List: RAG | Curated by Harold Conley

Jun 23, 2024
50 stories
2 saves
RAG
Justin Laughlin
in
Towards Data Science
Analyzing Unstructured PDF Data w/ Embedding Models and LLMsHow to turn PDFs into actionable insights
Jun 15
1
Jun 15
1
Madhav Thaker
(Part 2) Build a Conversational RAG with LangChain and Mistral-7BExplore building a RAG for intuitive follow-up questions in conversations, leveraging context for natural dialogue flow.
Jan 3
2
Jan 3
2
Lam Hoang
in
Artificial Intelligence in Plain English
How Chunk Sizes Affect Semantic Retrieval ResultsAn in-depth introduction to the concept of “chunking” and its relevance when working with Large Language Models (LLMs).
Mar 11
7
Mar 11
7
Wenqi Glantz
in
Towards Data Science
12 RAG Pain Points and Proposed SolutionsSolving the core challenges of Retrieval-Augmented Generation
Jan 30
16
Jan 30
16
Leonie Monigatti
in
Towards Data Science
Intro to DSPy: Goodbye Prompting, Hello Programming!How the DSPy framework solves the fragility problem in LLM-based applications by replacing prompting with programming and compiling
Feb 27
14
Feb 27
14
Andrei
in
LlamaIndex Blog
Querying a network of knowledge with llama-index-networksThe main premise behind RAG is the injection of context (or knowledge) to the LLM in order to yield more accurate responses from it. As…
Feb 27
5
Feb 27
5
Ilia Gyrdymov
Google Engine from scratch: PageRank algorithm in Dart/FlutterHi all,
Jul 5, 2022
Jul 5, 2022
Mixpeek
Search the contents of DWG files with Python using OCRAutoCAD has dominated the Computer Aided Design (CAD) space since the 1970’s. They created a file format for saving and sharing CAD files…
Nov 21, 2022
Nov 21, 2022
Ana Preciado
The Power Of Embedding Clustering: Leveraging Open AI to Analyze Common Themes in Recent High…What can movie text data tell us about the different film industry market clusters, and how can we use it to develop a cluster based…
Aug 7, 2023
Aug 7, 2023
Wayan Wardana
in
Level Up Coding
3 Query Expansion Methods Implemented Using Langchain to Improve Your RAGThere are multiple method that we can use to improve the capability of Retrieval Augmented Generation or RAG, one of the method is called…
Jan 25
2
Jan 25
2
Jesko Rehberg
Azure AI SearchRetrieve And Rank Relevant Information
Feb 1
Feb 1
Dr. Ernesto Lee
Building Semantic Search with Azure Cognitive Search and Python on Google Colab so You Can Talk to…Introduction
Sep 29, 2023
Sep 29, 2023
Sannidhi Siva
Vector Search in Azure Cognitive SearchAs per Microsoft Learn
Jul 20, 2023
Jul 20, 2023
Akshay Kokane
Step-by-Step Guide to Integrate Azure Cognitive’s Vector Search in Your ChatGPT-like App — Part 2This is continuation to part 1, where I discussed pros and cons of Semantic and Vector Search…
Sep 3, 2023
1
Sep 3, 2023
1
Guodong (Troy) Zhao
in
Bootcamp
How to improve RAG results in your LLM apps: from basics to advancedImprove your RAG quality and latency in your LLM app
Jan 22
9
Jan 22
9
Masato Naka
Enhancing LangChain’s RetrievalQA for Real Source LinksIntroduction
Jan 10
Jan 10
Ankush k Singal
in
AI Advances
Unleashing the Power of Semantic Chunking: A Journey with LlamaIndexAnkush k Singal
Jan 18
5
Jan 18
5
Wayan Wardana
in
AI Advances
These Are the 3 Langchain Functions I Used to Improve My RAGThere are three retriever functions in Langchain that I usually use to improve my Retrieval Augmented Generation (RAG). In this article, I…
Jan 19
1
Jan 19
1
Nuno Bispo
in
Django Unleashed
Leveraging Unstructured.io and MistralAI for Advanced PDF Data ProcessingTogether, Unstructured.io and MistralAI form a potent combination, turning the complex task of processing PDFs into a streamlined…
Dec 19, 2023
2
Dec 19, 2023
2
Pierre Guillou
unstructured library | Get the JSON and HTML versions of any PDF (legal, financial, medical…)…This post provides an operational response to the objective of extracting structured content from PDFs, including tables (notebook).
Dec 15, 2023
3
Dec 15, 2023
3