Streamlit AI Laptop Recommender -- 2

I want to put a complete, web-ready AI expert system online that suggests the best laptop for a user based on a few quick questions. The core of the project is a rule-based engine built with Experta in Python and wrapped in a Streamlit interface. Scope of work • Create or refine the rule base so that recommendations place the strongest weight on RAM and CPU, while still considering GPU, storage, OS and intended usage. • Design a simple, clean Streamlit front end—no clutter, just concise inputs and an easy-to-read results panel. • Load and preprocess a laptop data set (I can supply one, or you can extend it) and keep it in a Pandas-friendly format. • Return a ranked list of laptops with a brief rationale for each choice. Deliverables 1. Fully commented Python code (Experta rules, data processing, Streamlit app). 2.

requirements

.txt and concise setup guide so I can deploy with a single command. 3. A short video or screenshots that demonstrate the user flow from start page to final recommendation. Acceptance criteria – The app launches locally with streamlit run app.py. – Selecting different RAM / CPU combinations clearly changes the ranking order. – Page load and rule execution stay under two seconds on a mid-range machine. If you have prior work with rule-based systems, Streamlit, or laptop recommender tools, that will help us hit the ground running. Let me know your timeline and any clarifying questions—looking forward to collaborating!