README.md

metadata

title: AI Project
emoji: 👾
colorFrom: yellow
colorTo: pink
sdk: gradio
sdk_version: 5.22.0
app_file: app.py
pinned: false
short_description: Chat bot with RAG for LittleJS game engine

TowardsAI Course final project

By Eoin McGrath eoin.mcg@gmail.com

Title

Game dev tutor focusing on LittleJS framework

Overview

Data gathered from offical docs and github repo source. Processed and generated embeddings stored in Chroma DB. Evaluation scripts and data provided. Reranker used to improve generated answers.

Optional Extras

1. Implement streaming responses.
2. The app is designed for a specific goal/domain that is not a tutor about AI: designed for a specific javascript based game engine
3. You have shown evidence of collecting at least two data sources beyond those provided in our course: fetch_docs.py = output stored in ./data/littlejs_docs.csv fetch_repo.py = output stored in ./data/littlejs_repo.csv 4 There’s code for RAG evaluation in the folder, and the README contains the evaluation results: eval_generate_dataset.py = generates synthetic question context pairs eval_process_dataset.py = evaluation results based on above questions eval_results.txt = sample saved results
4. Use a reranker in your RAG pipeline. It can be a fine-tuned version (your choice): uses LLMRerank postprocessor