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# vectordatabase

Vector databases are purpose-built databases that are specialized to tackle the problems that arise when managing vector embeddings in production scenarios.

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Growing the Tree: Multi-Agent LLMs Meet RAG, Vector Search, and Goal-Oriented Thinking - Part 2

Growing the Tree: Multi-Agent LLMs Meet RAG, Vector Search, and Goal-Oriented Thinking - Part 2

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10 min read
Vector Databases: their utility and functioning (RAG usage)

Vector Databases: their utility and functioning (RAG usage)

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12 min read
Improve Your Python Search Relevancy with Astra DB Hybrid Search

Improve Your Python Search Relevancy with Astra DB Hybrid Search

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11 min read
VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval

VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval

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1 min read
Postgres vs. Qdrant: Why Postgres Wins for AI and Vector Workloads

Postgres vs. Qdrant: Why Postgres Wins for AI and Vector Workloads

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4 min read
📺 Find the Anime: A Semantic AI Anime Search Tool

📺 Find the Anime: A Semantic AI Anime Search Tool

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4 min read
Creating Your First OpenSearch Dashboard: A Step-by-Step Tutorial

Creating Your First OpenSearch Dashboard: A Step-by-Step Tutorial

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7 min read
Why PostgreSQL Might Be All the Backend You Need: Forget the Kitchen Sink

Why PostgreSQL Might Be All the Backend You Need: Forget the Kitchen Sink

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4 min read
Visual Grounding from Docling!

Visual Grounding from Docling!

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6 min read
Processing data with “Data Prep Kit” (part 2)

Processing data with “Data Prep Kit” (part 2)

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8 min read
Beyond Basic Practice: Creating the JobSage AI Interview Simulator with Gemini & Embeddings

Beyond Basic Practice: Creating the JobSage AI Interview Simulator with Gemini & Embeddings

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5 min read
Build Code-RAGent, an agent for your codebase

Build Code-RAGent, an agent for your codebase

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5 min read
Semantic Search with Spring Boot & Redis

Semantic Search with Spring Boot & Redis

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10 min read
Entendiendo los Embeddings en Inteligencia Artificial

Entendiendo los Embeddings en Inteligencia Artificial

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3 min read
Vector Database Indexing: A Comprehensive Guide

Vector Database Indexing: A Comprehensive Guide

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7 min read
🧭 Part 3: Implementing Vector Search with Pinecone

🧭 Part 3: Implementing Vector Search with Pinecone

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2 min read
Setting up the Pinecone MCP server in your IDE

Setting up the Pinecone MCP server in your IDE

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3 min read
Ingest (almost) any non-PDF document in a vector database, effortlessly

Ingest (almost) any non-PDF document in a vector database, effortlessly

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3 min read
Building a Semantic Meme Search Engine

Building a Semantic Meme Search Engine

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6 min read
Embeddings clustering with Agglomerative Hierarchical Clustering (messy-folder-reorganizer-ai)

Embeddings clustering with Agglomerative Hierarchical Clustering (messy-folder-reorganizer-ai)

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3 min read
Build RAG Chatbot 🤖 with LangChain, Milvus, Mistral AI Pixtral, and NVIDIA bge-m3

Build RAG Chatbot 🤖 with LangChain, Milvus, Mistral AI Pixtral, and NVIDIA bge-m3

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8 min read
Build a RAG Chat App with Firebase Genkit and Astra DB

Build a RAG Chat App with Firebase Genkit and Astra DB

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9 min read
Quick tip: How to Build Local LLM Apps with Ollama, DeepSeek-R1 and SingleStore

Quick tip: How to Build Local LLM Apps with Ollama, DeepSeek-R1 and SingleStore

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2 min read
What Are Embeddings? How They Help in RAG

What Are Embeddings? How They Help in RAG

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3 min read
Graph database vs relational vs vector vs NoSQL

Graph database vs relational vs vector vs NoSQL

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2 min read
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