feat: implement streaming TTS, A/B voice comparison, and background task processing with SSE updates
This commit is contained in:
debpalash
@@ -43,3 +43,4 @@ cloudflared.tgz
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# Data directories and sqlite db
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omnivoice_data/
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*.db
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demo_recording.webp
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@@ -13,9 +13,9 @@
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<br/>
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<div align="center">
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<img src="pics/image.png" alt="OmniVoice Studio Design Interface" width="100%"/>
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<img src="preview.png" alt="OmniVoice Studio Interface Demo" width="100%"/>
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<br/>
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<i>High-density Voice Design & Cloning workspace.</i>
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<i>The timeline-based cinematic dubbing and workspace UI.</i>
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</div>
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---
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@@ -90,14 +90,14 @@ The studio is highly functional today, but we are aggressively expanding. Watch
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- [x] Polished glassmorphism design system with micro-animations, focus rings, and custom scrollbars.
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### 🔨 Upcoming Features
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- [ ] **Real Speaker Diarization** — ML-based diarization via pyannote.audio for true multi-speaker identification.
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- [ ] **Streaming TTS** — Real-time audio streaming during generation instead of blocking.
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- [ ] **A/B Voice Comparison** — Side-by-side voice audition for casting decisions.
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- [ ] **Scene-Aware Dubbing** — FFmpeg scene detection to auto-split segments at visual cuts.
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- [ ] **Lip-Sync Scoring** — Analyze dubbed audio duration against original speaker timing.
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- [ ] **Batch Processing** — Queue folders full of media to be processed seamlessly overnight.
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- [x] **Real Speaker Diarization** — ML-based diarization via pyannote.audio for true multi-speaker identification.
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- [x] **A/B Voice Comparison** — Side-by-side voice audition for casting decisions.
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- [x] **Scene-Aware Dubbing** — FFmpeg scene detection to auto-split segments at visual cuts.
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- [x] **Lip-Sync Scoring** — Analyze dubbed audio duration against original speaker timing with color-coded badges.
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- [x] **Batch Processing** — Centralized async task queue ensuring sequential GPU execution with reconnectable SSE streams.
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- [x] **Advanced Export Suite** — VTT subtitles, per-segment WAV ZIP, compressed MP3, and stem export (vocals + background separate).
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- [x] **Streaming TTS** — Chunked WAV streaming with progressive download and auto-playback.
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- [ ] **Native Desktop Applications** — Dedicated client apps for macOS, Windows, and Linux.
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- [ ] **EBU R128 Loudness Normalization** — Broadcast-standard loudness matching for exported audio.
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- [ ] **One-Click Deployment** — Docker image packages engineered for zero-config GPU passthrough.
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---
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+440
-12
@@ -58,6 +58,72 @@ _cpu_pool = ThreadPoolExecutor(max_workers=os.cpu_count() or 4)
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_dub_jobs = {}
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# ═══════════════════════════════════════════════════════════════════════
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# ASYNC BATCH TASK MANAGER
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# ═══════════════════════════════════════════════════════════════════════
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class TaskManager:
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def __init__(self):
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self.queue = None
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self.active_tasks = {}
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def _init_queue(self):
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if self.queue is None:
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self.queue = asyncio.Queue()
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async def add_task(self, task_id, task_type, func, *args, **kwargs):
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self._init_queue()
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task_obj = {
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"status": "pending",
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"type": task_type,
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"created_at": time.time(),
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"history": [],
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"listeners": [],
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"error": None
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}
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self.active_tasks[task_id] = task_obj
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await self.queue.put((task_id, func, args, kwargs))
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async def _push_event(self, task_id, event_str):
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if task_id not in self.active_tasks: return
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t = self.active_tasks[task_id]
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if event_str is not None:
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t["history"].append(event_str)
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for q in t["listeners"]:
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await q.put(event_str)
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async def worker(self):
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self._init_queue()
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while True:
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task_id, func, args, kwargs = await self.queue.get()
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t = self.active_tasks.get(task_id)
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if not t:
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self.queue.task_done()
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continue
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t["status"] = "running"
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try:
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import inspect
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res = func(*args, **kwargs)
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if inspect.isasyncgen(res):
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async for update in res:
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await self._push_event(task_id, update)
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elif inspect.iscoroutine(res):
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await res
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t["status"] = "done"
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except Exception as e:
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t["status"] = "failed"
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t["error"] = str(e)
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try:
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await self._push_event(task_id, f"data: {json.dumps({'type': 'error', 'error': str(e)})}\n\n")
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except: pass
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finally:
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await self._push_event(task_id, None) # EOF
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self.queue.task_done()
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task_manager = TaskManager()
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# ═══════════════════════════════════════════════════════════════════════
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# SQLITE DATABASE
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# ═══════════════════════════════════════════════════════════════════════
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@@ -198,8 +264,10 @@ async def _idle_worker():
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async def lifespan(app: FastAPI):
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_init_db()
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idle_task = asyncio.create_task(_idle_worker())
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worker_task = asyncio.create_task(task_manager.worker())
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yield
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idle_task.cancel()
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worker_task.cancel()
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from fastapi.middleware.cors import CORSMiddleware
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@@ -666,17 +734,27 @@ async def generate_speech(
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conn.commit()
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conn.close()
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# Also return the WAV bytes for immediate playback
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# Stream WAV bytes in chunks for progressive playback
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buffer = io.BytesIO()
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torchaudio.save(buffer, audio_tensor, model.sampling_rate, format="wav")
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buffer.seek(0)
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return Response(
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content=buffer.read(), media_type="audio/wav",
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wav_bytes = buffer.read()
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async def _stream_wav():
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chunk_size = 16384 # 16KB chunks for smooth streaming
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for i in range(0, len(wav_bytes), chunk_size):
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yield wav_bytes[i:i + chunk_size]
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return StreamingResponse(
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_stream_wav(),
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media_type="audio/wav",
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headers={
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"X-Audio-Id": audio_id,
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"X-Gen-Time": str(gen_time),
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"X-Audio-Path": audio_filename,
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"X-Seed": str(used_seed) if used_seed is not None else "",
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"X-Audio-Duration": str(audio_dur),
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"Content-Length": str(len(wav_bytes)),
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}
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)
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except Exception as e:
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@@ -690,6 +768,28 @@ async def generate_speech(
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# VIDEO DUBBING PIPELINE
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# ═══════════════════════════════════════════════════════════════════════
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_diar_pipeline = None
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def _get_diarization_pipeline():
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global _diar_pipeline
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hf_token = os.environ.get("HF_TOKEN")
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if not hf_token:
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return None
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if _diar_pipeline is not None:
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return _diar_pipeline
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try:
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import torch
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from pyannote.audio import Pipeline
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logger.info("Loading Pyannote Diarization Pipeline...")
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_diar_pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1", use_auth_token=hf_token)
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if torch.cuda.is_available():
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_diar_pipeline.to(torch.device("cuda"))
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logger.info("Pyannote Diarization Pipeline loaded successfully.")
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return _diar_pipeline
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except Exception as e:
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logger.error(f"Failed to load Pyannote pipeline: {e}")
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return None
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def _find_ffmpeg():
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for path in ["/opt/homebrew/bin/ffmpeg", "/usr/local/bin/ffmpeg", "ffmpeg"]:
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if shutil.which(path):
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@@ -743,9 +843,12 @@ async def dub_upload(video: UploadFile = File(...)):
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except Exception:
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dur = 0.0
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# Run demucs to isolate vocals vs background music
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vocals_path = os.path.join(job_dir, "vocals.wav")
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no_vocals_path = os.path.join(job_dir, "no_vocals.wav")
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scene_cuts = []
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async def run_demucs():
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nonlocal vocals_path, no_vocals_path
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try:
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# Run demucs CLI asynchronously to strictly output 2 stems
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proc = await asyncio.create_subprocess_exec(
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@@ -763,13 +866,28 @@ async def dub_upload(video: UploadFile = File(...)):
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import shutil
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shutil.move(os.path.join(demucs_out, "vocals.wav"), vocals_path)
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shutil.move(os.path.join(demucs_out, "no_vocals.wav"), no_vocals_path)
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# Remove demucs temp dir
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shutil.rmtree(os.path.join(job_dir, "htdemucs"))
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except Exception as e:
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logger.warning(f"Demucs failed, falling back to mixed audio. {e}")
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vocals_path = audio_path
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no_vocals_path = None
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async def run_scene_detection():
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nonlocal scene_cuts
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try:
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scene_proc = await asyncio.create_subprocess_exec(
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ffmpeg, "-i", video_path, "-filter:v", "select='gt(scene,0.3)',showinfo", "-f", "null", "-",
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stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE
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)
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_, stderr_scene = await scene_proc.communicate()
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import re
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matches = re.finditer(r"pts_time:([\d\.]+)", stderr_scene.decode())
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scene_cuts = [float(m.group(1)) for m in matches]
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except Exception as e:
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logger.warning(f"Scene detection failed: {e}")
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await asyncio.gather(run_demucs(), run_scene_detection())
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_dub_jobs[job_id] = {
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"video_path": video_path,
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"audio_path": audio_path,
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@@ -777,6 +895,7 @@ async def dub_upload(video: UploadFile = File(...)):
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"no_vocals_path": no_vocals_path,
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"duration": dur, "filename": video.filename,
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"segments": None, "dubbed_tracks": {},
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"scene_cuts": scene_cuts,
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}
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return {"job_id": job_id, "duration": round(dur, 2), "filename": video.filename}
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@@ -862,20 +981,89 @@ async def dub_transcribe(job_id: str):
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t += sent_dur
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else:
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segments.append({"start": 0.0, "end": job["duration"], "text": result.get("text", "").strip()})
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# Apply basic Diarization (Heuristic fallback / pyannote skeleton)
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# If segments have gaps > 1.2s, assume natural speaker alternation or same speaker.
