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CHANGELOG.md

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Version 1.2.0 (Latest Update)

[Release Date]:

December 30, 2023 (Saturday)

[Release Notes]:

  • Introduced a new feature for recipe generation using multi-layer LSTM RNN networks, and PaLM API
  • Added PlaygroundAIs diffusion-based text-to-image model, for 1024x1024 quality image generation
  • Implemented streamlit session to store and persist session states making the web app more dynamic
  • Leveraged responsible AI practices, ensuring the algorithm promotes fair, unbiased ethical results
  • Added feature to display serving sizes, & preparation times for each generated/recommended recipe
  • Enhanced the streamlit user interface and streamlined the interactions for seamless inferencing

[Fixes/Updates]:

  • Implemented multiple performance optimization process, and bug fixes for smoother user experience
  • Refactored the code base to separate recommendation, text generation & image generation program
  • Added onboarding for web app users, implemented preloaders and added streamlit toast notification
  • Updated streamlit's color palette to infuse the vibrance of Generative AI across the application

Version 1.1.0 (Stable Release)

[Release Date]:

October 20, 2023 (Friday)

[Release Notes]:

  • Increased the size of the model's training data from 7,000+ recipes to over 2.2 million+ recipes
  • Integrated the StableDiffusion model and DALL-E 2 to generate images of the recommended recipes
  • Added feature for users to download the recommended recipes as a PDF document for offline access
  • Added feature for users to send recipe mails with PDF attachments to their registered email id
  • Expanded the ingredients list from 600, to over 20,000 ingredients for the user's to choose from

[Fixes/Updates]:

  • Updated recommendation model to replace the CBoW algorithm with feature space matching algorithm
  • Added new data preprocessing methods & updated the existing techniques to enable multiprocessing

Version 1.0.0 (Stable Release)

[Release Date]:

June 22, 2023 (Thursday)

[Release Notes]:

  • Developed a recipe recommendation system using a 2-layer CBoW model on TF/IDF and mean emeddings
  • Used training dataset with 7,000+ recipes collectd from various different culinary traditions
  • Added feature for authenticated users to send emails with recipes to their registered email ids
  • Added authentication feature for new users to register and existing users to signup for the app
  • Added feature for all users to rate the recipe recommendations to evaluate the model performance