redis-developer/LLM-Recommender
Use OpenAI, Redis, and streamlit to recommend hotels using Large Language Models
This tool helps travel planners or individuals find hotels in the US that match specific preferences. You input desired states, cities, and positive or negative qualities you're looking for, and it provides hotel recommendations along with the actual customer reviews that support each suggestion. It's designed for anyone looking to quickly narrow down hotel options based on detailed, natural language criteria.
No commits in the last 6 months.
Use this if you are a travel agent or an individual traveler who needs to quickly find hotel options that fit very specific, descriptive criteria like 'pet-friendly' or 'quiet rooms' and want to see the reviews that led to the recommendation.
Not ideal if you need to filter by more advanced criteria such as price range, specific amenities, or geographic proximity beyond state/city, or if you require handling of identically named hotels in different locations.
Stars
28
Forks
5
Language
Python
License
—
Category
Last pushed
Apr 15, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/redis-developer/LLM-Recommender"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
ovshake/bookstore-copilot
A PoC of using Weaviate + DSPy to make a BookStore CoPilot
sharmashobhit/simgen-ssg
A blog recommendation engine built for text driven static sites
yyigitturan/Semantic-Book-Recommender-System
AI-powered semantic book recommendation system enabling natural-language book discovery using...
cannox227/Taylor-s-Tune
Mood-driven music recommendations with Large Language Models
rabiaedayilmaz/advertisement-suggestion-system
Advertisement suggestion engine using graph + text embeddings for accurate, multilingual...