Elasticsearch Search Labs Projects

Overview

This repository contains three Elasticsearch implementations demonstrating different search approaches, built following the official Elasticsearch Search Labs Tutorial.

🔍 Projects

1. Full-Text Search

Traditional keyword-based search implementation

Features:

• ✅ Basic search queries with relevance scoring
• 📄 Pagination (from/size)
• 🔍 Filtering with boolean queries
• 📊 Faceted search with aggregations
• ⚡ Performance optimized settings

Directory: full-text-search/

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2. Vector Search (k-NN)

Vector similarity search implementation

Features:

• 🤖 Dense vector embeddings (sentence-transformers)
• 🔢 k-NN search
• 🔄 Hybrid vector+keyword search
• 🏎️ Optimized for production workloads

Directory: vector-search-knn/

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3. Semantic Search (ELSER)

Context-aware search using ELSER v2

Features:

• 🧠 ELSER v2 model deployment
• 💡 Semantic query expansion
• 🔄 Hybrid semantic+keyword search

Directory: semantic-search-elser/

🛠️ Technical Implementation

Requirements

Component	Requirement
Elasticsearch	8.x+ recommended
Python	3.8+
Dependencies	See requirements.txt

set up guide

• follow the project setup in Elasticsearch Search Labs Tutorial.
• replace the files by the files in this repo and u re free to go