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RAG & Vector Databases
Implement RAG systems, vector databases, and semantic search that give your applications perfect recall.
Latest in RAG & Vector Databases
September 19, 2025Optimization
EmbeddingGemma: Google’s 308M On-Device Multilingual Embedding Model for Privacy-Preserving AI
Google’s EmbeddingGemma packs 308M parameters into a powerful on-device embedding model, supporting 100+ languages for offline AI, RAG, and semantic search.
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June 16, 2025LLMs
Multilingual Chatbot Tutorial: RAG + SUTRA Integration Guide
Build a multilingual chatbot that pulls answers from PDFs or threads using Retrieval-Augmented Generation (RAG) and the SUTRA model by TWO Platforms. This tutorial walks you through creating your own AI assistant in Hindi, Bengali, Spanish, and more.
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March 20, 2025Tools
How to Build a General-Purpose LLM Agent?
Building a general-purpose LLM agent involves selecting the right model, managing memory, structuring control logic, and integrating tools. Frameworks like LangChain and ReAct enhance flexibility. Fine-tuning prompts and optimizing execution improve performance across tasks.
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January 04, 2025LLMs
TxtAI Semantic Search and LLM Workflows
Semantic search redefines how we find information by focusing on meaning, not keywords. txtai, an open-source platform, combines embeddings with LLMs to power smart search and workflows. Learn how to build intuitive systems for FAQs, document search, and more in this comprehensive guide!
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January 02, 2025Optimization
Qdrant: Vector Search and Semantic Matching
Unlock the power of Qdrant, a cutting-edge vector database for AI applications. Learn to store, search, and manage high-dimensional data for tasks like semantic search, recommendations, and more. This guide dives deep into setup, querying, visualization, and real-world use cases! 🚀
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December 28, 2024LLMs
Pinecone: Scalable Vector Database for AI Applications
Pinecone is a scalable vector database optimized for high-dimensional data, enabling efficient similarity searches for AI applications like recommendation systems and semantic search. Its real-time capabilities and advanced features make it a powerful tool for managing unstructured data at scale.
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December 24, 2024LLMs
Milvus: Unlocking the Power of Vector Databases
Milvus, an open-source vector database, powers AI applications like recommendation systems and similarity search. This guide covers setting up Milvus, creating collections, inserting data, and performing searches with detailed steps.
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December 17, 2024LLMs
ChromaDB : Efficient Vector Database for Embeddings
ChromaDB is a powerful vector database designed to handle embedding-based data storage and retrieval. It enables efficient similarity search and content-based querying for multimodal data, including text, images, and more.
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