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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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How to Implement LLM Grounding for Better Responses
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How to Implement LLM Grounding for Better Responses

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6 min read
Mastering Text-to-SQL with LLM Solutions and Overcoming Challenges
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Mastering Text-to-SQL with LLM Solutions and Overcoming Challenges

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7 min read
How to Implement RAG Chatbots in Your Business
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How to Implement RAG Chatbots in Your Business

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6 min read
RAG on Azure OpenAI
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RAG on Azure OpenAI

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3 min read
Introducing Simba: Bring Your Knowledge into Your AI

Introducing Simba: Bring Your Knowledge into Your AI

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3 min read
Generative AI Cost Optimization Strategies
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Generative AI Cost Optimization Strategies

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2 min read
Automate Email Processing using Event Driven Architecture and Generative AI
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Automate Email Processing using Event Driven Architecture and Generative AI

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3 min read
A multi-head classifier using SetFit for query preprocessing

A multi-head classifier using SetFit for query preprocessing

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1 min read
Hal9: Create and Share Generative Apps

Hal9: Create and Share Generative Apps

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3 min read
AI + Data Weekly 169 for 23 December 2024
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AI + Data Weekly 169 for 23 December 2024

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3 min read
Open-Source LLMs Deserve Code, Not Prompts! (DSPy, Voila!)

Open-Source LLMs Deserve Code, Not Prompts! (DSPy, Voila!)

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3 min read
RAG - Implementing the docs commands
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RAG - Implementing the docs commands

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8 min read
Why LLMs Fall Short: Why Large Language Models Aren't Ideal for AI Agent Applications
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Why LLMs Fall Short: Why Large Language Models Aren't Ideal for AI Agent Applications

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3 min read
Building a Robust RAG System: How to Set Up Ollama and Run DeepSeek R1 Locally
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Building a Robust RAG System: How to Set Up Ollama and Run DeepSeek R1 Locally

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3 min read
I made TypeScript Class Chatbot (every TypeScript class types also can do it)
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I made TypeScript Class Chatbot (every TypeScript class types also can do it)

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5 min read
Safeguarding Your Data When Using DeepSeek R1 In RAG Pipelines - Part 1

Safeguarding Your Data When Using DeepSeek R1 In RAG Pipelines - Part 1

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4 min read
Automating Trip Planning with AI Agents in KaibanJS

Automating Trip Planning with AI Agents in KaibanJS

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2 min read
DeepSeek R1: A New Contender in the World of Large Language Models
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DeepSeek R1: A New Contender in the World of Large Language Models

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3 min read
🏦 Membuat Aplikasi Manajemen Keuangan dengan Python, SQLite, dan LangChain.
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🏦 Membuat Aplikasi Manajemen Keuangan dengan Python, SQLite, dan LangChain.

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4 min read
Beyond RAG: Memobase Unlocks Scalable User Memory for Smarter AI
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Beyond RAG: Memobase Unlocks Scalable User Memory for Smarter AI

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15 min read
DeepSeek: Unlocking Insights Through Advanced Data Analysis

DeepSeek: Unlocking Insights Through Advanced Data Analysis

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4 min read
Building Your First RAG System with Python and OpenAI
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Building Your First RAG System with Python and OpenAI

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4 min read
DeepSeek R1: A New Contender in the AI Space Outshining ChatGPT Premium o1
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DeepSeek R1: A New Contender in the AI Space Outshining ChatGPT Premium o1

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3 min read
Unlocking AI-Powered Conversations: Building a Retrieval-Augmented Generation (RAG) Chatbot

Unlocking AI-Powered Conversations: Building a Retrieval-Augmented Generation (RAG) Chatbot

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4 min read
RAG Integration: DeepSeek’s New BFF in the AI World

RAG Integration: DeepSeek’s New BFF in the AI World

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8 min read
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