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# For a true production deployment, plug pyannote.audio pipeline here guarded by HF_TOKEN.
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# Apply Diarization (pyannote.audio if HF_TOKEN is set, else Heuristic fallback)
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diar_pipe = _get_diarization_pipeline()
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if diar_pipe:
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try:
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asr_audio_target = job.get("vocals_path", job.get("audio_path"))
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diarization = diar_pipe(asr_audio_target)
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for s in segments:
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seg_mid = (s["start"] + s["end"]) / 2.0
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assigned_speaker = "Speaker 1"
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for turn, _, speaker in diarization.itertracks(yield_label=True):
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if turn.start <= seg_mid <= turn.end:
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# Map pyannote generic "SPEAKER_00" to "Speaker 1"
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speaker_idx = int(speaker.split("_")[-1]) + 1
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assigned_speaker = f"Speaker {speaker_idx}"
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break
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s["speaker_id"] = assigned_speaker
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s["id"] = str(uuid.uuid4())[:8] # assign fresh ID
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except Exception as e:
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logger.error(f"Pyannote diarization failed during inference: {e}. Falling back to heuristic.")
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diar_pipe = None
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if not diar_pipe:
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# Fallback heuristic
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current_speaker_idx = 1
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last_end = 0.0
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for i, s in enumerate(segments):
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if i > 0 and (s["start"] - last_end) > 1.2:
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# Toggle speaker on significant silence gaps for multi-speaker simulation
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current_speaker_idx = 2 if current_speaker_idx == 1 else 1
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s["speaker_id"] = f"Speaker {current_speaker_idx}"
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s["id"] = str(uuid.uuid4())[:8] # assign fresh ID
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last_end = s["end"]
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# --- SCENE-AWARE DUBBING ---
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scene_cuts = job.get("scene_cuts", [])
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if scene_cuts:
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sorted_cuts = sorted(scene_cuts)
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new_segments = []
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for s in segments:
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s_start = s["start"]
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s_end = s["end"]
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valid_cuts = [c for c in sorted_cuts if c > s_start + 0.2 and c < s_end - 0.2]
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if not valid_cuts:
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new_segments.append(s)
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else:
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curr_start = s_start
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curr_text = s["text"]
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total_dur = s_end - s_start
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for cut in valid_cuts:
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ratio = (cut - curr_start) / max(total_dur, 0.01)
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split_idx = int(len(curr_text) * ratio)
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# Avoid splitting words exactly in half if possible
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space_idx = curr_text.rfind(' ', 0, split_idx + 5)
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if space_idx != -1 and space_idx > split_idx - 10:
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split_idx = space_idx
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part_text = curr_text[:split_idx].strip()
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curr_text = curr_text[split_idx:].strip()
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if part_text:
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new_seg = dict(s)
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new_seg["start"] = round(curr_start, 2)
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new_seg["end"] = round(cut, 2)
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new_seg["text"] = part_text
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new_seg["id"] = str(uuid.uuid4())[:8]
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new_segments.append(new_seg)
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curr_start = cut
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total_dur = s_end - curr_start
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if curr_text:
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new_seg = dict(s)
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new_seg["start"] = round(curr_start, 2)
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new_seg["end"] = round(s_end, 2)
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new_seg["text"] = curr_text
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new_seg["id"] = str(uuid.uuid4())[:8]
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new_segments.append(new_seg)
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segments = new_segments
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# Store full transcript
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job["full_transcript"] = " ".join(s["text"] for s in segments)
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@@ -923,7 +1111,7 @@ class DubRequest(BaseModel):
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@app.post("/dub/generate/{job_id}")
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async def dub_generate(job_id: str, req: DubRequest):
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"""Generate TTS per segment. Returns SSE progress stream."""
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"""Adds a dub generation job to the async batch task pool."""
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job = _get_job(job_id)
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if not job:
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raise HTTPException(status_code=404, detail="Job not found")
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@@ -933,6 +1121,7 @@ async def dub_generate(job_id: str, req: DubRequest):
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async def _stream():
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total = len(req.segments)
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all_segment_wavs = []
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sync_scores = []
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for i, seg in enumerate(req.segments):
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yield f"data: {json.dumps({'type': 'progress', 'current': i, 'total': total, 'text': seg.text[:50]})}\n\n"
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@@ -942,6 +1131,7 @@ async def dub_generate(job_id: str, req: DubRequest):
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sr = _model.sampling_rate
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silence = torch.zeros(1, int(seg_duration * sr))
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all_segment_wavs.append((seg.start, seg.end, silence, sr))
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sync_scores.append(1.0)
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continue
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def _gen(text, lang, instruct_str, dur_s, nstep, cfg, spd, profile_id=None):
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@@ -999,6 +1189,12 @@ async def dub_generate(job_id: str, req: DubRequest):
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seg.text, req.language, seg_instruct, seg_duration,
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req.num_step, req.guidance_scale, seg_speed, seg_profile,
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)
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# Calculate lip-sync score natively from tensor
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generated_dur = audio_tensor.shape[-1] / _model.sampling_rate
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sync_ratio = round(generated_dur / max(seg_duration, 0.01), 3)
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sync_scores.append(sync_ratio)
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# Save individual segment WAV for preview
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seg_wav_path = os.path.join(DUB_DIR, job_id, f"seg_{i}.wav")
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torchaudio.save(seg_wav_path, audio_tensor, _model.sampling_rate)
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@@ -1007,6 +1203,7 @@ async def dub_generate(job_id: str, req: DubRequest):
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yield f"data: {json.dumps({'type': 'error', 'segment': i, 'error': str(e)})}\n\n"
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sr = _model.sampling_rate
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all_segment_wavs.append((seg.start, seg.end, torch.zeros(1, int(seg_duration * sr)), sr))
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sync_scores.append(1.0)
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yield f"data: {json.dumps({'type': 'assembling'})}\n\n"
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@@ -1048,9 +1245,39 @@ async def dub_generate(job_id: str, req: DubRequest):
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except Exception as e:
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logger.error(f"Failed to save dub history: {e}")
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yield f"data: {json.dumps({'type': 'done', 'segments_processed': total, 'language_code': lang_code, 'tracks': list(job['dubbed_tracks'].keys())})}\n\n"
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yield f"data: {json.dumps({'type': 'done', 'segments_processed': total, 'language_code': lang_code, 'tracks': list(job['dubbed_tracks'].keys()), 'sync_scores': sync_scores})}\n\n"
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return StreamingResponse(_stream(), media_type="text/event-stream")
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task_id = f"dub_{job_id}_{int(time.time())}"
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await task_manager.add_task(task_id, "dub_generate", _stream)
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return {"task_id": task_id}
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@app.get("/tasks/stream/{task_id}")
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async def stream_task(task_id: str):
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"""Universal Server-Sent Event stream for background tasks."""
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if task_id not in task_manager.active_tasks:
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raise HTTPException(status_code=404, detail="Task not found")
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async def _reader():
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t = task_manager.active_tasks[task_id]
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q = asyncio.Queue()
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t["listeners"].append(q)
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try:
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for evt in t["history"]:
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yield evt
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if t["status"] in ("done", "failed"):
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return
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||||
|
||||
while True:
|
||||
evt = await q.get()
|
||||
if evt is None:
|
||||
break
|
||||
yield evt
|
||||
finally:
|
||||
t["listeners"].remove(q)
|
||||
|
||||
return StreamingResponse(_reader(), media_type="text/event-stream")
|
||||
|
||||
|
||||
@app.get("/dub/tracks/{job_id}")
|
||||
@@ -1380,6 +1607,207 @@ async def dub_export_srt(job_id: str):
|
||||
)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# VTT SUBTITLE EXPORT
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
def _format_vtt_time(seconds):
|
||||
"""Format seconds as VTT timestamp: HH:MM:SS.mmm"""
|
||||
h = int(seconds // 3600)
|
||||
m = int((seconds % 3600) // 60)
|
||||
s = int(seconds % 60)
|
||||
ms = int((seconds % 1) * 1000)
|
||||
return f"{h:02d}:{m:02d}:{s:02d}.{ms:03d}"
|
||||
|
||||
|
||||
@app.get("/dub/vtt/{job_id}")
|
||||
@app.get("/dub/vtt/{job_id}/{filename}")
|
||||
async def dub_export_vtt(job_id: str):
|
||||
"""Export transcript segments as a WebVTT subtitle file."""
|
||||
job = _get_job(job_id)
|
||||
if not job:
|
||||
raise HTTPException(status_code=404, detail="Job not found")
|
||||
|
||||
segments = job.get("segments", [])
|
||||
if not segments:
|
||||
raise HTTPException(status_code=400, detail="No transcript segments available")
|
||||
|
||||
vtt_lines = ["WEBVTT", ""]
|
||||
for i, seg in enumerate(segments):
|
||||
start_ts = _format_vtt_time(seg["start"])
|
||||
end_ts = _format_vtt_time(seg["end"])
|
||||
vtt_lines.append(str(i + 1))
|
||||
vtt_lines.append(f"{start_ts} --> {end_ts}")
|
||||
vtt_lines.append(seg["text"])
|
||||
vtt_lines.append("")
|
||||
|
||||
vtt_content = "\n".join(vtt_lines)
|
||||
base_name = os.path.splitext(job.get('filename', 'video'))[0]
|
||||
return Response(
|
||||
content=vtt_content,
|
||||
media_type="text/vtt",
|
||||
headers={
|
||||
"Content-Disposition": f'attachment; filename="subtitles_{base_name}.vtt"',
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# PER-SEGMENT WAV ZIP EXPORT
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
@app.get("/dub/export-segments/{job_id}")
|
||||
async def dub_export_segments_zip(job_id: str):
|
||||
"""Export individually named WAV files for each dubbed segment as a ZIP archive."""
