AmirLayegh/airbnb-semantic-search
A semantic search system for Airbnb listings in Stockholm, built with Superlinked and Qdrant. It leverages multi-attribute vector search and Retrieval-Augmented Generation (RAG) to enhance search accuracy, embedding different data types (e.g., price, description) with specialized models. Powered by FastAPI and Streamlit.
This tool helps real estate or hospitality professionals quickly find suitable rental properties based on natural language descriptions and specific criteria. You input a search query like "cozy apartments with a view under $150 with rating above 4.5" and it outputs a list of relevant property listings. It is designed for anyone needing to efficiently filter and discover properties from a large dataset, such as rental agents, travel planners, or property managers.
No commits in the last 6 months.
Use this if you need to search and filter a dataset of rental listings using conversational language combined with structured constraints like price or rating.
Not ideal if you're looking for a simple keyword search, or if your property data lacks detailed attributes for semantic matching.
Stars
24
Forks
8
Language
Python
License
MIT
Category
Last pushed
Jul 01, 2025
Commits (30d)
0
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curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/AmirLayegh/airbnb-semantic-search"
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