MeiliSearch
I’ll help you understand Meilisearch and show you how to integrate it with a web app for AI agents to search content. Let me first search for current information about Meilisearch.
Now I’ll create a comprehensive guide showing how to use Meilisearch with a web app to enable AI agents to search content. I’ll build a complete example for you.
Now let me create a complete working React application that demonstrates this:
Perfect! I’ve created a complete implementation of Meilisearch with AI Agents for web search. Here’s what you have:
📦 Files Created
1. Complete Guide (18KB)
Comprehensive documentation covering:
What Meilisearch is and why it’s powerful
Architecture overview
Setup instructions (Docker, Homebrew, direct install)
Complete backend implementation with Node.js/Express
Frontend React implementation
Semantic search with embeddings
Best practices and deployment strategies
2. React Component (18KB)
Beautiful, production-ready React component featuring:
✨ Modern UI with Tailwind CSS
🤖 AI Conversational mode (powered by Claude)
🔍 Direct search mode
📊 Real-time stats dashboard
🌐 URL indexing interface
📱 Responsive design
3. Backend Server (11KB)
Complete Express.js server with:
RESTful API endpoints
Meilisearch integration
Claude AI integration for conversational search
Web scraping & content extraction
Bulk indexing capabilities
Error handling & logging
4. Setup Script (5KB)
One-command setup that:
Checks Docker installation
Starts Meilisearch container
Creates project structure
Generates package.json files
Creates environment templates
5. Architecture Diagram (1.6KB)
Visual representation of the system architecture
🚀 Quick Start
Option 1: Automated Setup
bash setup.shOption 2: Manual Setup
# 1. Start Meilisearch
docker run -d -p 7700:7700 getmeili/meilisearch:latest
# 2. Clone the backend code and install
npm install express meilisearch @anthropic-ai/sdk axios cheerio cors dotenv
# 3. Set your Claude API key
export ANTHROPIC_API_KEY="your-key-here"
# 4. Run the server
node server.js🎯 Key Features
Meilisearch offers lightning-fast search with results in under 50ms, hybrid search combining semantic and keyword approaches, AI-powered conversational search through a new /chat endpoint, typo tolerance, and built-in RAG capabilities
What makes this special:
Hybrid Search: Combines AI semantic understanding with traditional keyword matching
Real-time: Index content and search instantly
Conversational: Ask questions naturally, get intelligent answers
Fast: Sub-50ms search response times
Easy: Simple REST API, works out of the box
💡 How It Works
User Query → React Frontend → Express Backend → Meilisearch
↓
Claude AI (optional)
↓
Smart Response with SourcesIndex Phase: Web content is scraped and stored in Meilisearch
Search Phase: User queries are sent to Meilisearch for fast retrieval
AI Phase (optional): Claude analyzes results and generates conversational answers
Display: Results shown with sources and citations
🔧 API Endpoints
POST /api/ai-search- Search with optional AI conversationPOST /api/index-url- Index a single URLPOST /api/bulk-index- Index multiple URLsGET /api/stats- Get indexing statisticsDELETE /api/clear- Clear all documents
🎨 Example Use Cases
Documentation Search: Index your docs, let users ask questions
Content Discovery: Search blog posts, articles, research papers
Customer Support: Build a knowledge base with AI-powered answers
Research Tool: Index academic papers and query them conversationally
Product Search: E-commerce with intelligent product recommendations
📚 Technologies Used
Meilisearch - Fast, typo-tolerant search engine
Claude AI - Intelligent response generation
React - Modern frontend framework
Express.js - Backend API server
Cheerio - Web scraping
Tailwind CSS - Beautiful UI
This is a production-ready implementation that you can deploy immediately or customize for your specific needs. The combination of Meilisearch’s speed and Claude’s intelligence creates a powerful search experience! 🎉
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