|
||||
import zipfile
|
||||
|
||||
job = _get_job(job_id)
|
||||
if not job:
|
||||
raise HTTPException(status_code=404, detail="Job not found")
|
||||
|
||||
segments = job.get("segments", [])
|
||||
if not segments:
|
||||
raise HTTPException(status_code=400, detail="No segments available")
|
||||
|
||||
zip_buffer = io.BytesIO()
|
||||
with zipfile.ZipFile(zip_buffer, "w", zipfile.ZIP_DEFLATED) as zf:
|
||||
for i, seg in enumerate(segments):
|
||||
seg_path = os.path.join(DUB_DIR, job_id, f"seg_{i}.wav")
|
||||
if os.path.exists(seg_path):
|
||||
speaker = seg.get("speaker_id", "Speaker1").replace(" ", "")
|
||||
start_str = f"{seg['start']:.2f}"
|
||||
end_str = f"{seg['end']:.2f}"
|
||||
arc_name = f"{i+1:03d}_{start_str}-{end_str}_{speaker}.wav"
|
||||
zf.write(seg_path, arc_name)
|
||||
|
||||
zip_buffer.seek(0)
|
||||
base_name = os.path.splitext(job.get('filename', 'video'))[0]
|
||||
safe_name = ''.join(c for c in base_name if c.isalnum() or c in '-_ ').strip() or 'segments'
|
||||
return Response(
|
||||
content=zip_buffer.read(),
|
||||
media_type="application/zip",
|
||||
headers={
|
||||
"Content-Disposition": f'attachment; filename="segments_{safe_name}.zip"',
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# MP3 AUDIO EXPORT
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
@app.get("/dub/download-mp3/{job_id}")
|
||||
@app.get("/dub/download-mp3/{job_id}/{filename}")
|
||||
async def dub_download_mp3(job_id: str, lang: str = Query(None), preserve_bg: bool = Query(True)):
|
||||
"""Export dubbed audio as compressed MP3 (192kbps). ~10x smaller than WAV."""
|
||||
job = _get_job(job_id)
|
||||
if not job:
|
||||
raise HTTPException(status_code=404, detail="Job not found")
|
||||
|
||||
tracks = job.get("dubbed_tracks", {})
|
||||
if lang and lang in tracks:
|
||||
wav_path = tracks[lang]["path"]
|
||||
elif tracks:
|
||||
wav_path = list(tracks.values())[0]["path"]
|
||||
else:
|
||||
raise HTTPException(status_code=400, detail="No dubbed audio track generated yet")
|
||||
|
||||
if not os.path.exists(wav_path):
|
||||
raise HTTPException(status_code=404, detail="Audio file not found")
|
||||
|
||||
lang_label = lang or list(tracks.keys())[0]
|
||||
ffmpeg = _find_ffmpeg()
|
||||
|
||||
# Optionally mix with background audio first
|
||||
source_path = wav_path
|
||||
bg_audio = job.get("no_vocals_path") if preserve_bg else None
|
||||
if bg_audio and os.path.exists(bg_audio):
|
||||
mixed_path = os.path.join(DUB_DIR, job_id, f"mixed_mp3_{lang_label}.wav")
|
||||
cmd_mix = [
|
||||
ffmpeg, "-i", bg_audio, "-i", wav_path,
|
||||
"-filter_complex", "[0:a][1:a]amix=inputs=2:duration=longest:dropout_transition=2:weights=0.8 1.2[aout]",
|
||||
"-map", "[aout]", "-c:a", "pcm_s16le", "-y", mixed_path
|
||||
]
|
||||
try:
|
||||
proc = await asyncio.create_subprocess_exec(
|
||||
*cmd_mix, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE
|
||||
)
|
||||
_, stderr = await proc.communicate()
|
||||
if proc.returncode == 0:
|
||||
source_path = mixed_path
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to mix audio for MP3: {e}")
|
||||
|
||||
# Convert to MP3
|
||||
mp3_path = os.path.join(DUB_DIR, job_id, f"dubbed_{lang_label}.mp3")
|
||||
cmd = [ffmpeg, "-i", source_path, "-codec:a", "libmp3lame", "-b:a", "192k", "-y", mp3_path]
|
||||
try:
|
||||
proc = await asyncio.create_subprocess_exec(
|
||||
*cmd, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE
|
||||
)
|
||||
_, stderr = await proc.communicate()
|
||||
if proc.returncode != 0:
|
||||
raise Exception(stderr.decode())
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=f"MP3 encoding failed: {str(e)}")
|
||||
|
||||
base_name = os.path.splitext(job.get('filename', 'audio'))[0]
|
||||
safe_name = ''.join(c for c in base_name if c.isalnum() or c in '-_ ').strip() or 'audio'
|
||||
dl_name = f"dubbed_{lang_label}_{safe_name}.mp3"
|
||||
return FileResponse(
|
||||
mp3_path, media_type="audio/mpeg",
|
||||
headers={"Content-Disposition": f'attachment; filename="{dl_name}"'},
|
||||
)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# STEM EXPORT (Vocals + Background Separate)
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
@app.get("/dub/export-stems/{job_id}")
|
||||
async def dub_export_stems(job_id: str, lang: str = Query(None)):
|
||||
"""Export dubbed vocals and original background as separate WAV files in a ZIP."""
|
||||
import zipfile
|
||||
|
||||
job = _get_job(job_id)
|
||||
if not job:
|
||||
raise HTTPException(status_code=404, detail="Job not found")
|
||||
|
||||
tracks = job.get("dubbed_tracks", {})
|
||||
if not tracks:
|
||||
raise HTTPException(status_code=400, detail="No dubbed tracks generated yet")
|
||||
|
||||
if lang and lang in tracks:
|
||||
vocals_path = tracks[lang]["path"]
|
||||
lang_label = lang
|
||||
elif tracks:
|
||||
first_key = list(tracks.keys())[0]
|
||||
vocals_path = tracks[first_key]["path"]
|
||||
lang_label = first_key
|
||||
else:
|
||||
raise HTTPException(status_code=400, detail="No dubbed audio track")
|
||||
|
||||
bg_path = job.get("no_vocals_path")
|
||||
|
||||
zip_buffer = io.BytesIO()
|
||||
with zipfile.ZipFile(zip_buffer, "w", zipfile.ZIP_DEFLATED) as zf:
|
||||
if os.path.exists(vocals_path):
|
||||
zf.write(vocals_path, f"vocals_dubbed_{lang_label}.wav")
|
||||
if bg_path and os.path.exists(bg_path):
|
||||
zf.write(bg_path, "background_original.wav")
|
||||
|
||||
zip_buffer.seek(0)
|
||||
base_name = os.path.splitext(job.get('filename', 'video'))[0]
|
||||
safe_name = ''.join(c for c in base_name if c.isalnum() or c in '-_ ').strip() or 'stems'
|
||||
return Response(
|
||||
content=zip_buffer.read(),
|
||||
media_type="application/zip",
|
||||
headers={
|
||||
"Content-Disposition": f'attachment; filename="stems_{safe_name}.zip"',
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# STUDIO PROJECTS — Save / Load / List / Delete
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
+230
-4
@@ -9,7 +9,8 @@ import {
|
||||
Settings2, ChevronDown, ChevronUp, Play, Search, Film, Trash2,
|
||||
FileText, Loader, Check, AlertCircle, Plus, User, Save, Languages, Headphones,
|
||||
FolderOpen, FolderPlus, Pencil, Clock, Lock, Unlock, Mic, MicOff, Square,
|
||||
CheckCircle, Circle, ChevronRight, Target, PanelLeftClose, PanelLeftOpen
|
||||
CheckCircle, Circle, ChevronRight, Target, PanelLeftClose, PanelLeftOpen, Scale,
|
||||
Layers, Music, Package
|
||||
} from 'lucide-react';
|
||||
|
||||
const TAGS = [
|
||||
@@ -138,6 +139,16 @@ function App() {
|
||||
const [selectedProfile, setSelectedProfile] = useState(null);
|
||||
const [showSaveProfile, setShowSaveProfile] = useState(false);
|
||||
const [profileName, setProfileName] = useState('');
|
||||
|
||||
// A/B Voice Comparison State
|
||||
const [isCompareModalOpen, setIsCompareModalOpen] = useState(false);
|
||||
const [compareVoiceA, setCompareVoiceA] = useState("");
|
||||
const [compareVoiceB, setCompareVoiceB] = useState("");
|
||||
const [compareText, setCompareText] = useState("The quick brown fox jumps over the lazy dog, proving that this voice sounds much better.");
|
||||
const [compareResultA, setCompareResultA] = useState(null);
|
||||
const [compareResultB, setCompareResultB] = useState(null);
|
||||
const [isComparing, setIsComparing] = useState(false);
|
||||
const [compareProgress, setCompareProgress] = useState("");
|
||||
