#!/usr/bin/env python3 """ FastAPI backend for Audio Transcription Pipeline. Serves on port 8081 with endpoints for transcription, ASCII viz, and health check. """ import json import logging import os import shutil import tempfile import time from typing import Optional import librosa import uvicorn from fastapi import FastAPI, File, Form, HTTPException, UploadFile from fastapi.middleware.cors import CORSMiddleware from fastapi.responses import JSONResponse, PlainTextResponse logging.basicConfig( level=logging.INFO, format="%(levelname)s:%(name)s:%(message)s", ) logger = logging.getLogger(__name__) # Quiet down libraries logging.getLogger("faster_whisper").setLevel(logging.WARNING) logging.getLogger("transformers").setLevel(logging.WARNING) logging.getLogger("librosa").setLevel(logging.WARNING) logging.getLogger("pipeline").setLevel(logging.WARNING) logging.getLogger("httpx").setLevel(logging.WARNING) app = FastAPI( title="Audio Transcription Pipeline", description="Transcribe, classify, diarize, summarize, and visualize audio", version="1.0.0", ) app.add_middleware( CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) # Lazy-loaded pipeline _pipeline = None def _get_pipeline(): global _pipeline if _pipeline is None: logger.info("Initializing AudioPipeline...") from pipeline.orchestrator import AudioPipeline _pipeline = AudioPipeline( enable_summarizer=True, enable_ascii=False, # ASCII on-demand ) logger.info("AudioPipeline initialized.") return _pipeline def _get_ascii_viz(): """Get AsciiSpectrogram instance (no caching - lightweight).""" from pipeline.ascii_spectrogram import AsciiSpectrogram return AsciiSpectrogram() def _clean_for_json(obj): """Recursively clean for JSON serialization.""" if isinstance(obj, dict): return {k: _clean_for_json(v) for k, v in obj.items() if not k.startswith("_")} elif isinstance(obj, list): return [_clean_for_json(item) for item in obj] elif isinstance(obj, float): if obj != obj: # NaN return None return obj return obj @app.get("/health") async def health_check(): """Health check endpoint.""" return { "status": "ok", "service": "audio-transcription-pipeline", "version": "1.0.0", } @app.post("/transcribe") async def transcribe( file: UploadFile = File(...), language: Optional[str] = Form(None), vad_filter: bool = Form(True), include_ascii: bool = Form(False), include_summary: bool = Form(True), ): """Transcribe an uploaded audio file through the full pipeline.""" start_time = time.time() # Save uploaded file to temp suffix = os.path.splitext(file.filename or "audio.wav")[1] or ".wav" with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp: shutil.copyfileobj(file.file, tmp) tmp_path = tmp.name try: pipe = _get_pipeline() result = pipe.process_file( tmp_path, language=language, vad_filter=vad_filter, ) # Add ASCII if requested if include_ascii: try: audio, sr = librosa.load(tmp_path, sr=16000, mono=True) viz = _get_ascii_viz() frames = [] for frame_text, timestamp in viz.generate_frames(audio, sr, fps=10): frames.append({"timestamp": round(timestamp, 2), "frame": frame_text}) result["ascii_frames"] = frames except Exception as e: logger.warning(f"ASCII viz failed: {e}") result["ascii_frames"] = [] # Add processing time elapsed = time.time() - start_time result.setdefault("metadata", {})["api_processing_time_seconds"] = round(elapsed, 2) clean = _clean_for_json(result) return JSONResponse(content=clean) except Exception as e: logger.exception(f"Transcription failed: {e}") raise HTTPException(status_code=500, detail=str(e)) finally: # Clean up temp file try: os.unlink(tmp_path) except OSError: pass @app.get("/ascii-viz") async def ascii_viz( audio_path: str = Form(...), columns: int = 80, rows: int = 20, fps: int = 10, mode: str = "spectrogram", ): """Generate ASCII spectrogram frames from an audio file path.""" if not os.path.exists(audio_path): raise HTTPException(status_code=404, detail=f"Audio file not found: {audio_path}") try: audio, sr = librosa.load(audio_path, sr=16000, mono=True) viz = _get_ascii_viz() frames = [] for frame_text, timestamp in viz.generate_frames(audio, sr, fps=fps, mode=mode): frames.append({"timestamp": round(timestamp, 2), "frame": frame_text}) return {"frames": frames, "count": len(frames), "duration": round(len(audio) / sr, 2)} except Exception as e: logger.exception(f"ASCII viz failed: {e}") raise HTTPException(status_code=500, detail=str(e)) @app.get("/ascii-viz-file") async def ascii_viz_file( audio_path: str, columns: int = 80, rows: int = 20, fps: int = 10, mode: str = "spectrogram", ): """Generate ASCII spectrogram and return as plain text.""" if not os.path.exists(audio_path): raise HTTPException(status_code=404, detail=f"Audio file not found: {audio_path}") try: audio, sr = librosa.load(audio_path, sr=16000, mono=True) viz = _get_ascii_viz() lines = [] for frame_text, timestamp in viz.generate_frames(audio, sr, fps=fps, mode=mode): lines.append(f"--- Frame @ {timestamp:.1f}s ---") lines.append(frame_text) return PlainTextResponse("\n".join(lines)) except Exception as e: logger.exception(f"ASCII viz failed: {e}") raise HTTPException(status_code=500, detail=str(e)) if __name__ == "__main__": uvicorn.run(app, host="0.0.0.0", port=8081, log_level="info")