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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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FalkorDB has integrated with cognee to improve AI-driven knowledge retrieval
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FalkorDB has integrated with cognee to improve AI-driven knowledge retrieval

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1 min read
De Chatbot a Experto Industrial: Construyendo un Asistente Inteligente con Amazon Bedrock
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De Chatbot a Experto Industrial: Construyendo un Asistente Inteligente con Amazon Bedrock

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13 min read
Reflecting on the ORAssistant Project: A Journey of Collaboration and Technical Growth

Reflecting on the ORAssistant Project: A Journey of Collaboration and Technical Growth

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2 min read
Semantic Search Feature

Semantic Search Feature

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5 min read
The ultimate guide to Retrieval-Augmented Generation (RAG)
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The ultimate guide to Retrieval-Augmented Generation (RAG)

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16 min read
How to Create Your Own RAG with Free LLM Models and a Knowledge Base
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How to Create Your Own RAG with Free LLM Models and a Knowledge Base

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7 min read
First step and troubleshooting Docling — RAG with LlamaIndex on my CPU laptop

First step and troubleshooting Docling — RAG with LlamaIndex on my CPU laptop

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5 min read
Customize ChatGPT for Your Codebase : OpenAI
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Customize ChatGPT for Your Codebase : OpenAI

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10 min read
User-Aligned Functions to Improve LLM-to-API Function-Calling Accuracy
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User-Aligned Functions to Improve LLM-to-API Function-Calling Accuracy

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11 min read
How Spring Boot and LangChain4J Enable Powerful Retrieval-Augmented Generation (RAG)

How Spring Boot and LangChain4J Enable Powerful Retrieval-Augmented Generation (RAG)

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3 min read
Large Language Models (LLMs)

Large Language Models (LLMs)

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1 min read
RAG Explained: Tackling the Big Problems in AI
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RAG Explained: Tackling the Big Problems in AI

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4 min read
Get Started with LangChain: A Step-by-Step Tutorial for Beginners
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Get Started with LangChain: A Step-by-Step Tutorial for Beginners

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4 min read
Function-based RAG: Extending LLMs Beyond Static Knowledge Bases
Cover image for Function-based RAG: Extending LLMs Beyond Static Knowledge Bases

Function-based RAG: Extending LLMs Beyond Static Knowledge Bases

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15 min read
RAPTOR: A Novel Tree-Based Retrieval System for Enhancing Language Models – Research Summary
Cover image for RAPTOR: A Novel Tree-Based Retrieval System for Enhancing Language Models – Research Summary

RAPTOR: A Novel Tree-Based Retrieval System for Enhancing Language Models – Research Summary

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2 min read
Understanding RAG and Long-Context LLMs: Insights from the SELF-ROUTE Hybrid Approach
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Understanding RAG and Long-Context LLMs: Insights from the SELF-ROUTE Hybrid Approach

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3 min read
Bolt.new with any LLM, you need to use it

Bolt.new with any LLM, you need to use it

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2 min read
Building RAG-Powered Applications with LangChain, Pinecone, and OpenAI
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Building RAG-Powered Applications with LangChain, Pinecone, and OpenAI

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7 min read
What is Chunk Size and Chunk Overlap
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What is Chunk Size and Chunk Overlap

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3 min read
Rethinking How We Train Customer-Facing AI Agents
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Rethinking How We Train Customer-Facing AI Agents

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1 min read
Extended RaBitQ: an Optimized Scalar Quantization Method
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Extended RaBitQ: an Optimized Scalar Quantization Method

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7 min read
Introducing Composio Tools| Agentic LLMs API Gateway
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Introducing Composio Tools| Agentic LLMs API Gateway

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3 min read
The Ghost of AI Past, Present, and Future
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The Ghost of AI Past, Present, and Future

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9 min read
Faiss with sqlite for RAG

Faiss with sqlite for RAG

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1 min read
Why Chunk Text Before Embedding
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Why Chunk Text Before Embedding

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2 min read
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