Backend Overview

Backend Overview

Understanding the Subtide backend server.

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Architecture

The Subtide backend is a Flask-based REST API that handles:

1. Video Processing - Downloading and extracting audio
2. Transcription - Converting speech to text using Whisper
3. Translation - Translating text using LLM APIs
4. Streaming - Real-time translation for Tier 4

┌─────────────────────────────────────────────────────────────┐
│                     Subtide Backend                          │
├─────────────────────────────────────────────────────────────┤
│                                                              │
│  ┌──────────┐    ┌──────────────┐    ┌────────────────┐    │
│  │  Flask   │───▶│   Whisper    │───▶│   Translation  │    │
│  │  API     │    │   Service    │    │   Service      │    │
│  └──────────┘    └──────────────┘    └────────────────┘    │
│       │                │                     │              │
│       │                ▼                     ▼              │
│       │         ┌──────────────┐    ┌────────────────┐    │
│       │         │    MLX /     │    │   OpenAI /     │    │
│       │         │   Faster     │    │   OpenRouter   │    │
│       │         └──────────────┘    └────────────────┘    │
│       │                                                     │
│       ▼                                                     │
│  ┌──────────────────────────────────────────────────────┐  │
│  │                  YouTube Service                      │  │
│  │           (yt-dlp for video/audio extraction)        │  │
│  └──────────────────────────────────────────────────────┘  │
│                                                              │
└─────────────────────────────────────────────────────────────┘

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Deployment Options

Option	Best For	Setup Difficulty
Binary	Personal use, quick start	Easy
Python Source	Development, customization	Medium
Docker	Production, teams	Medium
RunPod	GPU acceleration, cloud	Medium

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Quick Start

Binary (Fastest)

# Download from releases
chmod +x subtide-backend-macos
./subtide-backend-macos

Docker (Production)

cd backend
docker-compose up subtide-tier2

Source (Development)

cd backend
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
./run.sh

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Whisper Backends

Subtide supports multiple Whisper implementations:

MLX (Apple Silicon)

Optimized for M1/M2/M3/M4 Macs:

WHISPER_BACKEND=mlx ./subtide-backend

• Uses unified memory efficiently
• No separate GPU memory needed
• Best for macOS users

Faster-Whisper (NVIDIA)

CUDA-accelerated for NVIDIA GPUs:

WHISPER_BACKEND=faster ./subtide-backend

• Requires CUDA toolkit
• Significant speedup on supported GPUs
• Best for Linux/Windows with NVIDIA

OpenAI Whisper (Cloud)

Original Whisper implementation:

WHISPER_BACKEND=openai ./subtide-backend

• CPU-based (slower)
• Works everywhere
• Fallback option

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Model Selection

Model	Size	Speed	Quality
tiny	~39 MB	Fastest	Basic
base	~74 MB	Fast	Good
small	~244 MB	Medium	Better
medium	~769 MB	Slow	Great
large-v3	~1.5 GB	Slowest	Best
large-v3-turbo	~800 MB	Fast	Excellent

Recommended: large-v3-turbo for best speed/quality ratio.

---

Hardware Requirements

Apple Silicon

Mac	Memory	Recommended Model
8 GB	Limited	tiny, base
16 GB	Good	small, base
32 GB	Excellent	large-v3
64 GB+	Optimal	Any model

NVIDIA GPUs

GPU	VRAM	Recommended Model
RTX 3060	12 GB	medium
RTX 3090/4080	16-24 GB	large-v3
RTX 4090	24 GB	Any model

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Environment Variables

Core configuration:

Variable	Description	Default
PORT	Server port	5001
WHISPER_MODEL	Model size	base
WHISPER_BACKEND	Backend type	Auto
CORS_ORIGINS	Allowed origins	*

See Configuration for full list.

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Health Check

Verify the backend is running:

curl http://localhost:5001/health

Expected response:

{"status": "healthy"}

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Next Steps

• Docker Deployment - Container deployment
• RunPod Deployment - Cloud GPU deployment
• Local LLM Setup - Use local models
• API Reference - API documentation