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How to use this RAG AI Teaching assistant on your own data

Step 1 - Collect your videos

Move all your video files to the videos folder

Step 2 - Convert to mp3

Convert all the video files to mp3 by ruunning video_to_mp3

Step 3 - Convert mp3 to json

Convert all the mp3 files to json by ruunning mp3_to_json

Step 4 - Convert the json files to Vectors

Use the file preprocess_json to convert the json files to a dataframe with Embeddings and save it as a joblib pickle

Step 5 - Prompt generation and feeding to LLM

Read the joblib file and load it into the memory. Then create a relevant prompt as per the user query and feed it to the LLM

About

A RAG-based engine that turns video lectures into searchable knowledge. Built with Python, Whisper, and Ollama to help students find exactly what they need in seconds.

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