#FAISS
119 related articles
·3 min
Ollama + Qwen-Agent: Building a Local Private AI Assistant — From Deployment to Security Best Practices
A complete guide to building a local private AI assistant with Ollama and Qwen-Agent. Covers RAG knowledge integration, voice interaction, and permission isolation for a secure local AI Agent architecture.
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·3 min
You Don't Always Need a Vector Database for Vector Search — Brute Force Might Be All You Need
In-depth analysis of when brute force vector search beats vector databases. For RAG apps with under a few hundred thousand vectors, brute force offers exact recall, simpler architecture, and easier debugging.
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·3 min
A Guide to Selecting Datasets for RAG Experiments: Evaluating Dense, Sparse, and Hybrid Retrieval
A systematic guide to standardized datasets for RAG retrieval experiments, covering BEIR, MS MARCO, Natural Questions, and TREC benchmarks for dense, sparse, and hybrid retrieval evaluation.
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·5 min
Learn AI Agent Development from Scratch: A 3-Step Practical Path to Get Started Quickly
How to learn AI Agent development from scratch? This article outlines a clear 3-step path: Python crash course, LLM theory & practice, and LangChain framework project implementation.
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·3 min
A Beginner's Guide to AI Agents: Two Learning Paths for Developers and Practitioners
How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.
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·4 min
A Beginner's Guide to AI Agents: Core Principles and Learning Paths Explained
Learn AI Agent core principles from scratch: understand how Agents differ from LLMs, their execution mechanisms, why rule design matters, and find the right learning path for your goals.
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·3 min
From RAG to Agent Tuning: A Complete Guide to Deploying LLM Agents
A deep dive into LLM Agent frameworks covering RAG, Agent core components (tools, memory, planning), and Agent Tuning workflows with cost considerations for production deployment.
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·4 min
A Beginner's Guide to AI Agents: Core Principles and Learning Paths Explained
A beginner's guide to AI Agents: understand core principles, how Agents differ from LLMs, their execution mechanisms, and get tailored learning path recommendations.
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·3 min
Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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·3 min
Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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·3 min
Getting Started with AI Agent Development: A Learning Path from Zero to Deployment
A systematic guide to the complete learning path for AI Agent development—covering prompt engineering, RAG knowledge bases, LangChain & LangGraph, fine-tuning, and multi-agent collaboration.
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·8 min
LangChain Crash Course: A Complete Roadmap from Zero to Agent Development
A systematic roadmap from LangChain and LangGraph to multi-agent development, covering RAG, Tool Calling, MCP, and more, helping developers break into AI app development.
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·7 min
Context Engineering: A Systematic Approach to Stop AI Agents from 'Talking Nonsense'
Context engineering is the core methodology for building efficient AI Agents, covering query enhancement, RAG retrieval, prompt design, memory management, and tool invocation. Master Write, Select, Compress, and Isolate to solve LLM hallucination at its root.
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·6 min
Vue3 from Scratch: A Hands-On Journey to Building an AI Health Monitoring System
A Vue3 beginner tutorial centered on "learn just enough, apply immediately." A three-stage path covers reactivity, Composition API, Element Plus, and data visualization, culminating in an enterprise-grade AI health monitoring system with blood sugar management, RAG consultation, and doctor-patient collaboration.
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Human-Centered AI: Real-World Implemen…
·6 min
Human-Centered AI: Real-World Implementation in Healthcare and Design
An MSR workshop reveals the truth about AI deployment: from a $20 corneal diagnostic device to expert-in-the-loop chatbots, researchers share real-world experiences of AI in healthcare and design within resource-scarce environments.
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·2 min
Dify for Beginners: A Complete Visual Guide to Building RAG Knowledge Bases
A beginner's guide to Dify: build RAG knowledge bases visually with zero coding. Covers agents, workflows, and why private deployment makes Dify ideal for enterprise AI.
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AstrBot: A Deep Dive into the Multi-Pl…
·2 min
AstrBot: A Deep Dive into the Multi-Platform AI Agent Development Framework
AstrBot is an open-source AI Agent framework supporting WeChat, QQ, Telegram and more, with multi-LLM compatibility and plugin extensibility. Full technical breakdown inside.
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·3 min
Don't Start AI Learning with Machine Learning: A Beginner's Guide to the Onion Model
Gaurav Sen reveals the fatal trap in AI learning: starting from ML fundamentals often leads to burnout. Learn the Onion Model approach—RAG, Agents first, Transformers next, math last.
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·3 min
Andrew Ng × Anthropic: A Practical Guide to Claude Code and Its Core Methodology
Andrew Ng and Anthropic's Claude Code course covers RAG development, data analysis, and Figma-to-frontend projects, with deep dives into context management, MCP tools, and CLAUDE.md architecture.
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TurboVec: A Deep Dive into the Rust-Po…
·3 min
TurboVec: A Deep Dive into the Rust-Powered High-Performance Vector Index Library
TurboVec is a Rust-based vector index library powered by TurboQuant, with Python bindings for RAG, semantic search, and AI applications. A deep-dive into its architecture.
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