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⚡ Blitz AI

Blitz AI

Professional Transcription Studio

The most powerful open-source transcription tool with Hebrew-first support.

Transcribe any audio or video — local files, YouTube, Vimeo, entire playlists — with your choice of engine.

License: MIT Made with FastAPI Made with Next.js Hebrew First

Quick Start · Features · Architecture · מדריך בעברית · LLM Setup Prompt

Why Blitz AI?

Most transcription tools treat Hebrew as an afterthought. Blitz AI was built Hebrew-first — RTL layout, Hebrew-optimized models, and a correction studio designed for right-to-left editing. But it works beautifully with any language.

What makes Blitz AI different:

Feature Blitz AI Otter.ai Descript MacWhisper
Hebrew-first RTL UI Yes No Partial No
Local (free) transcription Yes No No Yes
YouTube/Vimeo download Yes No Limited No
Playlist batch processing Yes No No No
Video player in studio Yes No Yes No
Correction studio Yes No Yes No
5 export formats Yes 3 4 3
ivrit-ai Hebrew model Yes No No No
Open source Yes No No No
No subscription Yes $8-30/mo $24+/mo $75 once

Features

Transcription Engines — Choose Your Power

Engine Speed Cost Best For
Whisper V3 Large (Local) ~1x real-time Free Privacy, no internet needed
Groq Whisper (Cloud) 299x real-time $0.04/hr Speed, large batches
Google Gemini (Cloud) Fast ~$0.01/min Multilingual, context
ivrit-ai (HuggingFace) Varies Free/Low Best Hebrew accuracy

Input Sources

  • File upload — Drag & drop any audio/video format (mp3, wav, mp4, mkv, mov, flac, ogg, webm...)
  • Multi-file upload — Select dozens of files at once
  • Folder scan — Point to a folder path, Blitz AI finds all media files recursively
  • YouTube — Paste a video URL, Blitz AI downloads video + audio automatically
  • Vimeo — Same magic, different platform
  • Playlists — Paste a YouTube playlist URL, transcribe an entire course
  • 1000+ sites — Powered by yt-dlp, supports Dailymotion, Facebook, TikTok, Twitch...

Correction Studio

  • Video/audio player synced with transcript
  • Click any segment to jump to that timestamp
  • Edit text directly — every save creates a new version (infinite undo)
  • Confidence highlighting for uncertain words
  • Keyboard shortcuts (Ctrl+S save, F2 play/pause)
  • Version history — go back to any previous edit

Export Formats

Format Extension Used By
SubRip .srt Premiere Pro, DaVinci Resolve, YouTube
WebVTT .vtt HTML5 video, web players
Advanced SSA .ass Aegisub, anime subtitles, complex styling
Plain Text .txt Docs, articles, summaries
JSON .json Developers, custom processing

Beautiful UI

  • White + pink theme inspired by modern SaaS design
  • Collapsible right sidebar (RTL-native)
  • Full dark mode
  • Responsive, desktop-first design
  • Hebrew font (Heebo) optimized for readability

Architecture

graph TB
    subgraph "Frontend — Next.js 15"
        UI[Beautiful RTL UI]
        UP[Upload Zone]
        URL[YouTube/URL Input]
        STUDIO[Correction Studio]
        EXP[Export Manager]
    end

    subgraph "Backend — FastAPI"
        API[REST API + WebSocket]
        TM[Transcription Manager]
        DL[URL Downloader<br/>yt-dlp]
        AP[Audio Processor<br/>ffmpeg]
        CM[Chunk Merger]
        ES[Export Service]
    end

    subgraph "Transcription Engines"
        WH[Whisper V3 Large<br/>Local · Free]
        GR[Groq API<br/>Cloud · $0.04/hr]
        GM[Google Gemini<br/>Cloud · Fast]
        HF[ivrit-ai<br/>Best Hebrew]
    end

    subgraph "Storage"
        DB[(SQLite<br/>Projects & Transcripts)]
        FS[File System<br/>Audio/Video Files]
    end

    UI --> API
    UP -->|Upload files| API
    URL -->|YouTube/Vimeo URL| API

    API --> TM
    API --> DL
    DL -->|Download video + audio| FS
    TM --> AP
    AP -->|Convert to WAV 16kHz| FS
    AP -->|Split 30s chunks| TM

    TM -->|Choose engine| WH
    TM -->|Choose engine| GR
    TM -->|Choose engine| GM
    TM -->|Choose engine| HF

    WH -->|Segments + words| CM
    GR -->|Segments + words| CM
    GM -->|Segments + words| CM
    HF -->|Segments + words| CM

    CM -->|Merged transcript| DB
    STUDIO -->|Edit & save| DB
    EXP --> ES
    ES -->|SRT/VTT/ASS/TXT/JSON| UI

    style WH fill:#10b981,color:#fff
    style GR fill:#f59e0b,color:#fff
    style GM fill:#3b82f6,color:#fff
    style HF fill:#8b5cf6,color:#fff
    style UI fill:#ec4899,color:#fff
    style STUDIO fill:#ec4899,color:#fff
Loading

Transcription Pipeline

sequenceDiagram
    participant U as User
    participant F as Frontend
    participant B as Backend
    participant E as Engine
    participant DB as Database

    U->>F: Upload file / Paste URL
    F->>B: POST /api/transcribe

    alt YouTube/Vimeo URL
        B->>B: yt-dlp download video (MP4)
        B->>B: yt-dlp extract audio (WAV)
    end

    B->>B: ffmpeg convert → WAV 16kHz mono
    B->>B: Split into 30s chunks (2s overlap)

    loop Each chunk
        B->>E: transcribe_chunk(audio)
        E-->>B: segments + word timestamps
        B-->>F: WebSocket: progress update
    end

    B->>B: Merge chunks (align timestamps, deduplicate)
    B->>DB: Store segments + words
    B-->>F: WebSocket: completed!

