Movie & Book Recommendation System

Welcome to the Movie & Book Recommendation System! This application was developed for the 2024 Hackathon: Assistants-api-llamaindex-mongodb-battle. The primary function of this app is to provide movie and/or book recommendations based solely on the user's description of the movie.

Table of Contents

1. Roadmap
2. Progress

Roadmap

The development of the Movie & Book Recommendation System is divided into the following stages:

1. Data Filtering and Preprocessing:

   • Collection of raw data from reliable sources.
   • Filtering of data to remove any irrelevant information.
   • Cleaning and preprocessing of data to ensure consistency and accuracy.
   • Transformation of data into a format suitable for our machine learning models.

2. RAG Pipeline with LLamaindex, GPT-4, and MongoDB Vector Database:

   • Development of a MongoDB vector database for storing and querying vector representations of data.
   • Implementation of the Retrieval-Augmented Generation (RAG) pipeline.
   • Integration of LLamaindex for efficient data indexing and retrieval.
   • Use of GPT-4 for generating high-quality text based on user input.

3. LLM Testing with TruLens:

   • Evaluation of the Language Learning Model (LLM) using TruLens to ensure its performance and reliability.
   • Identification and rectification of any issues or discrepancies in the LLM.
   • Continuous testing and improvement of the LLM based on user feedback and performance metrics.

Progress

• Data Filtering: #################--: 90%

• DataSet construction: #################: 100%

Run app_ERROR.py.

---

app.py only contains a description of the app.