361 lines
12 KiB
Python
361 lines
12 KiB
Python
#!/usr/bin/env python3
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"""
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Class recording watcher for Rocinante.
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Watches C:/Recordings (mounted as /recordings) for new .wav files.
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For each file detected:
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1. Waits for the file to finish being written
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2. Converts WAV -> MP3 via ffmpeg (deletes original WAV)
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3. Splits long recordings into 10-minute chunks
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4. Transcribes each chunk via local faster-whisper-server (large-v3, CUDA)
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5. Stitches results back together with corrected timestamps
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6. POSTs transcript + metadata to n8n /webhook/class/ingest
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Folder convention: subfolder name = class name
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/recordings/HIST-2020/lecture-03-3.wav -> class=HIST-2020, title=lecture 03 3
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"""
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import os
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import time
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import subprocess
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import logging
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import requests
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from pathlib import Path
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from watchdog.observers.polling import PollingObserver as Observer
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from watchdog.events import FileSystemEventHandler
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# Config from environment
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WHISPER_URL = os.environ.get("WHISPER_URL", "http://whisper:8000")
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N8N_WEBHOOK = os.environ.get("N8N_WEBHOOK_URL", "https://n8n.paccoco.com/webhook/class/ingest")
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WATCH_DIR = os.environ.get("WATCH_DIR", "/recordings")
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WHISPER_MODEL = os.environ.get("WHISPER_MODEL", "large-v3")
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CHUNK_MINUTES = int(os.environ.get("CHUNK_MINUTES", "10"))
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s %(levelname)-8s %(message)s",
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datefmt="%Y-%m-%d %H:%M:%S",
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)
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log = logging.getLogger("watcher")
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def wait_for_file_stable(path: Path, interval: float = 2.0, required_stable: int = 3) -> None:
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"""Block until the file size stops changing (i.e. the copy is complete)."""
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log.info(f"Waiting for {path.name} to finish writing...")
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prev_size = -1
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stable_count = 0
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while stable_count < required_stable:
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try:
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size = path.stat().st_size
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except FileNotFoundError:
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time.sleep(interval)
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continue
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if size == prev_size and size > 0:
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stable_count += 1
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else:
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stable_count = 0
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prev_size = size
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time.sleep(interval)
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log.info(f"{path.name} is stable ({prev_size:,} bytes)")
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# Extra check: verify the file handle is released and readable
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for attempt in range(60):
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try:
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with open(path, 'rb') as f:
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f.read(1024)
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break
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except (PermissionError, OSError) as e:
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log.info(f"File not yet readable ({e}), retrying... ({attempt + 1}/60)")
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time.sleep(5)
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else:
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raise RuntimeError(f"File {path.name} is not readable after 60 attempts")
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def convert_to_mp3(wav_path: Path) -> Path:
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mp3_path = wav_path.with_suffix(".mp3")
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log.info(f"Converting to MP3: {wav_path.name}")
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result = subprocess.run(
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[
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"ffmpeg", "-y",
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"-i", str(wav_path),
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"-codec:a", "libmp3lame",
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"-qscale:a", "4",
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str(mp3_path),
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],
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capture_output=True,
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text=True,
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)
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if result.returncode != 0:
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raise RuntimeError(f"ffmpeg failed:\n{result.stderr}")
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wav_path.unlink()
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log.info(f"Deleted original WAV: {wav_path.name}")
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return mp3_path
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def get_duration(mp3_path: Path) -> float:
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"""Return audio duration in seconds via ffprobe."""
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result = subprocess.run(
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[
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"ffprobe", "-v", "quiet",
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"-show_entries", "format=duration",
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"-of", "csv=p=0",
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str(mp3_path),
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],
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capture_output=True,
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text=True,
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)
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return float(result.stdout.strip() or "0")
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def split_into_chunks(mp3_path: Path, chunk_minutes: int = CHUNK_MINUTES) -> list:
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"""Split MP3 into chunks. Returns [mp3_path] if short enough."""
