen_at": datetime.now(timezone.utc).isoformat(),
}
import sqlite3
conn = sqlite3.connect(DB_PATH)
conn.execute("""
INSERT OR REPLACE INTO ene.dsp_nodes
(node_id, dsp_available, pipewire_available, virtual_soundcard_supported,
physical_soundcard, max_sample_rate, spectral_bands, latency_target_us,
fft_size, overlap_factor, last_seen_at)
VALUES (:node_id, :dsp_available, :pipewire_available,
:virtual_soundcard_supported, :physical_soundcard, :max_sample_rate,
:spectral_bands, :latency_target_us, :fft_size, :overlap_factor,
:last_seen_at)
""", capabilities)
conn.commit()
conn.close()
receipt = {
"schema": "flac_dsp_node_registration_v1",
"version": "1.0.0",
"generated_at_utc": datetime.now(timezone.utc).isoformat(),
"node_id": node_id,
"action": "register",
"capabilities": {k: v for k, v in capabilities.items() if k != "node_id"},
"pipewire_probe": pw,
"hardware_probe": hw,
"claim_boundary": "node-capability-probe-only",
}
_write_receipt(receipt)
return capabilities
def _write_receipt(receipt: dict) -> None:
Path(RECEIPT_LOG).parent.mkdir(parents=True, exist_ok=True)
with open(RECEIPT_LOG, "a") as f:
f.write(json.dumps(receipt) + "\n")
def process_flac_chunk(chunk_path: str, work_unit_id: str, parent_hash: Optional[str] = None) -> dict:
import struct
result = {
"work_unit_id": work_unit_id,
"chunk_path": chunk_path,
"status": "unknown",
"fft_peaks": [],
"spectral_centroid_hz": 0.0,
"rms_level_db": -60.0,
"processing_node": os.environ.get("HOSTNAME", "unknown"),
}
try:
import numpy as np
import soundfile as sf
data, samplerate = sf.read(chunk_path)
if data.ndim > 1:
data = data.mean(axis=1)
n_fft = 4096
hop = n_fft // 2
window = np.hanning(n_fft)
S = []
for i in range(0, len(data) - n_fft, hop):
frame = data[i:i + n_fft] * window
spectrum = np.abs(np.fft.rfft(frame))
S.append(spectrum)
S = np.array(S)
mean_spectrum = S.mean(axis=0)
freqs = np.fft.rfftfreq(n_fft, 1.0 / samplerate)
peak_indices = np.argsort(mean_spectrum)[-8:]
result["fft_peaks"] = [
{"freq_hz": float(freqs[i]), "magnitude": float(mean_spectrum[i])}
for i in sorted(peak_indices)
]
spectral_sum = np.sum(mean_spectrum)
if spectral_sum > 0:
result["spectral_centroid_hz"] = float(
np.sum(freqs * mean_spectrum) / spectral_sum
)
rms = np.sqrt(np.mean(data ** 2))
result["rms_level_db"] = float(20 * np.log10(rms + 1e-12))
result["status"] = "ok"
except ImportError:
result["status"] = "missing_libs"
result["error"] = "numpy or soundfile not available"
except Exception as e:
result["status"] = "error"
result["error"] = str(e)
receipt = {
"schema": "flac_dsp_work_receipt_v1",
"version": "1.0.0",
"generated_at_utc": datetime.now(timezone.utc).isoformat(),
"work_unit_id": work_unit_id,
"parent_hash": parent_hash,
"result": {k: v for k, v in result.items() if k not in ("fft_peaks",)},
"fft_peaks": result["fft_peaks"][:4],
"processing_node": os.environ.get("HOSTNAME", "unknown"),
"claim_boundary": "dsp-compute-result",
}
_write_receipt(receipt)
return result
def main() -> int:
parser = argparse.ArgumentParser(description="FLAC DSP Node — PipeWire/FLAC compute worker")
sub = parser.add_subparsers(dest="cmd", required=True)
reg = sub.add_parser("register", help="Register this node's DSP capabilities")
reg.add_argument("--node-id", required=True, help="Unique node identifier")
proc = sub.add_parser("process", help="Process a FLAC chunk workload")
proc.add_argument("--chunk", required=True, help="Path to FLAC chunk file")
proc.add_argument("--work-unit-id", required=True, help="Work unit identifier")
proc.add_argument("--parent-hash", help="Parent receipt hash for chaining")
args = parser.parse_args()
if args.cmd == "register":
caps = register_node(args.node_id)
print(json.dumps(caps, indent=2))
return 0
if args.cmd == "process":
result = process_flac_chunk(args.chunk, args.work_unit_id, args.parent_hash)
print(json.dumps(result, indent=2))
return 0
return 1
if __name__ == "__main__":
sys.exit(main())