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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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IndexIVFFlat y IndexIVFPQ

IndexIVFFlat y IndexIVFPQ

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4 min read
FalkorDB vs Neo4j

FalkorDB vs Neo4j

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2 min read
Exploring RAG: Discover How LangChain and LlamaIndex Transform LLMs?

Exploring RAG: Discover How LangChain and LlamaIndex Transform LLMs?

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2 min read
CommunityKG-RAG: Leveraging Community Structures in Knowledge Graph for Advanced RAG in Fact-Checking

CommunityKG-RAG: Leveraging Community Structures in Knowledge Graph for Advanced RAG in Fact-Checking

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1 min read
PDF chat with source highlights

PDF chat with source highlights

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1 min read
Create a Smart RAG App with LangChain and Streamlit

Create a Smart RAG App with LangChain and Streamlit

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21 min read
Understanding Retrieval-Augmented Generation (RAG) with OpenAI

Understanding Retrieval-Augmented Generation (RAG) with OpenAI

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1 min read
Building a Document Retrieval & Q&A System with OpenAI and Streamlit

Building a Document Retrieval & Q&A System with OpenAI and Streamlit

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6 min read
RAG Chatbot with Amazon Bedrock & LangChain

RAG Chatbot with Amazon Bedrock & LangChain

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4 min read
AIM Weekly for 04Nov2024

AIM Weekly for 04Nov2024

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5 min read
Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMs

Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMs

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1 min read
Are LLMs Still Lost in the Middle? 46:25

Are LLMs Still Lost in the Middle?

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1 min read
Building a Perplexity-like Open Source AI Search with SWIRL

Building a Perplexity-like Open Source AI Search with SWIRL

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4 min read
Retrieval-Augmented Generation (RAG): A Developer's Guide 🚀

Retrieval-Augmented Generation (RAG): A Developer's Guide 🚀

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2 min read
Serverless LLM Chatbot Using Your Custom Data - built with Langtail and Qdrant

Serverless LLM Chatbot Using Your Custom Data - built with Langtail and Qdrant

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5 min read
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