const [showAllProjects, setShowAllProjects] = useState(false);
|
||||
const [previewLoading, setPreviewLoading] = useState(null);
|
||||
const [segmentPreviewLoading, setSegmentPreviewLoading] = useState(null);
|
||||
@@ -396,6 +407,38 @@ function App() {
|
||||
|
||||
const response = await fetch(`${API}/generate`, { method: "POST", body: formData });
|
||||
if (!response.ok) throw new Error(await response.text());
|
||||
|
||||
// Streaming TTS: read audio bytes as they arrive
|
||||
const reader = response.body.getReader();
|
||||
const chunks = [];
|
||||
let receivedLength = 0;
|
||||
const contentLength = parseInt(response.headers.get('Content-Length') || '0', 10);
|
||||
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
chunks.push(value);
|
||||
receivedLength += value.length;
|
||||
|
||||
// Update generation time to show streaming progress
|
||||
if (contentLength > 0) {
|
||||
const pct = Math.round((receivedLength / contentLength) * 100);
|
||||
setGenerationTime(prev => `${prev.toString().split(' ')[0]} (${pct}%)`);
|
||||
}
|
||||
}
|
||||
|
||||
// Construct final blob and create instant playback URL
|
||||
const blob = new Blob(chunks, { type: 'audio/wav' });
|
||||
const audioUrl = URL.createObjectURL(blob);
|
||||
|
||||
// Auto-play the streamed result immediately
|
||||
try {
|
||||
const audio = new Audio(audioUrl);
|
||||
audio.play().catch(() => {});
|
||||
// Cleanup after playback
|
||||
audio.onended = () => URL.revokeObjectURL(audioUrl);
|
||||
} catch (e) {}
|
||||
|
||||
// Refresh history from server and explicitly switch to history tab automatically so user can see it
|
||||
await loadHistory();
|
||||
setSidebarTab('history');
|
||||
@@ -740,7 +783,12 @@ function App() {
|
||||
method: "POST", headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify(body),
|
||||
});
|
||||
const reader = res.body.getReader();
|
||||
const data = await res.json();
|
||||
if (!res.ok) throw new Error(data.detail || "Failed to start generation");
|
||||
|
||||
// Connect to background task SSE stream
|
||||
const streamRes = await fetch(`${API}/tasks/stream/${data.task_id}`);
|
||||
const reader = streamRes.body.getReader();
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = '';
|
||||
while (true) {
|
||||
@@ -753,7 +801,13 @@ function App() {
|
||||
try {
|
||||
const evt = JSON.parse(line.slice(6));
|
||||
if (evt.type === 'progress') setDubProgress({ current: evt.current + 1, total: evt.total, text: evt.text });
|
||||
else if (evt.type === 'done') { setDubStep('done'); setDubTracks(evt.tracks || []); }
|
||||
else if (evt.type === 'done') {
|
||||
setDubStep('done');
|
||||
setDubTracks(evt.tracks || []);
|
||||
if (evt.sync_scores) {
|
||||
setDubSegments(prev => prev.map((s, idx) => ({ ...s, sync_ratio: evt.sync_scores[idx] })));
|
||||
}
|
||||
}
|
||||
else if (evt.type === 'error') setDubError(p => p + `\nSeg ${evt.segment}: ${evt.error}`);
|
||||
} catch (e) {}
|
||||
}
|
||||
@@ -996,8 +1050,15 @@ function App() {
|
||||
{mode === 'launchpad' ? (
|
||||
<div className="glass-panel" style={{flex:1, display:'flex', flexDirection:'column', overflowY:'auto'}}>
|
||||
<div style={{padding:'20px 30px', borderBottom:'1px solid rgba(255,255,255,0.08)'}}>
|
||||
<div style={{display:'flex', justifyContent:'space-between', alignItems:'flex-start'}}>
|
||||
<div>
|
||||
<h2 style={{margin:0, fontSize:'1.4rem', display:'flex', alignItems:'center', gap:'10px'}}><Globe color="#ebdbb2"/> Unified Workspace</h2>
|
||||
<p style={{margin:'4px 0 0 0', color:'#a89984', fontSize:'0.85rem'}}>Select a cloned voice, design preset, or dubbing project to load into the studio.</p>
|
||||
</div>
|
||||
<button className="btn-primary" onClick={() => setIsCompareModalOpen(true)} style={{display:'flex', alignItems:'center', gap:6, padding:'6px 14px', fontSize:'0.85rem', width:'auto', marginTop:0}}>
|
||||
<Scale size={16}/> A/B Voice Comparison
|
||||
</button>
|
||||
</div>
|
||||
|
||||
{/* Quick Start Guide */}
|
||||
<div style={{marginTop:'20px', padding:'15px', background:'rgba(255,255,255,0.02)', borderRadius:'8px', border:'1px solid rgba(255,255,255,0.05)'}}>
|
||||
@@ -1468,7 +1529,8 @@ function App() {
|
||||
</div>
|
||||
{dubSegments.map((seg, idx) => (
|
||||
<div key={seg.id} className={`segment-row ${dubStep==='generating'&&dubProgress.current===idx+1?'segment-active':''} ${dubStep==='generating'&&dubProgress.current>idx+1?'segment-done':''}`}>
|
||||
<span className="segment-time" style={{width:55}}>
|
||||
<span className="segment-time" style={{width:55, display:'flex', flexDirection:'column'}}>
|
||||
<span>
|
||||
{formatTime(seg.start)}–{formatTime(seg.end)}
|
||||
{seg.speed && seg.speed !== 1.0 && (
|
||||
<span style={{fontSize:'0.55rem', color: seg.speed > 1 ? '#d3869b' : '#8ec07c', marginLeft:2}}>
|
||||
@@ -1476,6 +1538,22 @@ function App() {
|
||||
</span>
|
||||
)}
|
||||
</span>
|
||||
{seg.sync_ratio !== undefined && (
|
||||
<span style={{
|
||||
fontSize: '0.5rem',
|
||||
marginTop: 2,
|
||||
display: 'inline-flex',
|
||||
alignItems: 'center',
|
||||
gap: 2,
|
||||
color: seg.sync_ratio >= 0.95 && seg.sync_ratio <= 1.05 ? '#b8bb26' :
|
||||
seg.sync_ratio > 1.25 ? '#fb4934' : '#fabd2f'
|
||||
}} title={`Generated audio is ${Math.round(seg.sync_ratio * 100)}% the duration of original`}>
|
||||
{seg.sync_ratio >= 0.95 && seg.sync_ratio <= 1.05 ? <CheckCircle size={8}/> :
|
||||
seg.sync_ratio > 1.25 ? <AlertCircle size={8}/> : <Circle size={8}/>}
|
||||
Sync: {Math.round(seg.sync_ratio * 100)}%
|
||||
</span>
|
||||
)}
|
||||
</span>
|
||||
<span style={{width:50, fontSize:'0.58rem', color:'#a89984'}}>{seg.speaker_id || ''}</span>
|
||||
<input className="input-base segment-input" value={seg.text}
|
||||
onChange={e => editSegments(dubSegments.map(s => s.id===seg.id?{...s,text:e.target.value}:s))}
|
||||
@@ -1574,6 +1652,25 @@ function App() {
|
||||
<FileText size={11}/> SRT
|
||||
</button>
|
||||
</div>
|
||||
{/* Advanced Export Row */}
|
||||
<div style={{display:'flex', gap:4, marginTop:4}}>
|
||||
<button className="btn-primary" style={{marginTop:0, flex:1, padding:'4px 7px', fontSize:'0.62rem', background:dubSegments.length?'linear-gradient(135deg,#b8bb26,#98971a)':undefined}}
|
||||
onClick={() => triggerDownload(`${API}/dub/vtt/${dubJobId}/subtitles.vtt`, 'subtitles.vtt')} disabled={!dubSegments.length}>
|
||||
<FileText size={10}/> VTT
|
||||
</button>
|
||||
<button className="btn-primary" style={{marginTop:0, flex:1, padding:'4px 7px', fontSize:'0.62rem', background:dubStep==='done'?'linear-gradient(135deg,#fabd2f,#d79921)':undefined}}
|
||||
onClick={() => triggerDownload(`${API}/dub/download-mp3/${dubJobId}/audio.mp3?preserve_bg=${preserveBg}`, 'dubbed_audio.mp3')} disabled={dubStep!=='done'}>
|
||||
<Music size={10}/> MP3
|
||||
</button>
|
||||
<button className="btn-primary" style={{marginTop:0, flex:1, padding:'4px 7px', fontSize:'0.62rem', background:dubStep==='done'?'linear-gradient(135deg,#fe8019,#d65d0e)':undefined}}
|
||||
onClick={() => triggerDownload(`${API}/dub/export-segments/${dubJobId}`, 'segments.zip')} disabled={dubStep!=='done'}>
|
||||
<Package size={10}/> Clips
|
||||
</button>
|
||||
<button className="btn-primary" style={{marginTop:0, flex:1, padding:'4px 7px', fontSize:'0.62rem', background:dubStep==='done'?'linear-gradient(135deg,#d3869b,#b16286)':undefined}}
|
||||
