Memory-Enabled RAG on Your CSV Data
Enhance your data Q&A with contextual memory. This interactive demo builds on a standard Retrieval-Augmented Generation (RAG) flow by enabling the model to remember your previous questions in a single session. Built using GPT + LlamaIndex, it allows more human-like conversations.
💡 Try Asking:
What is the average salary in the Sales department?
Who has the highest performance score?
What about the lowest sales in Q3?
📂 Try with our sample file:
Conversational Memory
Remembers your previous questions and answers within the same session, enabling natural follow-up conversations.
Enhanced RAG
Built on top of standard RAG architecture with memory capabilities for more contextual and accurate responses.
Context-Aware
Understands context from previous interactions to provide more relevant and precise answers to your data queries.
How Memory-Enhanced RAG Works
Upload Your Data
Upload your CSV file containing the data you want to analyze.
Ask Questions
Ask natural language questions about your data using conversational queries.
Context Memory
The system remembers your previous questions and provides context-aware follow-up responses.
Smart Insights
Get accurate, contextual answers that build upon your conversation history for deeper insights.