Accommodation Finder using RAG

A Gradio-based chatbot application designed to help users find apartments. It leverages a Retrieval-Augmented Generation (RAG) pipeline implemented using LangChain to provide apartment suggestions based on mimicked scraped data from real estate website due to terms of service restrictions.

Key Features:

User Input:

Users interact with a chat-based interface to ask about available apartments , specifying any preferences they might have (e.g., bedrooms, budget).

Dynamic Response Generation:

The application dynamically retrieves information from a Chroma-based vector store, powered by OpenAI embeddings, to provide relevant apartment listings.

The results are presented in two stages:

A brief summary that directly addresses the user's preferences.

A well-formatted table containing details such as apartment name, number of bedrooms, rent, location, and availability.

Real-time Interaction:

The chatbot delivers responses in real-time, making it easy for users to quickly find and evaluate available accommodation options.

Custom Prompting:

A custom prompt is employed to ensure that the output is clear, relevant to the user’s needs, and neatly formatted with both a description and tabular data.

Scraped Data Integration:

Apartment listings are retrieved from scraped data format, enhancing the application's ability to provide up-to-date and accurate suggestions.

Skills:

#RAG #LangChain #Gradio #OpenAI_API #WebScraping #Python