Chat-With-Data is a Python-based tool and web interface built on Streamlit, LangChain, and OpenAI’s GPT API. It automatically parses tabular datasets or database schemas and creates an AI agent that understands natural language queries about your data. Under the hood, it chunks large tables, builds an embedding index for semantic search, and formulates dynamic prompts to generate context-aware responses. Users ask questions like “What are the top 5 sales regions this quarter?” or “Show me a bar chart of revenue by category,” and receive answers or interactive plots without writing SQL or pandas code. The platform runs locally or on a server, ensuring data privacy while accelerating exploratory analysis for both technical and nontechnical users.

LangChain is an open-source Python framework designed to accelerate development of AI-powered applications. It provides abstractions for chaining multiple language model calls (chains), building agents that interact with external tools, and managing conversation memory. Developers can define prompts, output parsers, and run end-to-end workflows. Integrations include vector stores, databases, APIs, and hosting platforms, enabling production-ready chatbots, document analysis, code assistants, and custom AI pipelines.