    U->>F: Open Correction Studio
    F->>B: GET /api/studio/{id}
    B-->>F: Video + segments + words

    U->>F: Edit transcript
    F->>B: PUT /api/studio/{id}
    B->>DB: New version (append-only)

    U->>F: Export as SRT
    F->>B: POST /api/export/{id}
    B-->>F: Downloaded file
Loading

Database Schema

erDiagram
    PROJECT ||--o{ TRANSCRIPT_VERSION : has
    TRANSCRIPT_VERSION ||--o{ SEGMENT : contains
    SEGMENT ||--o{ WORD : contains
    PROJECT }o--o{ TAG : tagged

    PROJECT {
        string id PK
        string name
        string source_path
        string video_path
        string source_url
        string source_type
        float duration_seconds
        string status
        float progress
    }

    TRANSCRIPT_VERSION {
        string id PK
        string project_id FK
        int version_number
        datetime created_at
    }

    SEGMENT {
        string id PK
        string version_id FK
        int index_num
        float start_time
        float end_time
        string text
        float confidence
    }

    WORD {
        string id PK
        string segment_id FK
        string word
        float start_time
        float end_time
        float confidence
    }
Loading

Quick Start

🇮🇱 לא טכני? יש מדריך מפורט בעברית שמסביר כל שלב בשפת בני אדם.

🤖 מעדיף שה-AI יעזור? העתיקו את ה-LLM Setup Prompt ל-ChatGPT/Claude והוא ידריך אתכם.

Prerequisites

  • Python 3.11+
  • Node.js 18+
  • ffmpeg (brew install ffmpeg on macOS)
  • yt-dlp (pip install yt-dlp or brew install yt-dlp)

1. Clone

git clone https://github.com/hoodini/blitzai.git
cd blitzai

2. Backend Setup

cd backend
python -m venv .venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows
pip install -r requirements.txt

# Configure API keys (optional — local Whisper works without any keys)
# IMPORTANT: .env must stay inside backend/ — the app reads it from here
cp .env.example .env
# Edit .env to add your API keys (at least one: GROQ_API_KEY or HUGGINGFACE_API_KEY)
# Note: Groq free tier is limited to 20 requests/min — the app auto-paces and retries

3. Frontend Setup

cd ../frontend
npm install

4. Run

# Terminal 1 — Backend
cd backend
uvicorn app.main:app --host 127.0.0.1 --port 8000 --reload

# Terminal 2 — Frontend
cd frontend
npm run dev

Open http://localhost:3000 and start transcribing!

API Keys (Optional)

Engine Where to Get Env Variable
Groq console.groq.com GROQ_API_KEY
Google Gemini aistudio.google.com GEMINI_API_KEY
HuggingFace huggingface.co/settings/tokens HUGGINGFACE_API_KEY

Note: Local Whisper requires no API key — it runs entirely on your machine.

Groq free tier: Limited to 20 requests/minute. Blitz AI automatically spaces requests to stay under this limit, so longer files may take a bit more time. Rate limit retries are handled transparently.

Tech Stack

Layer Technology
Frontend Next.js 15, React, TypeScript, Tailwind CSS, shadcn/ui
Backend Python, FastAPI, SQLAlchemy, Pydantic
Database SQLite (WAL mode)
Audio ffmpeg, yt-dlp
Local ASR faster-whisper (CTranslate2)
Cloud ASR Groq, Google Gemini, HuggingFace

Project Structure

blitzai/
├── backend/
│   ├── app/
│   │   ├── main.py              # FastAPI app + WebSocket
│   │   ├── config.py            # Settings & env vars
│   │   ├── database.py          # SQLite setup
│   │   ├── models.py            # SQLAlchemy models
│   │   ├── schemas.py           # Pydantic schemas
│   │   ├── engines/             # Transcription engines
│   │   │   ├── base.py          # Engine protocol
│   │   │   ├── faster_whisper.py
│   │   │   ├── groq_engine.py
│   │   │   ├── gemini_engine.py
│   │   │   └── huggingface_engine.py
│   │   ├── services/
│   │   │   ├── audio_processor.py    # ffmpeg operations
│   │   │   ├── url_downloader.py     # yt-dlp integration
│   │   │   ├── transcription_manager.py
│   │   │   ├── chunk_merger.py
│   │   │   └── export_service.py
│   │   └── routers/
│   │       ├── transcribe.py    # Upload/URL/folder endpoints
│   │       ├── projects.py      # CRUD
│   │       ├── studio.py        # Correction studio API
│   │       ├── export.py        # Export endpoints
│   │       └── settings.py
│   ├── requirements.txt
│   └── .env.example              # API key template (copy to .env)
├── frontend/
│   ├── src/
│   │   ├── app/                 # Next.js pages (RTL)
│   │   ├── components/          # React components
│   │   ├── stores/              # Zustand state
│   │   └── lib/                 # API client & utils
│   └── package.json
├── README.md
└── SETUP_GUIDE.md

Contributing

Contributions welcome! Areas to help:

  • WaveSurfer.js waveform visualization
  • Speaker diarization (who said what)
  • Real-time WebSocket progress bar
  • More export formats (EDL, FCPXML)
  • Batch operations UI
  • Docker support
  • i18n (Arabic, Russian, English UI)

License

MIT License — free for personal and commercial use.

Built with passion by Yuval Avidani

Website X Instagram TikTok GitHub LinkTree Facebook

About

קול — Professional Transcription Studio. Hebrew-first, 4 engines, YouTube support, correction studio.

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