Skip to main content

A versatile tool for YouTube media downloading and AI processing with SQLite-based glossary.

Project description

imansur-ytb

A professional, modular AI pipeline for high-quality YouTube media ingestion and technical translation.

Philosophy: Modular Pipeline Architecture

This library is designed as a series of independent pipeline components. Each module is decoupled, meaning you can use the downloader without the translator, or provide your own transcripts to the translation engine.

Installation

pip install imansur-ytb

Module 1: Media (The Collector)

Handles media downloading with zero-touch FFmpeg management.

from imansur_ytb import get_video

# Returns a list of metadata dictionaries containing file paths
media_list = get_video("https://youtube.com/watch?v=...", audio_only=True)

Module 2: Translator (The Intelligence)

A standalone technical translation engine optimized for English-to-Turkish dubbing scripts. It features AI Term Discovery and persistent SQLite memory.

from imansur_ytb import translate_transcript

# Use as a standalone tool for any transcript JSON
translated_data = translate_transcript(
    transcript_path="my_transcript.json",
    api_key="YOUR_GEMINI_KEY", # or set GEMINI_API_KEY in .env
    verbose=True
)

Key Features of Module 2:

  • Zero-Config .env Support: Automatically picks up GEMINI_API_KEY.
  • SQLite Glossary: Ships with a default 1300+ term technical dictionary.
  • Auto-Learning: Discovers new terms during translation and updates the local glossary.
  • Consistency: Uses a double-pass AI logic to ensure terminology remains consistent across the entire transcript.

Parameter Reference

translate_transcript(...)

Parameter Type Default Description
transcript_path str Required Path to the input JSON transcript
api_key str None Gemini API Key (Will check .env if None)
model str "gemini-2.0-flash" AI Model (Optimized for Flash)

Module 3: Synthesis (The Voice)

Converts text or transcripts to high-quality neural speech using edge-tts.

from imansur_ytb import synthesize_text, synthesize_transcript

# 1. Simple TTS (for PBX/Switchboard)
synthesize_text("Hoş geldiniz!", "welcome.mp3", voice="tr-TR-AhmetNeural")

# 2. Pipeline Dubbing (Timed & Synced)
synthesize_transcript("tr_transcript.json", output_file="full_dub.mp3", verbose=True)

Key Features of Module 3:

  • Free & Unlimited: No API tokens required (uses Microsoft Edge TTS).
  • Auto-Sync: Automatically calculates if a segment needs to be sped up to fit the video timing.
  • Timed Merging: Uses FFmpeg to place audio segments at exact timestamps with correct silences.

Developed by imansur - Building the future of AI Dubbing.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

imansur_ytb-0.6.0.tar.gz (51.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

imansur_ytb-0.6.0-py3-none-any.whl (50.4 kB view details)

Uploaded Python 3

File details

Details for the file imansur_ytb-0.6.0.tar.gz.

File metadata

  • Download URL: imansur_ytb-0.6.0.tar.gz
  • Upload date:
  • Size: 51.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.10

File hashes

Hashes for imansur_ytb-0.6.0.tar.gz
Algorithm Hash digest
SHA256 f13859974849349758721228f53bc477ba34a917af963fcf4acc83fcf7be1b20
MD5 0da4b7b2578e29ef46d7eb10a1d24631
BLAKE2b-256 94a6cd663cc36d9de3e41287ca24b5ec1966036ae14e82b0c85bdc27b092148d

See more details on using hashes here.

File details

Details for the file imansur_ytb-0.6.0-py3-none-any.whl.

File metadata

  • Download URL: imansur_ytb-0.6.0-py3-none-any.whl
  • Upload date:
  • Size: 50.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.10

File hashes

Hashes for imansur_ytb-0.6.0-py3-none-any.whl
Algorithm Hash digest
SHA256 2ced730d32d69b0bac187203819708bada0e2ea75ea8d3ac3dc11b5424d4102a
MD5 81b69aaf1809dab74621e3b5f41829da
BLAKE2b-256 97eeec8fcb4cfd4fb6163fde4549d7c47d5904924c42cb2ddcd68b4c4702204e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page