onClick={() => triggerDownload(`${API}/dub/export-stems/${dubJobId}`, 'stems.zip')} disabled={dubStep!=='done'}>
|
||||
<Layers size={10}/> Stems
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
@@ -2002,6 +2099,135 @@ function App() {
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* ═══ A/B VOICE COMPARISON MODAL ═══ */}
|
||||
{isCompareModalOpen && (
|
||||
<div style={{
|
||||
position: 'fixed', top: 0, left: 0, right: 0, bottom: 0,
|
||||
background: 'rgba(0,0,0,0.85)', backdropFilter: 'blur(8px)',
|
||||
display: 'flex', alignItems: 'center', justifyContent: 'center', zIndex: 9999
|
||||
}}>
|
||||
<div className="glass-panel" style={{ width: 600, maxWidth: '90vw', padding: '24px', display: 'flex', flexDirection: 'column', gap: '16px', position: 'relative' }}>
|
||||
<h2 style={{ margin: 0, color: '#ebdbb2', display: 'flex', alignItems: 'center', gap: '8px', fontSize: '1.2rem' }}>
|
||||
<Scale /> A/B Voice Comparison
|
||||
</h2>
|
||||
<p style={{ margin: 0, fontSize: '0.85rem', color: '#a89984' }}>Compare two voices side by side to make casting decisions.</p>
|
||||
|
||||
<div style={{ display: 'flex', flexDirection: 'column', gap: 6 }}>
|
||||
<label style={{ fontSize: '0.75rem', color: '#a89984', fontWeight: 600 }}>Test Phrase</label>
|
||||
<textarea
|
||||
className="input-base"
|
||||
value={compareText}
|
||||
onChange={e => setCompareText(e.target.value)}
|
||||
rows={2}
|
||||
style={{ resize: 'none' }}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div style={{ display: 'grid', gridTemplateColumns: '1fr 1fr', gap: '20px' }}>
|
||||
{/* Voice A */}
|
||||
<div style={{ display: 'flex', flexDirection: 'column', gap: 8, padding: 12, border: '1px solid rgba(255,255,255,0.05)', borderRadius: 8, background: 'rgba(255,255,255,0.01)' }}>
|
||||
<h3 style={{ margin: 0, color: '#d3869b', fontSize: '0.9rem', display: 'flex', alignItems: 'center', justifyContent: 'center', gap: 6 }}><Fingerprint size={14}/> Voice A</h3>
|
||||
<select className="input-base" value={compareVoiceA} onChange={e => setCompareVoiceA(e.target.value)}>
|
||||
<option value="">-- Select Voice --</option>
|
||||
{profiles.map(p => <option key={p.id} value={p.id}>{p.name}</option>)}
|
||||
{PRESETS.map(p => <option key={p.id} value={`preset:${p.id}`}>{p.name} (Preset)</option>)}
|
||||
</select>
|
||||
{compareResultA ? (
|
||||
<audio src={compareResultA} controls style={{ width: '100%', height: 32, outline: 'none' }} />
|
||||
) : (
|
||||
<div style={{ height: 32, display: 'flex', alignItems: 'center', justifyContent: 'center', color: '#665c54', fontSize: '0.75rem', background: 'rgba(0,0,0,0.2)', borderRadius: 4 }}>No Audio</div>
|
||||
)}
|
||||
</div>
|
||||
|
||||
{/* Voice B */}
|
||||
<div style={{ display: 'flex', flexDirection: 'column', gap: 8, padding: 12, border: '1px solid rgba(255,255,255,0.05)', borderRadius: 8, background: 'rgba(255,255,255,0.01)' }}>
|
||||
<h3 style={{ margin: 0, color: '#8ec07c', fontSize: '0.9rem', display: 'flex', alignItems: 'center', justifyContent: 'center', gap: 6 }}><Fingerprint size={14}/> Voice B</h3>
|
||||
<select className="input-base" value={compareVoiceB} onChange={e => setCompareVoiceB(e.target.value)}>
|
||||
<option value="">-- Select Voice --</option>
|
||||
{profiles.map(p => <option key={p.id} value={p.id}>{p.name}</option>)}
|
||||
{PRESETS.map(p => <option key={p.id} value={`preset:${p.id}`}>{p.name} (Preset)</option>)}
|
||||
</select>
|
||||
{compareResultB ? (
|
||||
<audio src={compareResultB} controls style={{ width: '100%', height: 32, outline: 'none' }} />
|
||||
) : (
|
||||
<div style={{ height: 32, display: 'flex', alignItems: 'center', justifyContent: 'center', color: '#665c54', fontSize: '0.75rem', background: 'rgba(0,0,0,0.2)', borderRadius: 4 }}>No Audio</div>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div style={{ display: 'flex', justifyContent: 'flex-end', gap: '10px', marginTop: '10px' }}>
|
||||
<button className="btn-primary" style={{ background: 'transparent', color: '#a89984', padding: '6px 14px' }} onClick={() => setIsCompareModalOpen(false)}>
|
||||
Close
|
||||
</button>
|
||||
<button
|
||||
className="btn-primary"
|
||||
disabled={isComparing || !compareVoiceA || !compareVoiceB || !compareText.trim()}
|
||||
onClick={async () => {
|
||||
setIsComparing(true);
|
||||
setCompareResultA(null);
|
||||
setCompareResultB(null);
|
||||
|
||||
const generateVoice = async (voiceId, setProgress) => {
|
||||
setProgress(`Preparing voice...`);
|
||||
const formData = new FormData();
|
||||
formData.append("text", compareText);
|
||||
|
||||
let fin_prof = voiceId;
|
||||
let fin_inst = "";
|
||||
if (fin_prof.startsWith('preset:')) {
|
||||
const pr = PRESETS.find(p => p.id === fin_prof.replace('preset:', ''));
|
||||
if (pr) {
|
||||
const parts = Object.values(pr.attrs).filter(v => v !== 'Auto');
|
||||
fin_inst = parts.join(', ');
|
||||
}
|
||||
fin_prof = '';
|
||||
} else if (profiles.find(p => p.id === fin_prof)?.instruct) {
|
||||
fin_inst = profiles.find(p => p.id === fin_prof).instruct;
|
||||
}
|
||||
|
||||
if (fin_prof) formData.append("profile_id", fin_prof);
|
||||
if (fin_inst) formData.append("instruct", fin_inst);
|
||||
|
||||
formData.append("num_step", steps);
|
||||
formData.append("guidance_scale", cfg);
|
||||
formData.append("speed", speed);
|
||||
formData.append("denoise", denoise);
|
||||
formData.append("postprocess_output", postprocess);
|
||||
|
||||
const res = await fetch(`${API}/generate`, { method: "POST", body: formData });
|
||||
if (!res.ok) throw new Error(await res.text());
|
||||
return URL.createObjectURL(await res.blob());
|
||||
};
|
||||
|
||||
try {
|
||||
setCompareProgress("Generating Voice A...");
|
||||
const audioA = await generateVoice(compareVoiceA, setCompareProgress);
|
||||
setCompareResultA(audioA);
|
||||
|
||||
setCompareProgress("Generating Voice B...");
|
||||
const audioB = await generateVoice(compareVoiceB, setCompareProgress);
|
||||
setCompareResultB(audioB);
|
||||
|
||||
setCompareProgress("");
|
||||
toast.success("Comparison complete!");
|
||||
loadHistory();
|
||||
} catch (err) {
|
||||
toast.error("Play failed: " + err.message);
|
||||
setCompareProgress("");
|
||||
} finally {
|
||||
setIsComparing(false);
|
||||
}
|
||||
}}
|
||||
style={{ padding: '6px 14px', width: 200, display: 'flex', justifyContent: 'center', alignItems: 'center' }}
|
||||
>
|
||||
{isComparing ? <><Loader className="spinner" size={14}/> {compareProgress}</> : <><Play size={14}/> Compare</>}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
@@ -1,5 +0,0 @@
|
||||
import json
|
||||
from omnivoice.utils.lang_map import LANG_NAMES, lang_display_name
|
||||
languages = ["Auto"] + sorted(lang_display_name(n) for n in LANG_NAMES)
|
||||
with open("frontend/src/languages.json", "w") as f:
|
||||
json.dump(languages, f)
|
||||
Generated
-2575
File diff suppressed because it is too large
Load Diff
+1
-1
@@ -7,7 +7,7 @@
|
||||
"dev": "turbo run dev //#dev:api",
|
||||
"build": "turbo run build",
|
||||
"start": "turbo run start",
|
||||
"dev:api": "uv run uvicorn api:app --host 0.0.0.0 --port 8000 --reload"
|
||||
"dev:api": "uv run uvicorn backend.main:app --host 0.0.0.0 --port 8000 --reload"
|
||||
},
|
||||
"workspaces": [
|
||||
"frontend"
|
||||
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 1.2 MiB |
BIN
Binary file not shown.
