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# rag

Retrieval augmented generation, or RAG, is an architectural approach that can improve the efficacy of large language model (LLM) applications by leveraging custom data.

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🚀 Build AI Agents from a Prompt — Meet Nexent, the Open-Source Agent Platform
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🚀 Build AI Agents from a Prompt — Meet Nexent, the Open-Source Agent Platform

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3 min read
What Is Vertex AI Agent Memory Bank ?
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What Is Vertex AI Agent Memory Bank ?

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4 min read
Embeddings & Cosine Similarity Explained Simply
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Embeddings & Cosine Similarity Explained Simply

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10 min read
RAG Systems Model (MongoDB)
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RAG Systems Model (MongoDB)

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1 min read
Revolutionizing AI with Retrieval-Augmented Generation (RAG): Architectures, Workflows, and Practical Applications
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Revolutionizing AI with Retrieval-Augmented Generation (RAG): Architectures, Workflows, and Practical Applications

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3 min read
The Hidden Failures in RAG Systems — And How WFGY Fixes Them

The Hidden Failures in RAG Systems — And How WFGY Fixes Them

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3 min read
Towards Lifelong Dialogue Agents via Timeline-based Memory Management

Towards Lifelong Dialogue Agents via Timeline-based Memory Management

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2 min read
Building RAG Applications with LangChain(Part-4)
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Building RAG Applications with LangChain(Part-4)

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5 min read
Schema In, Data Out: A Smarter Way to Mock
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Schema In, Data Out: A Smarter Way to Mock

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6 min read
AI in The Context of Learning
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AI in The Context of Learning

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3 min read
AI Summarization Agent🧾 in 7 minutes! 🔥
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AI Summarization Agent🧾 in 7 minutes! 🔥

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10 min read
🚀 Building an AI Resume Screener with GPT-4 + LangChain + FAISS
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🚀 Building an AI Resume Screener with GPT-4 + LangChain + FAISS

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2 min read
Between Structure and Imagination: What happens when code becomes a sketchpad for ideas.

Between Structure and Imagination: What happens when code becomes a sketchpad for ideas.

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8 min read
How to setup RAG with VectorDB

How to setup RAG with VectorDB

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4 min read
Bổ sung ngữ cảnh cho LLM: Nâng cao độ chính xác và tin cậy cho ứng dụng GenAI
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Bổ sung ngữ cảnh cho LLM: Nâng cao độ chính xác và tin cậy cho ứng dụng GenAI

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10 min read
RAG vs Fine-Tuning: Which One Wins the Cost Game Long-Term?
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RAG vs Fine-Tuning: Which One Wins the Cost Game Long-Term?

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3 min read
Building RAG Applications with LangChain(Part-5)
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Building RAG Applications with LangChain(Part-5)

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3 min read
Beyond Search: How to Chat with Your Documents Using AstraDB Vector Database, Docling and Granite

Beyond Search: How to Chat with Your Documents Using AstraDB Vector Database, Docling and Granite

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15 min read
The Hidden Cost of LangChain: Why My Simple RAG System Cost 2.7x More Than Expected

The Hidden Cost of LangChain: Why My Simple RAG System Cost 2.7x More Than Expected

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7 min read
Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models

Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models

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2 min read
Agent Engineering: Orchestrating and Architecting Intelligent AI Agents

Agent Engineering: Orchestrating and Architecting Intelligent AI Agents

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9 min read
Comprehending RAGs with a keyword search [LLM A1]
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Comprehending RAGs with a keyword search [LLM A1]

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3 min read
10 Best LangChain Alternatives You Must Know in 2025
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10 Best LangChain Alternatives You Must Know in 2025

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6 min read
Evaluate your Prompt- No Guesswork!

Evaluate your Prompt- No Guesswork!

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1 min read
Graphs over Chains - My LangGraph Journey (part-1)
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Graphs over Chains - My LangGraph Journey (part-1)

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3 min read
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