Josh Knapp
48fe41b064
- Implement faster-whisper TranscribeService with word-level timestamps, progress reporting, and hardware auto-detection - Wire up Rust SidecarManager for Python process lifecycle (spawn, IPC, shutdown) - Add transcribe_file Tauri command bridging frontend to Python sidecar - Integrate wavesurfer.js WaveformPlayer with play/pause, skip, seek controls - Build TranscriptEditor with word-level click-to-seek and active highlighting - Connect file import flow: prompt → asset load → transcribe → display - Add typed tauri-bridge service with TranscriptionResult interface - Add Python tests for hardware detection and transcription result formatting Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
76 lines
2.2 KiB
Python
76 lines
2.2 KiB
Python
"""GPU/CPU detection and VRAM estimation."""
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from __future__ import annotations
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import os
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import sys
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from dataclasses import dataclass
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@dataclass
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class HardwareInfo:
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"""Detected hardware capabilities."""
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has_cuda: bool = False
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cuda_device_name: str = ""
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vram_mb: int = 0
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ram_mb: int = 0
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cpu_cores: int = 0
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recommended_model: str = "base"
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recommended_device: str = "cpu"
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recommended_compute_type: str = "int8"
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def detect_hardware() -> HardwareInfo:
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"""Detect available hardware and recommend model configuration."""
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info = HardwareInfo()
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# CPU info
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info.cpu_cores = os.cpu_count() or 1
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# RAM info
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try:
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with open("/proc/meminfo") as f:
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for line in f:
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if line.startswith("MemTotal:"):
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# Value is in kB
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info.ram_mb = int(line.split()[1]) // 1024
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break
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except (FileNotFoundError, ValueError):
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pass
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# CUDA detection
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try:
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import torch
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if torch.cuda.is_available():
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info.has_cuda = True
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info.cuda_device_name = torch.cuda.get_device_name(0)
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info.vram_mb = torch.cuda.get_device_properties(0).total_mem // (1024 * 1024)
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except ImportError:
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print("[sidecar] torch not available, GPU detection skipped", file=sys.stderr, flush=True)
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# Model recommendation based on hardware
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if info.has_cuda and info.vram_mb >= 8000:
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info.recommended_model = "large-v3-turbo"
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info.recommended_device = "cuda"
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info.recommended_compute_type = "int8"
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elif info.has_cuda and info.vram_mb >= 4000:
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info.recommended_model = "medium"
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info.recommended_device = "cuda"
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info.recommended_compute_type = "int8"
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elif info.ram_mb >= 16000:
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info.recommended_model = "medium"
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info.recommended_device = "cpu"
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info.recommended_compute_type = "int8"
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elif info.ram_mb >= 8000:
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info.recommended_model = "small"
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info.recommended_device = "cpu"
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info.recommended_compute_type = "int8"
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else:
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info.recommended_model = "base"
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info.recommended_device = "cpu"
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info.recommended_compute_type = "int8"
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return info
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