Chat with CSV App using LangChain Agents and Streamlit

Imagine being able to chat with your CSV files, asking questions and getting quick insights, this is what we discuss in this article on how to build a tool to achieve above using LangChain agents and Streamlit. By building a chat interface that allows users to interact with their data using natural language, we can democratise data access. This tool helps non-technical users to ask questions about their data and get instant answers. It also speeds up the data exploration process for analysts and developers, allowing them to focus on more complex tasks.

LangChain and Agents

LangChain is a powerful framework that facilitates the creation of LLM powered applications. It provides tools to connect language models with various data sources and APIs. One of its key features is the concept of agents that are developed to perform specific tasks. In this application, we will use a specific type of agent “create_pandas_dataframe_agent” designed to interact with pandas dataframes. This allows the agent to understand the structure and content of the CSV file and…