Context Search Engine is an AI-powered semantic document search platform built for learning, experimentation, and real-world prototyping. It demonstrates the full lifecycle of modern vector-based search — from document ingestion to chunking, embedding, indexing, and contextual query matching.

• Updated Dec 24, 2025
• Python

A highly efficient, isomorphic, full-featured, multilingual text search engine library, providing full-text search, fuzzy matching, phonetic scoring, document indexing and more, with micro JSON state hydration/dehydration in-browser and server-side.

• Updated Jul 21, 2023
• TypeScript

dead simple document index and search, nothing fancy

• Updated Mar 28, 2024
• Python

This repository highlights my learning journey in building Retrieval-Augmented Generation (RAG) pipelines using DeepSeek on Lightning AI, covering document ingestion, retrieval, and integration with generative AI. It showcases fine-tuning, evaluation, and optimization for accurate open-domain QA and knowledge management.

• Updated Jan 24, 2025
• Jupyter Notebook

Educational Document Base prototype to perform queries based on similarity and dissimilarity measures of documents to which stemming, lemmantization and latent semantic indexing was applied.

• Updated Aug 25, 2021
• Jupyter Notebook

An AI-powered solution for efficient document querying. It uses Llama Index for vector-based indexing and OpenAI's GPT to interpret natural language queries, providing accurate search results.

• Updated Sep 21, 2024
• Jupyter Notebook

The chatbot built as a part of Hackathon 2024 (Microsoft & Sword) competition on MS Azure AI Studio. The chatbot aims to assist HR with frequently used questions issue

• Updated Jan 6, 2025
• Python

Universal utility for indexing documents into a vector database for RAG and semantic search.

• Updated Dec 13, 2025
• Python

Programa que simula um algoritmo de indexação de documentos similar ao do Google. Ele é capaz de identificar ocorrências de termos em arquivos TXT.

• Updated Feb 10, 2023
• Python

The purpose of this project is also to compare the efficiency and performance of two different methods for handling search operations: the inverted index and the term-document matrix

• Updated Jul 30, 2024
• Python

Developed an AI-powered document intelligence platform for educators with Google Drive integration, enabling seamless processing of diverse document formats. Leveraged Qdrant vectorization and AzureOpenAI gpt-4o-mini to create a robust question answering system with optimized search capabilities, transparent citations, and direct source navigation.

• Updated Apr 17, 2025
• Python

LLM-powered knowledge base indexer that builds a growing semantic layer of keywords and relationships for intelligent document search

• Updated Oct 30, 2025
• Python

Lightweight Python information-retrieval toolkit that builds and queries a document index, performs content retrieval and user profiling, provides ranking-analysis visualizations, and includes a Flask web UI with demos.

• Updated Oct 21, 2025
• Python

Atlas - Enterprise document indexing plugin for OpenClaw. Vectorless RAG using PageIndex with async indexing, incremental updates, and smart caching. Scales from 10 to 5000+ documents. Perfect for financial reports, legal docs, technical manuals, and research papers.

• Updated Feb 9, 2026
• TypeScript

Implementation of Document Indexing as part of COMP34711: NLP

• Updated Aug 5, 2023
• Jupyter Notebook

A real-time Personal Document Intelligence system that utilizes Java filesystem monitoring and Python RAG orchestration with Google Gemini to automatically index and semantically query local documents

• Updated Feb 5, 2026
• Python

Open Source Search Engine with built-in web/document crawler and an indexing method.

• Updated May 4, 2024
• C++

It is a search engine that uses json files as corpus of data.

• Updated Feb 18, 2024
• Python