A framework for benchmarking embedding models in hybrid search scenarios (BM25 + vector search) using Weaviate.
Simple RAG system powered by Milvus.
Enterprise Legal AI for India — RAG-powered research, contract analysis & document drafting built for 1.67M advocates. No hallucinations. Indian corpus. Indian law.
A simple hybrid search Flask application that integrates traditional full-text (lexical/BM25) search with semantic (neural sparse embeddings) search. It also provides autocomplete functionality.
EduPilot is an intelligent course assistant built for Indiana University students. It answers questions across four graduate courses — AML, ADT, STAT, and LLM — using a seven-stage multi-agent RAG pipeline that retrieves directly from course lecture slides and materials, cites every claim and verifies its own answers, and refuses to hallucinate.
🔍 Benchmark embedding models in hybrid search with Weaviate. Evaluate MRR@K, Hit@K, latency, and memory using your data or MTEB datasets.
LocalRAG is a privacy-focused RAG application for interacting with documents and SQL databases using natural language. It supports PDF, DOCX, TXT, Markdown, and CSV files, with hybrid search, embeddings, Qdrant, reranking, and local Ollama LLMs.
A 3-stage Information Retrieval engine leveraging Elasticsearch, BERT embeddings, and RRF to implement a robust Hybrid Search strategy for EU Research Projects.
Hybrid BM25-powered search & DB management toolkit for PostgreSQL/pgvector with LangChain integration
A production-ready Retrieval-Augmented Generation (RAG) system for semantic search over product reviews.
Enterprise AI Knowledge Assistant built using Azure AI Foundry, Azure OpenAI, Azure AI Search, FastMCP and Model Context Protocol (MCP).
A multi-turn agentic dialogue system built on hybrid dense-sparse retrieval, hierarchical agent coordination, and rubric-based evaluation. Designed for real-world deployment with FastAPI serving, streaming responses, and full observability
Hybrid semantic + BM25 search system for natural language recruiter queries. Matches candidates to jobs using sentence-transformers, ChromaDB, and rank_bm25.
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