AI Engines

This is playground and utils libraries for AI stuff.

It is not a framework, but a collection of useful tools and examples. It's not a pinned repo, not a featured and supported, and in general violates all the best practices of software development. But it's a good place to start. At the beginning and the end of all, this repo contains stuff that I mentioned in my articles, thus, refer to my blog posts first.

What you can find here

• examples - a collection of examples of AI projects, including:
  • image_generation - see article first, this is example of image generation with LLM via API
  • speak_and_hear - see article first, this is LLM speech recognition and TTS example
  • test_generator - see article first, this is QA automatic tests generator
  • llm_api_comparison - see article first, this is LLM API comparison for 2023
• utils - a collection of useful tools for AI development, in general them all of them used in example projects:
  • article_extractor - limbo for article extraction from web pages
  • audio_recorder - a simple audio recorder, used in speech recognition / TTS examples
  • discord_interations - a simple discord interactions wrapper, used to fire self-bot commands
  • discord_watcher - a simple discord watcher bot, used to watch for messages in discord channels and get content (urls)
  • llm_timer_wrapper - a simple timer wrapper for LLM APIs, used for benchmarking of models
  • logger_config - general logger
  • other - all that doesn't fit in other files, i.e. env checkers
  • page_retriever - web page retriever and parser
  • transcriptors - custom transcriptors wrappers for speech recognition
  • translators - custom translators for text translation wrappers
  • tts - custom TTS engines wrappers

Running up that hill

Once again, refer to my blog posts first. If you do so, you may try exec some top-level scripts from parent directory:

git clone git@github.com:wwakabobik/ai_engines.git  # clone this repo
cd ai_engines  # go to repo directory
# It's highly recommended to use python 3.11+ and venv
python -m venv venv  # create virtual environment
source venv/bin/activate  # activate virtual environment
pip install -r requirements.txt  # install dependencies
# then you may run some top-level script, like:
PYTHONPATH=. python -m examples.test_generator.generator_test
PYTHONPATH=. python -m examples.speak_and_hear.test_gpt 

Well, in most cases you need to create cred file to run examples, so, create creds.py under examples directory and fill it with your credentials, like:

# -*- coding: utf-8 -*-
"""Creds file"""
oai_token = "alksjdlksajlkdjlajiouoieuoqijnc"
oai_organization = "slkahkdjshakjhfkjafs"
cohere_token = "saklljlkdjsaldjljasldjlsak"
llama_token="asiuoiduaosudouasosuoduoqoihicdhzch"
ablt_token="sadhsakhdajskhaskdkja"
claude_token="dkshjjsdhkjdshkjhskj"
openweathermap_appid = "salkdjaslkjldasjlkdasl"
midjourney_cookie="skjaklshkldfhkjsahjhfkjbkfsa"

GL&HF!