Retrieval-Augmented Generation (RAG) chatbot focuses on The Americans with Disabilities Act (ADA) standards, with the goal of providing precise, actionable guidance on ADA design standards.

The ADA-RAG chatbot is designed specifically to field queries related to ADA standards, delivering exact sections, chapters, and bullet points that guide architects, designers, and compliance officers. This tool does not stray from its primary function; if asked about unrelated topics, it maintains focus by not providing an answer, emphasizing its specialized nature. The ADA-RAG chatbot stands as a prime example of how targeted technological solutions can streamline complex information retrieval, making compliance more straightforward and accessible.

Technical Specifications

• RAG Process: data loading, splitting, embedding, and data storing.

• Hosting: VM instance in the cloud for dependable access and scalability.

• Environment: Dockerized image on Linux for reliability and easy updates.

• LLM: Google Gemini for LLM and text embedding.

• Database: Pinecone vectorstore database.

• Debug and Monitor: Langsmith