Intelligent document assistant using Langchain
-
Updated
Jan 4, 2026 - Jupyter Notebook
Intelligent document assistant using Langchain
An AI-powered legal document analysis system built using Retrieval-Augmented Generation (RAG) to understand and answer questions from Indonesian court decision documents. This project enables users to explore legal cases, retrieve relevant historical court decisions, and generate context-aware answers based on retrieved legal documents.
Semantic research paper search engine using Sentence Transformers and FAISS for fast, intelligent, and context-aware paper retrieval.
A custom Information Retrieval (IR) system that searches and ranks documents from multiple datasets using TF-IDF, Embeddings, and Hybrid representations with natural language queries.
Add a description, image, and links to the embadding topic page so that developers can more easily learn about it.
To associate your repository with the embadding topic, visit your repo's landing page and select "manage topics."