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Rx Data Science and Artificial Intelligence
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Semantic Chunks for RAG

In order to abide by the context window of the LLM , we usually break text into smaller parts / pieces which is called chunking. LLMs, although capable of ...

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RAG Evaluation and Meta-Evaluation with GroUSE

This tutorial introduces GroUSE, a framework for evaluating Retrieval-Augmented Generation (RAG) pipelines, focusing on the final stage: Grounded ...

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Deep Evaluation of RAG Systems using deepeval

This code demonstrates the use of the deepeval library to perform comprehensive evaluations of Retrieval-Augmented Generation (RAG) systems. It ...

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Simple RAG with Llamaindex

This code implements a basic Retrieval-Augmented Generation (RAG) system for processing and querying PDF document(s). The system uses a pipeline that ...

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Simple RAG (Retrieval-Augmented Generation) System

This code implements a basic Retrieval-Augmented Generation (RAG) system for processing and querying PDF documents. The system encodes the document ...

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Simple RAG (Retrieval-Augmented Generation) System for CSV Files

This code implements a basic Retrieval-Augmented Generation (RAG) system for processing and querying CSV documents. The system encodes the document ...

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Simple RAG (Retrieval-Augmented Generation) System for CSV Files

This code implements a basic Retrieval-Augmented Generation (RAG) system for processing and querying CSV documents. The system encodes the document ...

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Semantic Chunking for Document Processing

This code implements a semantic chunking approach for processing and retrieving information from PDF documents, first proposed by Greg Kamradt and ...

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Self-RAG: A Dynamic Approach to Retrieval-Augmented Generation

Self-RAG is an advanced algorithm that combines the power of retrieval-based and generation-based approaches in natural language processing. It ...

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RAG System with Feedback Loop

This system implements a Retrieval-Augmented Generation (RAG) approach with an integrated feedback loop. It aims to improve the quality and relevance ...

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Reranking Methods in RAG Systems

Reranking is a crucial step in Retrieval-Augmented Generation (RAG) systems that aims to improve the relevance and quality of retrieved documents. It ...

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Reranking Methods in RAG Systems

Reranking is a crucial step in Retrieval-Augmented Generation (RAG) systems that aims to improve the relevance and quality of retrieved documents. It ...

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Reliable-RAG

The "Reliable-RAG" method enhances the traditional Retrieval-Augmented Generation (RAG) approach by adding layers of validation and refinement to ...

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Relevant Segment Extraction (RSE)

Relevant segment extraction (RSE) is a method of reconstructing multi-chunk segments of contiguous text out of retrieved chunks. This step occurs ...

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RAPTOR: Recursive Abstractive Processing and Thematic Organization for Retrieval

RAPTOR is an advanced information retrieval and question-answering system that combines hierarchical document summarization, embedding-based ...

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Query Transformations for Improved Retrieval in RAG Systems

This code implements three query transformation techniques to enhance the retrieval process in Retrieval-Augmented Generation (RAG) systems: ...

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