|
After Width: | Height: | Size: 962 KiB |
@@ -41,6 +41,7 @@ dependencies = [
|
||||
"numpy",
|
||||
"soundfile",
|
||||
"psutil>=7.2.2",
|
||||
"pyannote-audio>=4.0.4",
|
||||
]
|
||||
|
||||
[project.optional-dependencies]
|
||||
@@ -105,3 +106,10 @@ include = ["omnivoice"]
|
||||
|
||||
[tool.hatch.build.targets.wheel]
|
||||
packages = ["omnivoice"]
|
||||
|
||||
[dependency-groups]
|
||||
dev = [
|
||||
"httpx>=0.28.1",
|
||||
"pytest>=9.0.3",
|
||||
"pytest-asyncio>=1.3.0",
|
||||
]
|
||||
|
||||
@@ -0,0 +1,11 @@
|
||||
{
|
||||
"name": "omnivoice-promo-recorder",
|
||||
"version": "1.0.0",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"record": "node record_promo.js"
|
||||
},
|
||||
"dependencies": {
|
||||
"playwright": "^1.43.0"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,177 @@
|
||||
import { chromium } from 'playwright';
|
||||
import { execSync } from 'child_process';
|
||||
import path from 'path';
|
||||
import fs from 'fs';
|
||||
import { fileURLToPath } from 'url';
|
||||
|
||||
const __filename = fileURLToPath(import.meta.url);
|
||||
const __dirname = path.dirname(__filename);
|
||||
|
||||
const URL = 'http://localhost:5173';
|
||||
const OUTPUT_DIR = path.join(__dirname, '..', 'pics');
|
||||
const RAW_VIDEO = path.join(OUTPUT_DIR, 'raw_record.webm');
|
||||
const FINAL_MP4 = path.join(OUTPUT_DIR, 'promo.mp4');
|
||||
const FINAL_GIF = path.join(OUTPUT_DIR, 'promo.gif');
|
||||
|
||||
// Ensure output directory exists
|
||||
if (!fs.existsSync(OUTPUT_DIR)) {
|
||||
fs.mkdirSync(OUTPUT_DIR, { recursive: true });
|
||||
}
|
||||
|
||||
async function run() {
|
||||
console.log('🎬 Starting Cinematic Promo Recording...');
|
||||
|
||||
const browser = await chromium.launch({
|
||||
headless: false,
|
||||
args: [
|
||||
'--window-size=1920,1080',
|
||||
'--force-device-scale-factor=2', // retina
|
||||
'--disable-font-subpixel-positioning',
|
||||
'--disable-smooth-scrolling'
|
||||
]
|
||||
});
|
||||
|
||||
const context = await browser.newContext({
|
||||
viewport: { width: 1920, height: 1080 },
|
||||
deviceScaleFactor: 2,
|
||||
recordVideo: {
|
||||
dir: OUTPUT_DIR,
|
||||
size: { width: 1920, height: 1080 }
|
||||
}
|
||||
});
|
||||
|
||||
const page = await context.newPage();
|
||||
let recordingOffsetSeconds = 0;
|
||||
const scriptStartTime = Date.now();
|
||||
|
||||
// Helper for cinematic pausing
|
||||
const wait = (ms) => new Promise(r => setTimeout(r, ms));
|
||||
|
||||
// Helper for smooth zoom injections
|
||||
const cinematicZoom = async (selector, scale, xOffset = 0, yOffset = 0) => {
|
||||
await page.evaluate(({ selector, scale, xOffset, yOffset }) => {
|
||||
const el = document.querySelector('body');
|
||||
el.style.transition = 'transform 2s cubic-bezier(0.25, 1, 0.5, 1)';
|
||||
el.style.transformOrigin = `${xOffset}% ${yOffset}%`;
|
||||
el.style.transform = `scale(${scale})`;
|
||||
}, { selector, scale, xOffset, yOffset });
|
||||
};
|
||||
|
||||
const resetZoom = async () => {
|
||||
await page.evaluate(() => {
|
||||
const el = document.querySelector('body');
|
||||
el.style.transform = 'scale(1)';
|
||||
});
|
||||
};
|
||||
|
||||
try {
|
||||
console.log('📍 Navigating to OmniVoice Studio Launchpad...');
|
||||
await page.goto(URL, { waitUntil: 'load' });
|
||||
|
||||
// Give it enough time to stabilize the layout
|
||||
await wait(2500);
|
||||
|
||||
console.log('📍 Switching to History tab in sidebar...');
|
||||
await page.locator('button:has-text("History")').first().click();
|
||||
await wait(1500);
|
||||
|
||||
console.log('📍 Loading Project from History...');
|
||||
// Click the "Load" button on the first history item
|
||||
await page.locator('button:has-text("Load")').first().click();
|
||||
|
||||
// Wait for the workspace to fully load, waveforms to draw, etc
|
||||
console.log('⏳ Waiting for dubbing workspace to render...');
|
||||
await wait(3500);
|
||||
|
||||
// 🎥 Cinematic Zoom on the Video Player
|
||||
console.log('📍 Zooming on Video Playback...');
|
||||
// Assuming video is roughly in the top left/center of the main view
|
||||
await cinematicZoom('.video-player-container', 1.4, 20, 30);
|
||||
await wait(2000);
|
||||
|
||||
// Play the video
|
||||
console.log('📍 Playing timeline...');
|
||||
// Click play button (WaveSurfer play or native)
|
||||
// Finding the play button by its lucide icon class or explicit text is best
|
||||
// Using a broad selector for the play button in the waveform bar
|
||||
const playBtn = page.locator('button:has(.lucide-play), .waveform-controls button').first();
|
||||
if (await playBtn.isVisible()) {
|
||||
await playBtn.click();
|
||||
}
|
||||
|
||||
// Let it play for a bit while zoomed
|
||||
await wait(6000);
|
||||
|
||||
// Reset zoom and zoom into the segment table
|
||||
console.log('📍 Highlighting Segment Controls...');
|
||||
await resetZoom();
|
||||
await wait(1500);
|
||||
await cinematicZoom('.segment-table', 1.3, 80, 50);
|
||||
await wait(3000);
|
||||
|
||||
// Highlight Output Options
|
||||
console.log('📍 Showing Export Options...');
|
||||
await resetZoom();
|
||||
await wait(1000);
|
||||
await cinematicZoom('text=Output Options', 1.5, 50, 95);
|
||||
await wait(3000);
|
||||
|
||||
// Reset zoom
|
||||
await resetZoom();
|
||||
await wait(1500);
|
||||
|
||||
// Show Clone Tab
|
||||
console.log('📍 Navigating Tabs (Clone, Design)...');
|
||||
await page.click('text=Clone');
|
||||
await wait(2500);
|
||||
|
||||
// Show Design Tab
|
||||
console.log('📍 Showing Voice Design...');
|
||||
await page.click('text=Design');
|
||||
await wait(2500);
|
||||
|
||||
// Back to Dub
|
||||
await page.click('text=Dub');
|
||||
await wait(2000);
|
||||
|
||||
console.log('✅ Browser automation complete.');
|
||||
} catch (error) {
|
||||
console.error('❌ Error during automation:', error);
|
||||
} finally {
|
||||
// Stop recording and close
|
||||
const videoPath = await page.video().path();
|
||||
await context.close();
|
||||
await browser.close();
|
||||
|
||||
// Rename the raw recording
|
||||
if (fs.existsSync(videoPath)) {
|
||||
fs.renameSync(videoPath, RAW_VIDEO);
|
||||
console.log(`\n💾 Raw recording saved to: ${RAW_VIDEO}`);
|
||||
|
||||
console.log('✂️ Processing with FFmpeg (Trimming, Speeding, GIF Generation)...');
|
||||
try {
|
||||
console.log(`✂️ Processing final MP4 without trimming...`);
|
||||
|
||||
// Generate MP4 Promo (Lossless quality)
|
||||
// preset=veryslow, crf=16 is virtually lossless
|
||||
// Speed up the entire video slightly (0.85*PTS is about 15% faster) since UI interactions can feel slow on playback
|
||||
execSync(`ffmpeg -y -i "${RAW_VIDEO}" -filter_complex "[0:v]setpts=0.85*PTS[v]" -map "[v]" -c:v libx264 -preset veryslow -crf 16 -pix_fmt yuv420p "${FINAL_MP4}"`, { stdio: 'inherit' });
|
||||
console.log(`\n✨ HIGH QUALITY MP4 generated: ${FINAL_MP4}`);
|
||||
|
||||
// Generate GIF Promo (24fps, 1080p width, high quality palette)
|
||||
execSync(`ffmpeg -y -i "${FINAL_MP4}" -vf "fps=24,scale=1080:-1:flags=lanczos,split[s0][s1];[s0]palettegen=max_colors=255:stats_mode=diff[p];[s1][p]paletteuse=dither=bayer:bayer_scale=5" -loop 0 "${FINAL_GIF}"`, { stdio: 'inherit' });
|
||||
console.log(`✨ HIGH QUALITY GIF generated: ${FINAL_GIF}`);
|
||||
|
||||
// Clean up raw
|
||||
fs.unlinkSync(RAW_VIDEO);
|
||||
|
||||
} catch (e) {
|
||||
console.error('❌ FFmpeg processing failed. Please ensure ffmpeg is installed natively.');
|
||||
console.error(e.message);
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
run();
|
||||
@@ -1,21 +0,0 @@
|
||||
import asyncio
|
||||
from playwright.async_api import async_playwright
|
||||
|
||||
async def main():
|
||||
async with async_playwright() as p:
|
||||
browser = await p.chromium.launch()
|
||||
page = await browser.new_page(viewport={"width": 1280, "height": 800}, device_scale_factor=2)
|
||||
await page.goto("http://localhost:5173", wait_until="networkidle")
|
||||
await asyncio.sleep(2) # Wait for initial load
|
||||
|
||||
# Take screenshot of design layout
|
||||
await page.screenshot(path="pics/omnivoice_studio_1.png")
|
||||
|
||||
# Click dub tab
|
||||
await page.click("button:has-text('Dub')")
|
||||
await asyncio.sleep(1)
|
||||
await page.screenshot(path="pics/omnivoice_studio_2.png")
|
||||
|
||||
await browser.close()
|
||||
|
||||
asyncio.run(main())
|
||||
@@ -1,13 +0,0 @@
|
||||
const fs = require('fs');
|
||||
const acorn = require('acorn');
|
||||
const jsx = require('acorn-jsx');
|
||||
|
||||
const code = fs.readFileSync('frontend/src/App.jsx', 'utf8');
|
||||
|
||||
try {
|
||||
acorn.Parser.extend(jsx()).parse(code, { sourceType: 'module', ecmaVersion: 2020 });
|
||||
console.log("SUCCESS NO PARSE ERRORS");
|
||||
} catch (e) {
|
||||
console.log("PARSE ERROR AT:", e.loc);
|
||||
console.log("Message:", e.message);
|
||||
}
|
||||
@@ -0,0 +1,526 @@
|
||||
"""
|
||||
OmniVoice Studio API — Unit Test Suite
|
||||
Tests all roadmap features: TaskManager, scene detection, lip-sync scoring,
|
||||
export endpoints (VTT, SRT, MP3, segments ZIP, stems ZIP), streaming TTS.
|
||||
|
||||
Uses FastAPI's TestClient (synchronous httpx) to avoid needing a running server.
|
||||
GPU/model inference is mocked so tests run on any machine in seconds.
|
||||
"""
|
||||
|
||||
import io
|
||||
import os
|
||||
import json
|
||||
import uuid
|
||||
import wave
|
||||
import struct
|
||||
import time
|
||||
import pytest
|
||||
import asyncio
|
||||
|
||||
# Patch environment before importing api
|
||||
os.environ.setdefault("OMNIVOICE_MODEL", "test")
|
||||
|
||||
from unittest.mock import patch, MagicMock, AsyncMock
|
||||
import torch
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Helpers
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def make_wav_bytes(duration_s=1.0, sample_rate=24000, channels=1) -> bytes:
|
||||
"""Create a valid WAV file in memory for testing."""
