LLM-based application leveraging LangChain for Retrieval-Augmented Generation (RAG) on imported PDF documents. Enables users to interactively query and converse with PDF content using vector-based retrieval.
DocuQuery is a document querying application that utilizes Retrieval-Augmented Generation (RAG) and the Llama2 model for efficient information retrieval from large documents. This user-friendly tool supports PDF uploads and delivers quick, accurate responses to user queries.
Elara AI is designed to enable seamless conversational AI experiences augmented by your own documents and data sources. Leveraging Retrieval-Augmented Generation, it combines powerful language models with vector search to provide relevant, context-aware answers in real-time chat.
Retrieval-Augmented Generation (RAG) Model for a Question Answering (QA) bot that interacts with financial data, specifically Profit & Loss (P&L) tables extracted from PDF documents.
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