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duration = get_duration(mp3_path)
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chunk_secs = chunk_minutes * 60
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if duration <= chunk_secs:
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log.info(f"Recording is {duration/60:.1f}min — no splitting needed")
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return [mp3_path]
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total_chunks = int(duration / chunk_secs) + 1
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log.info(f"Recording is {duration/60:.1f}min — splitting into {total_chunks} x {chunk_minutes}min chunks")
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chunks = []
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start = 0.0
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i = 0
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while start < duration:
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chunk_path = mp3_path.parent / f"{mp3_path.stem}_chunk{i:03d}.mp3"
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subprocess.run(
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[
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"ffmpeg", "-y",
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"-i", str(mp3_path),
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"-ss", str(start),
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"-t", str(chunk_secs),
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"-codec:a", "copy",
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str(chunk_path),
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],
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capture_output=True,
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)
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chunks.append((chunk_path, start))
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start += chunk_secs
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i += 1
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return chunks
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def transcribe_chunk(mp3_path: Path) -> dict:
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with open(mp3_path, "rb") as f:
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resp = requests.post(
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f"{WHISPER_URL}/v1/audio/transcriptions",
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files={"file": (mp3_path.name, f, "audio/mpeg")},
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data={
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"model": WHISPER_MODEL,
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"language": "en",
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"response_format": "verbose_json",
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},
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timeout=3600,
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)
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resp.raise_for_status()
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return resp.json()
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def transcribe(mp3_path: Path) -> dict:
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"""Transcribe an MP3, splitting into chunks if needed."""
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chunks = split_into_chunks(mp3_path)
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# Short recording — single chunk, no splitting
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if len(chunks) == 1 and isinstance(chunks[0], Path):
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log.info(f"Transcribing {mp3_path.name} with {WHISPER_MODEL}...")
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result = transcribe_chunk(mp3_path)
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result["segments"] = deduplicate_hallucinations(result.get("segments", []))
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log.info("Transcription complete")
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return result
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# Long recording — transcribe each chunk and stitch
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all_segments = []
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all_text = []
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for i, (chunk_path, time_offset) in enumerate(chunks):
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log.info(f"Transcribing chunk {i+1}/{len(chunks)}: {chunk_path.name} (offset {time_offset/60:.1f}min)")
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try:
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result = transcribe_chunk(chunk_path)
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segments = result.get("segments", [])
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for s in segments:
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s["start"] = s.get("start", 0) + time_offset
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s["end"] = s.get("end", 0) + time_offset
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all_segments.extend(segments)
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all_text.append(result.get("text", "").strip())
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except Exception as e:
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log.error(f"Chunk {i+1} failed: {e}")
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finally:
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chunk_path.unlink(missing_ok=True)
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all_segments = deduplicate_hallucinations(all_segments)
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total_duration = get_duration(mp3_path)
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log.info(f"Transcription complete — {len(chunks)} chunks stitched")
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return {
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"text": " ".join(all_text),
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"segments": all_segments,
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"duration": total_duration,
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}
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def is_silence(text: str) -> bool:
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"""Return True if the segment is just silence/noise markers."""
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stripped = text.strip()
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return not stripped or all(c in '.…♪ \t' for c in stripped)
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def deduplicate_hallucinations(segments: list, max_repeats: int = 3) -> list:
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"""
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Remove Whisper phrase-loop hallucinations.
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When Whisper gets stuck it emits the same segment text hundreds of times
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in a row (e.g. "I'm also a software engineer." × 200). This function
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collapses any run longer than `max_repeats` down to at most `max_repeats`
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occurrences and logs a warning so the truncation is visible in the logs.