|
||||
n_samples = int(duration_s * sample_rate)
|
||||
buf = io.BytesIO()
|
||||
with wave.open(buf, "wb") as wf:
|
||||
wf.setnchannels(channels)
|
||||
wf.setsampwidth(2)
|
||||
wf.setframerate(sample_rate)
|
||||
wf.writeframes(struct.pack(f"<{n_samples}h", *([0] * n_samples)))
|
||||
buf.seek(0)
|
||||
return buf.read()
|
||||
|
||||
|
||||
def make_audio_tensor(duration_s=1.0, sample_rate=24000) -> torch.Tensor:
|
||||
"""Create a torch audio tensor of the given duration."""
|
||||
n_samples = int(duration_s * sample_rate)
|
||||
return torch.zeros(1, n_samples)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Fixtures
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@pytest.fixture(scope="session", autouse=True)
|
||||
def _mock_model():
|
||||
"""Prevent real model loading across the entire test session."""
|
||||
mock = MagicMock()
|
||||
mock.sampling_rate = 24000
|
||||
mock.generate.return_value = [make_audio_tensor(1.0)]
|
||||
|
||||
import backend.main as api_mod
|
||||
api_mod.model = mock
|
||||
api_mod._init_db()
|
||||
yield mock
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def client():
|
||||
"""Create a TestClient for the FastAPI app (no server needed)."""
|
||||
from fastapi.testclient import TestClient
|
||||
from backend.main import app
|
||||
return TestClient(app)
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def seeded_job(client):
|
||||
"""Create a fake dub job with segments, tracks, and WAV files on disk."""
|
||||
import backend.main as api_mod
|
||||
|
||||
job_id = str(uuid.uuid4())[:8]
|
||||
job_dir = os.path.join(api_mod.DUB_DIR, job_id)
|
||||
os.makedirs(job_dir, exist_ok=True)
|
||||
|
||||
# Write fake segment WAVs
|
||||
for i in range(3):
|
||||
seg_path = os.path.join(job_dir, f"seg_{i}.wav")
|
||||
with open(seg_path, "wb") as f:
|
||||
f.write(make_wav_bytes(0.5))
|
||||
|
||||
# Write a fake dubbed track
|
||||
track_path = os.path.join(job_dir, "dubbed_en.wav")
|
||||
with open(track_path, "wb") as f:
|
||||
f.write(make_wav_bytes(2.0))
|
||||
|
||||
# Write a fake background audio
|
||||
bg_path = os.path.join(job_dir, "no_vocals.wav")
|
||||
with open(bg_path, "wb") as f:
|
||||
f.write(make_wav_bytes(2.0))
|
||||
|
||||
# Write a fake video
|
||||
video_path = os.path.join(job_dir, "original.mp4")
|
||||
with open(video_path, "wb") as f:
|
||||
f.write(b"\x00" * 100)
|
||||
|
||||
job = {
|
||||
"video_path": video_path,
|
||||
"audio_path": os.path.join(job_dir, "audio.wav"),
|
||||
"vocals_path": os.path.join(job_dir, "vocals.wav"),
|
||||
"no_vocals_path": bg_path,
|
||||
"duration": 3.0,
|
||||
"filename": "test_video.mp4",
|
||||
"segments": [
|
||||
{"id": "a1", "start": 0.0, "end": 1.0, "text": "Hello world", "speaker_id": "Speaker 1"},
|
||||
{"id": "a2", "start": 1.0, "end": 2.0, "text": "How are you", "speaker_id": "Speaker 1"},
|
||||
{"id": "a3", "start": 2.0, "end": 3.0, "text": "Goodbye", "speaker_id": "Speaker 2"},
|
||||
],
|
||||
"dubbed_tracks": {
|
||||
"en": {"path": track_path, "language": "English", "language_code": "en"},
|
||||
},
|
||||
"scene_cuts": [1.5],
|
||||
}
|
||||
|
||||
api_mod._dub_jobs[job_id] = job
|
||||
yield job_id, job
|
||||
# Cleanup
|
||||
api_mod._dub_jobs.pop(job_id, None)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# TASK MANAGER TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestTaskManager:
|
||||
"""Tests for the centralized async batch task queue."""
|
||||
|
||||
def test_task_manager_init(self):
|
||||
from backend.main import TaskManager
|
||||
tm = TaskManager()
|
||||
assert tm.active_tasks == {}
|
||||
assert tm.queue is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_add_task_creates_entry(self):
|
||||
from backend.main import TaskManager
|
||||
tm = TaskManager()
|
||||
tm._init_queue()
|
||||
|
||||
async def dummy():
|
||||
pass
|
||||
|
||||
await tm.add_task("t1", "test", dummy)
|
||||
assert "t1" in tm.active_tasks
|
||||
assert tm.active_tasks["t1"]["status"] == "pending"
|
||||
assert tm.active_tasks["t1"]["type"] == "test"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_worker_processes_task(self):
|
||||
from backend.main import TaskManager
|
||||
tm = TaskManager()
|
||||
results = []
|
||||
|
||||
async def work():
|
||||
results.append("done")
|
||||
|
||||
await tm.add_task("t2", "test", work)
|
||||
|
||||
# Run worker for a brief period
|
||||
worker = asyncio.create_task(tm.worker())
|
||||
await asyncio.sleep(0.2)
|
||||
worker.cancel()
|
||||
|
||||
assert "done" in results
|
||||
assert tm.active_tasks["t2"]["status"] == "done"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_worker_handles_failure(self):
|
||||
from backend.main import TaskManager
|
||||
tm = TaskManager()
|
||||
|
||||
async def fail():
|
||||
raise ValueError("boom")
|
||||
|
||||
await tm.add_task("t3", "test", fail)
|
||||
|
||||
worker = asyncio.create_task(tm.worker())
|
||||
await asyncio.sleep(0.2)
|
||||
worker.cancel()
|
||||
|
||||
assert tm.active_tasks["t3"]["status"] == "failed"
|
||||
assert "boom" in tm.active_tasks["t3"]["error"]
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# SRT EXPORT TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestSRTExport:
|
||||
def test_srt_export(self, client, seeded_job):
|
||||
job_id, _ = seeded_job
|
||||
res = client.get(f"/dub/srt/{job_id}")
|
||||
assert res.status_code == 200
|
||||
content = res.text
|
||||
assert "1\n" in content
|
||||
assert "Hello world" in content
|
||||
assert "-->" in content
|
||||
|
||||
def test_srt_404_missing_job(self, client):
|
||||
res = client.get("/dub/srt/nonexistent")
|
||||
assert res.status_code == 404
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# VTT EXPORT TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestVTTExport:
|
||||
def test_vtt_export(self, client, seeded_job):
|
||||
job_id, _ = seeded_job
|
||||
res = client.get(f"/dub/vtt/{job_id}")
|
||||
assert res.status_code == 200
|
||||
content = res.text
|
||||
assert content.startswith("WEBVTT")
|
||||
assert "Hello world" in content
|
||||
assert "-->" in content
|
||||
# VTT uses periods not commas
|
||||
assert "." in content.split("-->")[0]
|
||||
|
||||
def test_vtt_format_correct(self, client, seeded_job):
|
||||
job_id, _ = seeded_job
|
||||
res = client.get(f"/dub/vtt/{job_id}")
|
||||
lines = res.text.strip().split("\n")
|
||||
assert lines[0] == "WEBVTT"
|
||||
# Find a timestamp line
|
||||
ts_lines = [l for l in lines if "-->" in l]
|
||||
assert len(ts_lines) == 3
|
||||
# Verify format: HH:MM:SS.mmm
|
||||
for ts in ts_lines:
|
||||
start, end = ts.split("-->")
|
||||
assert "." in start.strip()
|
||||
assert "." in end.strip()
|
||||
|
||||
def test_vtt_404_missing_job(self, client):
|
||||
res = client.get("/dub/vtt/nonexistent")
|
||||
assert res.status_code == 404
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# PER-SEGMENT ZIP EXPORT TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestSegmentZipExport:
|
||||
def test_segments_zip_export(self, client, seeded_job):
|
||||
job_id, _ = seeded_job
|
||||
res = client.get(f"/dub/export-segments/{job_id}")
|
||||
assert res.status_code == 200
|
||||
assert res.headers["content-type"] == "application/zip"
|
||||
|
||||
import zipfile
|
||||
zf = zipfile.ZipFile(io.BytesIO(res.content))
|
||||
names = zf.namelist()
|
||||
assert len(names) == 3
|
||||
# Verify naming convention: 001_0.00-1.00_Speaker1.wav
|
||||
assert names[0].startswith("001_")
|
||||
assert names[0].endswith(".wav")
|
||||
assert "Speaker" in names[0]
|
||||
|
||||
def test_segments_zip_404(self, client):
|
||||
res = client.get("/dub/export-segments/nonexistent")
|
||||
assert res.status_code == 404
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# STEM EXPORT TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestStemExport:
|
||||
def test_stems_zip_export(self, client, seeded_job):
|
||||
job_id, _ = seeded_job
|
||||
res = client.get(f"/dub/export-stems/{job_id}")
|
||||
assert res.status_code == 200
|
||||
assert res.headers["content-type"] == "application/zip"
|
||||
|
||||
import zipfile
|
||||
zf = zipfile.ZipFile(io.BytesIO(res.content))
|
||||
names = zf.namelist()
|
||||
assert any("vocals" in n for n in names)
|
||||
assert any("background" in n for n in names)
|
||||
|
||||
def test_stems_404_no_tracks(self, client):
|
||||
import backend.main as api_mod
|
||||
job_id = "stems_test"
|
||||
api_mod._dub_jobs[job_id] = {
|
||||
"segments": [], "dubbed_tracks": {}, "filename": "t.mp4",
|
||||
"video_path": "", "duration": 0,
|
||||
}
|
||||
res = client.get(f"/dub/export-stems/{job_id}")
|
||||
assert res.status_code == 400
|
||||
api_mod._dub_jobs.pop(job_id, None)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# SCENE-AWARE DUBBING TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestSceneAwareDubbing:
|
||||
def test_scene_cuts_stored(self, seeded_job):
|
||||
_, job = seeded_job
|
||||
assert "scene_cuts" in job
|
||||
assert isinstance(job["scene_cuts"], list)
|
||||
|
||||
def test_scene_split_algorithm(self):
|
||||
"""Test the segment splitting logic directly."""
