Features

• Translation (sieve/seamless_text2text): Translates text from a source language to a target language.
• Youtube Link Transcription (langchain/youtube_transcripts): Transcribes audio from a given URL.
• Detect Language (sieve): Identifies the language of the given text.
• Text to Speech (sieve): Converts text into spoken words.
• Translate and Talk (sieve): Translates text from one language to another and then converts the translated text to speech.
• Youtube Video Download (sieve): Downloads a Youtube video in MP4 format given its URL.
• Detect Language and Translate: Detects the language of the text and translates it to a specified target language.
• Audio Enhancement (sieve): Enhances the quality of an mp3 or wav file.
• Visual question answering (sieve/llava-vl-13b): Visual question answering with GPT-4 level capabilities.

Setup

To set up the package, follow these steps:

1. Install the Package: Install this package using pip: pip install common-ml-functions

2. Import in Your Project: Import the required functionalities in your Python project:

from common-ml-functions.translation import translate
from common-ml-functions.text_to_speech import convert_text_to_speech
# ... other imports as needed

Usage

The package offers a range of functionalities that can be easily integrated into Python projects. Here are some of the features and how to use them:

Translation: Use translate(original_text, source_language, target_language) to translate text.

from common-ml-functions.language import translate

translated_text = translate("Hello, world!", "en", "es")
print(translated_text)

Youtube Link Transcription: Use yb_transcript(url) to get transcriptions of YouTube videos.

from common-ml-functions.yb import yb_transcript

transcript = yb_transcript("https://www.youtube.com/watch?v=example")
print("Transcript:", transcript)

Detect Language: Use detect(text) to identify the language of a given text.

from common-ml-functions.language import detect

language_code = detect("Ceci est un texte en français.")
print(f"The detected language code is: {language_code}")

Text to Speech: Use convert_text_to_speech(text) to convert text into speech.

from common-ml-functions.text_to_speech import convert_text_to_speech

audio_file_path = convert_text_to_speech("Hello, this is a test.")
print(f"Audio file saved at: {audio_file_path}")

Translate and Talk: Use translate_and_talk(text, target_language) to translate and convert text to speech.

from common-ml-functions.text_to_speech import translate_and_talk

audio_file_path = translate_and_talk("This is a test.", "es")
print(f"Translated and converted to speech, file saved at: {audio_file_path}")

Youtube Video Download: Use yb_download(url) to download YouTube videos.

from common-ml-functions.yb import yb_download

video_path = yb_download("https://www.youtube.com/watch?v=example")
print(f"Video downloaded at: {video_path}")

Detect Language and Translate: Combine detect and translate for detecting and translating text.

from common-ml-functions.language import detect_and_translate

translated_text = detect_and_translate("Bonjour le monde!", "en")
print(translated_text)

Audio Enhancement: Use enhance_audio(audio_url, speed_boost, steps) for audio enhancement.

from common-ml-functions.audio import enhance_audio

enhanced_audio_path = enhance_audio("http://example.com/audio.mp3", True, 50)
print(f"Enhanced audio saved at: {enhanced_audio_path}")

Visual question answering: Use visual_question_answering(image_url, prompt) for visual Q&A.

from common-ml-functions.visual import visual_question_answering

answer = visual_question_answering("http://example.com/image.jpg", "What is depicted in this image?")
print(answer)

Contributing!

Please consider contributing to this young and humble project! Email any questions at andere.emi@gmail.com