BAI657C Generative AI Lab 10

 

Program 10:

Aim:

Build a chatbot for the Indian Penal Code. We'll start by downloading the official Indian Penal Code document, and then we'll create a chatbot that can interact with it. Users will be able to ask questions about the Indian Penal Code and have a conversation with it.

Theory:

A chatbot for the Indian Penal Code (IPC) is built to allow users to interact with legal content in a simple, conversational way. The process begins by obtaining the official IPC document, usually in PDF format. This document is then loaded and divided into smaller text chunks to make processing efficient. Next, these text chunks are converted into vector embeddings, which are numerical representations of text that capture meaning. These embeddings are stored in a vector database (such as FAISS) to enable fast and relevant search.

When a user asks a question, the chatbot converts the query into an embedding and performs a similarity search to find the most relevant sections of the IPC document. The retrieved content is then presented as the answer. Thus, the chatbot enables users to quickly access legal information by combining document processing, embeddings, and intelligent search techniques.

Step 1: Install required libraries for document processing, embeddings, and vector search.

Step 2: Upload the IPC PDF file from the local system into the Colab environment.

Step 3: Import necessary modules for loading documents, splitting text, and creating embeddings.

Step 4: Load the uploaded PDF file and extract its content.

Step 5: Split the document into smaller text chunks for better processing.

Step 6: Convert text chunks into numerical embeddings using a pre-trained model.

Step 7: Store embeddings in a FAISS vector database for efficient similarity search.

Step 8: Define a chatbot function to retrieve relevant IPC sections based on user query.

Step 9: Run an interactive loop to accept user queries and display answers.