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"""
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if not segments:
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return segments
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result = []
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i = 0
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while i < len(segments):
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text = segments[i].get("text", "").strip().lower()
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j = i + 1
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while j < len(segments) and segments[j].get("text", "").strip().lower() == text:
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j += 1
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count = j - i
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if count > max_repeats:
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log.warning(
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f"Hallucination detected: '{segments[i].get('text', '').strip()[:60]}'"
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f" × {count} — keeping {max_repeats}, dropping {count - max_repeats}"
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)
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result.extend(segments[i : i + max_repeats])
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else:
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result.extend(segments[i:j])
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i = j
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return result
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def build_timestamped(segments: list) -> str:
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lines = []
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for s in segments:
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text = s.get('text', '').strip()
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if is_silence(text):
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continue
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mins = int(s.get("start", 0) // 60)
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secs = int(s.get("start", 0) % 60)
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lines.append(f"[{mins}:{secs:02d}] {text}")
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return "\n".join(lines)
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def send_to_n8n(class_name: str, lecture_title: str, result: dict) -> None:
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segments = result.get("segments", [])
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# Filter silence from full text
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meaningful = [s.get("text", "") for s in segments if not is_silence(s.get("text", ""))]
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full_text = " ".join(meaningful).strip() or result.get("text", "").strip()
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duration = result.get("duration") or (segments[-1].get("end", 0) if segments else 0)
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payload = {
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"class_name": class_name,
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"lecture_title": lecture_title,
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"transcript": full_text,
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"timestamped_transcript": build_timestamped(segments),
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"duration_seconds": duration,
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}
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log.info(f"Sending to n8n: {class_name} / {lecture_title} ({len(full_text)} chars)")
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resp = requests.post(N8N_WEBHOOK, json=payload, timeout=300)
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resp.raise_for_status()
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log.info(f"n8n accepted — HTTP {resp.status_code}")
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# ---------------------------------------------------------------------------
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# Processing pipeline
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# ---------------------------------------------------------------------------
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def process_wav(wav_path: Path) -> None:
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# Must be inside a class subfolder, not the root recordings dir
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if wav_path.parent == Path(WATCH_DIR):
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log.warning(f"Skipping {wav_path.name} — drop files into a class subfolder, e.g. /recordings/HIST-2020/")
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return
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class_name = wav_path.parent.name
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lecture_title = wav_path.stem.replace("-", " ").replace("_", " ")
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log.info(f"--- Processing: {class_name} / {lecture_title} ---")
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wait_for_file_stable(wav_path)
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mp3_path = convert_to_mp3(wav_path)
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result = transcribe(mp3_path)
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send_to_n8n(class_name, lecture_title, result)
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log.info(f"--- Done: {class_name} / {lecture_title} ---")
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# ---------------------------------------------------------------------------
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# Watchdog handler
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# ---------------------------------------------------------------------------
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class WavHandler(FileSystemEventHandler):
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def on_created(self, event):
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if event.is_directory:
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return
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path = Path(event.src_path)
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if path.suffix.lower() == ".wav":
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log.info(f"Detected new WAV: {path}")
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try:
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process_wav(path)
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except Exception as exc:
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log.error(f"Failed to process {path}: {exc}", exc_info=True)
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# ---------------------------------------------------------------------------
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# Entry point
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# ---------------------------------------------------------------------------
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def scan_existing(watch_dir: Path) -> None:
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"""Process any .wav files already present at startup."""
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existing = list(watch_dir.rglob("*.wav")) + list(watch_dir.rglob("*.WAV"))
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if not existing:
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return
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log.info(f"Found {len(existing)} existing WAV(s) at startup — processing...")
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for wav in existing:
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try:
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process_wav(wav)
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except Exception as exc:
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log.error(f"Failed to process {wav}: {exc}", exc_info=True)
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if __name__ == "__main__":
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watch_dir = Path(WATCH_DIR)
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watch_dir.mkdir(parents=True, exist_ok=True)
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log.info(f"Whisper URL : {WHISPER_URL}")
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log.info(f"n8n webhook : {N8N_WEBHOOK}")
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log.info(f"Watching : {watch_dir} (recursive)")
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# Process any WAVs already sitting in the folder
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scan_existing(watch_dir)
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observer = Observer()
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observer.schedule(WavHandler(), str(watch_dir), recursive=True)
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observer.start()
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log.info("Watcher started — drop a .wav into a class subfolder to begin")
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try:
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while True:
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time.sleep(1)
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except KeyboardInterrupt:
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pass
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finally:
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observer.stop()
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observer.join()
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log.info("Watcher stopped")
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