personal_development/video_transcription/ai_transcriber_v2/context/CURRENT_STATE.md

Current State of AI Transcriber V2

Date: January 12, 2026 Version: 2.0 (Refactored & Robust)

🚀 Recently Completed Features

1. Unified Translation Logic: All scripts now use a shared fallback pipeline: Primary (User Pref) -> Secondary -> Local LLM (Ollama) -> MyMemory.
2. Flattened Directory Structure: Removed nested ai_transcriber_v2/ai_transcriber_v2 folders. All V2 modules are now in the root of ai_transcriber_v2/.
3. Flatpak & Bazzite Compatibility:
   • Added flatpak-spawn --host support for ffmpeg, ffprobe, and ollama.
   • Updated mount_truenas.sh to handle UID/GID mapping for write permissions on remote shares.
4. Hardware-Accelerated Safety Checks:
   • Size Validation: Rejects any remuxed file that drops more than 20% of the original size.
   • Duration Validation: Rejects any remuxed file where the duration differs by more than 1 second.
   • Zero-Byte Check: Deletes empty outputs immediately.
5. Intelligent Skipping:
   • Whisper detects source language; if it matches the target (e.g., English to English), translation is skipped entirely.
6. Progress Tracking:
   • Integrated tqdm progress bars for iterative translation steps.
   • Enabled verbose=True for Whisper to show live transcription segments.
7. Stability:
   • Fixed SQLAlchemy DetachedInstanceError by expunging objects from sessions in tracker.py.
   • Added GracefulKiller for clean Ctrl+C shutdowns (finishes current file, then exits).

🛠 Active Setup

• Environment: Bazzite (Linux) running VS Code via Flatpak.
• Local LLM: Ollama with llama3 (or dolphin-llama3).
• Media Tools: Host-level FFmpeg/FFprobe accessible via flatpak-spawn.

📌 Next Steps / Future Ideas

• Consider batching small SRT segments for Gemini to reduce API calls and improve context.
• Add a GUI or Web dashboard for tracking job_history.db.
• Implement auto-retry for specific "failed_validation" files with different model parameters.