HomeMatch is an AI-powered real estate application designed to revolutionize the way potential buyers interact with property listings. By leveraging cutting-edge technologies like Large Language Models (LLMs) and vector databases. HomeMatch creates personalized property search experiences tailored to the buyers unique preferences. This project utilizes Retrieval-Augmented Generation (RAG) to combine semantic search and natural language generation, allowing for customized, engaging property descriptions that resonates with users.
- Personalized Property Listings: Generates natural, buyer-specific descriptions based on user preferences.
- Semantic Search: Matches buyer preferences to relevant property listings using a vector database.
- Customizable Input: Accepts preferences in natural language, making the interface intuitive for non-technical users.
- Accurate and Relevant Results: Ensures property details are factually correct while emphasizing aspects that matter most to the buyer.
- Scalable Data: Handles large datasets of real estate listings using vector-based search.
- Large Language Model (LLM): OpenAI's GPT-4o mini for generating descriptions and handling user input.
- Vector Database: ChromaDB for storing and performing semantic searches on property listing embeddings.
- LangChain: For efficient integration of LLMs and vector embeddings.
- Clone the repository.
- Install dependencies:
bash pip install -r requirements.txt - Set your OpenAI API key in .env file
- Run the application:
python main.pyorpython3 main.py