SLS : Neural Information Retrieval(IR)-based Semantic Search model
A fully interactive domain-specific chatbot implemented using Prolog and PySwip.
An autonomous research agent that synthesizes detailed reports by combining dynamic planning, unsupervised topic discovery (PCA/KMeans) HyDe (hypothetical doc embeddings), and a self-correcting reflexion loop.
Solutions from the Advent of Haystack 2024 event, exploring Haystack framework fundamentals through advanced RAG pipelines and intelligent agents
Project repository for the development of a Question-Answering (QA) information retrieval system fine-tuned on customer queries.
About Twitter Searcher is a search engine which searches documents in the corpus of tweets scrapped from your Twitter homepage. The search engine is the implementation of the Vector Space Model. The tweets are scrapped using selenium and stored in MongoDB as a corpus. MongoDB is a document-based Database System.
Context that works
An information retrieval system for boolean queries, proximity quries and wildcard queries using Inverted indexing, Biword indexing, positional indexing and soundex indexing.
A complete IR system.
Moogle!, A basic System of Information Retrieval. First Programming Project
SpeciFic is an NLP fanfiction recommender for AO3 that compares Knowledge Graph and semantic-embedding (FAISS) retrieval approaches in an automated evaluation framework.
Real-time SaaS support platform with a self-improving knowledge base — hybrid retrieval pipeline (Atlas Search + Gemini embeddings), tag normalisation via fuzzy/vector matching, and a feedback loop that re-ranks articles automatically from agent and customer votes.
Complex Query Synthesis for Enhanced Information Retrieval
Rank based information retrieval system. Ranking done based on Tf-Idf scores of documents and queries
Library Management System is an application which refers to library systems which are generally small or medium in size. It is used by librarian to manage the library using a computerized system where he/she can add new books and Page sources.
RAG-PDF Assistant — A simple Retrieval-Augmented Generation (RAG) chatbot that answers questions using custom PDF documents. It uses HuggingFace embeddings for text representation, stores them in a Chroma vector database, and generates natural language answers with Google Gemini. In this example, the assistant is powered by a few school policy doc
AI-powered customer support bot
Information Retrieval System for text documents.
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