|
||||
segments = [
|
||||
{"id": "s1", "start": 0.0, "end": 3.0, "text": "Hello world this is a test sentence", "speaker_id": "Speaker 1"},
|
||||
]
|
||||
scene_cuts = [1.5]
|
||||
|
||||
# Run the algorithm inline (mirrors api.py logic)
|
||||
sorted_cuts = sorted(scene_cuts)
|
||||
new_segments = []
|
||||
for s in segments:
|
||||
s_start = s["start"]
|
||||
s_end = s["end"]
|
||||
valid_cuts = [c for c in sorted_cuts if c > s_start + 0.2 and c < s_end - 0.2]
|
||||
|
||||
if not valid_cuts:
|
||||
new_segments.append(s)
|
||||
else:
|
||||
curr_start = s_start
|
||||
curr_text = s["text"]
|
||||
total_dur = s_end - s_start
|
||||
|
||||
for cut in valid_cuts:
|
||||
ratio = (cut - curr_start) / max(total_dur, 0.01)
|
||||
split_idx = int(len(curr_text) * ratio)
|
||||
space_idx = curr_text.rfind(' ', 0, split_idx + 5)
|
||||
if space_idx != -1 and space_idx > split_idx - 10:
|
||||
split_idx = space_idx
|
||||
|
||||
part_text = curr_text[:split_idx].strip()
|
||||
curr_text = curr_text[split_idx:].strip()
|
||||
|
||||
if part_text:
|
||||
new_seg = dict(s)
|
||||
new_seg["start"] = round(curr_start, 2)
|
||||
new_seg["end"] = round(cut, 2)
|
||||
new_seg["text"] = part_text
|
||||
new_seg["id"] = "new1"
|
||||
new_segments.append(new_seg)
|
||||
|
||||
curr_start = cut
|
||||
total_dur = s_end - curr_start
|
||||
|
||||
if curr_text:
|
||||
new_seg = dict(s)
|
||||
new_seg["start"] = round(curr_start, 2)
|
||||
new_seg["end"] = round(s_end, 2)
|
||||
new_seg["text"] = curr_text
|
||||
new_seg["id"] = "new2"
|
||||
new_segments.append(new_seg)
|
||||
|
||||
assert len(new_segments) == 2
|
||||
assert new_segments[0]["end"] == 1.5
|
||||
assert new_segments[1]["start"] == 1.5
|
||||
# Text should be split
|
||||
combined = new_segments[0]["text"] + " " + new_segments[1]["text"]
|
||||
assert combined == "Hello world this is a test sentence"
|
||||
|
||||
def test_no_split_when_cut_too_close_to_edge(self):
|
||||
"""Cuts within 0.2s of segment edges should NOT split."""
|
||||
segments = [{"id": "s1", "start": 0.0, "end": 1.0, "text": "Short", "speaker_id": "Speaker 1"}]
|
||||
scene_cuts = [0.1, 0.9] # Both within 0.2s padding
|
||||
|
||||
sorted_cuts = sorted(scene_cuts)
|
||||
new_segments = []
|
||||
for s in segments:
|
||||
valid_cuts = [c for c in sorted_cuts if c > s["start"] + 0.2 and c < s["end"] - 0.2]
|
||||
if not valid_cuts:
|
||||
new_segments.append(s)
|
||||
|
||||
assert len(new_segments) == 1 # No split occurred
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# LIP-SYNC SCORING TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestLipSyncScoring:
|
||||
def test_sync_ratio_calculation(self):
|
||||
"""Test the sync ratio math directly."""
|
||||
seg_duration = 2.0 # original segment is 2 seconds
|
||||
sample_rate = 24000
|
||||
|
||||
# Generated audio is exactly 2 seconds → ratio = 1.0
|
||||
audio_tensor = make_audio_tensor(2.0, sample_rate)
|
||||
generated_dur = audio_tensor.shape[-1] / sample_rate
|
||||
sync_ratio = round(generated_dur / max(seg_duration, 0.01), 3)
|
||||
assert sync_ratio == 1.0
|
||||
|
||||
def test_sync_ratio_fast(self):
|
||||
"""Generated audio shorter than original → ratio < 1."""
|
||||
seg_duration = 2.0
|
||||
audio_tensor = make_audio_tensor(1.5, 24000)
|
||||
generated_dur = audio_tensor.shape[-1] / 24000
|
||||
sync_ratio = round(generated_dur / max(seg_duration, 0.01), 3)
|
||||
assert sync_ratio == 0.75
|
||||
|
||||
def test_sync_ratio_slow(self):
|
||||
"""Generated audio longer than original → ratio > 1."""
|
||||
seg_duration = 2.0
|
||||
audio_tensor = make_audio_tensor(3.0, 24000)
|
||||
generated_dur = audio_tensor.shape[-1] / 24000
|
||||
sync_ratio = round(generated_dur / max(seg_duration, 0.01), 3)
|
||||
assert sync_ratio == 1.5
|
||||
|
||||
def test_sync_ratio_thresholds(self):
|
||||
"""Verify color-coded classification logic."""
|
||||
def classify(ratio):
|
||||
if 0.95 <= ratio <= 1.05:
|
||||
return "green"
|
||||
elif ratio > 1.25:
|
||||
return "red"
|
||||
else:
|
||||
return "yellow"
|
||||
|
||||
assert classify(1.0) == "green"
|
||||
assert classify(0.95) == "green"
|
||||
assert classify(1.05) == "green"
|
||||
assert classify(0.8) == "yellow"
|
||||
assert classify(1.2) == "yellow"
|
||||
assert classify(1.3) == "red"
|
||||
assert classify(1.5) == "red"
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# SRT/VTT TIMESTAMP FORMATTING TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestTimestampFormatting:
|
||||
def test_srt_time_format(self):
|
||||
from backend.main import _format_srt_time
|
||||
assert _format_srt_time(0.0) == "00:00:00,000"
|
||||
assert _format_srt_time(61.5) == "00:01:01,500"
|
||||
assert _format_srt_time(3661.123) == "01:01:01,123"
|
||||
|
||||
def test_vtt_time_format(self):
|
||||
from backend.main import _format_vtt_time
|
||||
assert _format_vtt_time(0.0) == "00:00:00.000"
|
||||
assert _format_vtt_time(61.5) == "00:01:01.500"
|
||||
# SRT uses comma, VTT uses period
|
||||
assert "." in _format_vtt_time(1.0)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# API ENDPOINT VALIDATION TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestAPIEndpoints:
|
||||
def test_model_status(self, client):
|
||||
res = client.get("/model/status")
|
||||
assert res.status_code == 200
|
||||
data = res.json()
|
||||
assert "loaded" in data
|
||||
assert "status" in data
|
||||
|
||||
def test_sysinfo(self, client):
|
||||
res = client.get("/sysinfo")
|
||||
assert res.status_code == 200
|
||||
data = res.json()
|
||||
assert "cpu" in data
|
||||
assert "ram" in data
|
||||
|
||||
def test_dub_tracks(self, client, seeded_job):
|
||||
job_id, _ = seeded_job
|
||||
res = client.get(f"/dub/tracks/{job_id}")
|
||||
assert res.status_code == 200
|
||||
data = res.json()
|
||||
assert "tracks" in data
|
||||
assert "en" in data["tracks"]
|
||||
|
||||
def test_tasks_stream_404(self, client):
|
||||
res = client.get("/tasks/stream/nonexistent")
|
||||
assert res.status_code == 404
|
||||
|
||||
def test_dub_download_404(self, client):
|
||||
res = client.get("/dub/download/nonexistent")
|
||||
assert res.status_code == 404
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
# STREAMING TTS TESTS
|
||||
# ═══════════════════════════════════════════════════════════════════════
|
||||
|
||||
class TestStreamingTTS:
|
||||
def test_generate_returns_streaming_response(self, client):
|
||||
"""POST /generate should return streamed WAV with metadata headers."""
|
||||
with patch("backend.main.get_model") as mock_get:
|
||||
mock_model = MagicMock()
|
||||
mock_model.sampling_rate = 24000
|
||||
mock_model.generate.return_value = [make_audio_tensor(1.0)]
|
||||
|
||||
async def _get():
|
||||
return mock_model
|
||||
mock_get.return_value = _get()
|
||||
|
||||
import backend.main as api_mod
|
||||
api_mod.model = mock_model
|
||||
|
||||
res = client.post("/generate", data={
|
||||
"text": "Hello world",
|
||||
"num_step": "4",
|
||||
"guidance_scale": "2.0",
|
||||
"speed": "1.0",
|
||||
"denoise": "true",
|
||||
"t_shift": "0.1",
|
||||
"position_temperature": "5.0",
|
||||
"class_temperature": "0.0",
|
||||
"layer_penalty_factor": "5.0",
|
||||
"postprocess_output": "true",
|
||||
})
|
||||
assert res.status_code == 200
|
||||
assert res.headers.get("content-type") == "audio/wav"
|
||||
assert res.headers.get("x-audio-id") is not None
|
||||
assert res.headers.get("x-gen-time") is not None
|
||||
assert res.headers.get("x-audio-duration") is not None
|
||||
# Verify it's valid WAV
|
||||
assert len(res.content) > 44 # WAV header is 44 bytes minimum
|
||||
Reference in New Issue
Block a user