Dominik PolzerinTowards Data Science17 (Advanced) RAG Techniques to Turn Your LLM App Prototype into a Production-Ready SolutionA collection of RAG techniques to help you develop your RAG app into something robust that will lastJun 2628Jun 2628
Justin LaughlininTowards Data ScienceAnalyzing Unstructured PDF Data w/ Embedding Models and LLMsHow to turn PDFs into actionable insightsJun 151Jun 151
Sjoerd TiemensmaHow I build my own Perplexity on Telegram with Function Calling GPT-4o (No-Code)How to build your own research assistant with Make.com, RapidAPI, using GPT-4o, with function calling!Jun 102Jun 102
ZillizHow to build a Retrieval-Augmented Generation (RAG) system using Llama3, Ollama, DSPy, and MilvusApr 281Apr 281
Bhargob DekainLevel Up CodingLangGraph, FastAPI, and Streamlit/Gradio: The Perfect Trio for AI DevelopmentLearn how to build and deploy AI applications quickly and efficiently with this powerful tech stack. It helps to test the app locally…Jun 184Jun 184
Fabio MatricardiinGenerative AIChatbot cheat code: build your AI assistant running a HUGE llm without spending a penny — Part…Gradio_client, Python and Streamlit are your secret trick for an AI assistant with Billion of parameters.. and it is free!May 19May 19
Fabio MatricardiinGenerative AILlama.cpp one man band! Embeddings + LLM for a full RAG stackWe can really do everything with llama.cpp. Check out how to create a full RAG application for free, locally on your PC. No GPU required!Jun 161Jun 161
Shuyi YanginTowards Data ScienceBuild your own RAG and run it locally on your laptop: ColBERT + DSPy + StreamlitTutorial for GenAI beginners: let’s build a very simple RAG (Retrieval Augmented Generation) system locally, step-by-step.Mar 135Mar 135
Ala Eddine GRINEinThe Deep HubRAG chatbot powered by Langchain, OpenAI, Google Generative AI and Hugging Face APIsIntroductionFeb 133Feb 133
Ankush k SingalinAI AdvancesUnifying RAG Frameworks: Harnessing the Power of Adaptive Routing, Corrective Fallback, and…Ankush k SingalApr 241Apr 241
Benedict Neoinbitgrit Data Science PublicationBuild an AI Chatbot with MistralAI + StreamlitChat with your docs RAG + embeddings with MistralAI.Mar 283Mar 283
DataStaxinBuilding Real-World, Real-Time AIBuilding a Wikipedia Chatbot with Astra DB, LangChain, and VercelHow DataStax built a natural language search interface for Wikipedia using AstraDB Vector, LangChain, and Vercel.Jan 301Jan 301
Dr. Leon EversberginTowards Data ScienceHow to Build a Local Open-Source LLM Chatbot With RAGTalking to PDF documents with Google’s Gemma-2b-it, LangChain, and StreamlitMar 3115Mar 3115
Plaban NayakinThe AI ForumRAG on Complex PDF using LlamaParse, Langchain and GroqRetrieval-Augmented Generation (RAG) is a new approach that leverages Large Language Models (LLMs) to automate knowledge search, synthesis…Apr 712Apr 712
Heiko HotzinTowards Data ScienceRAG vs Finetuning — Which Is the Best Tool to Boost Your LLM Application?The definitive guide for choosing the right method for your use caseAug 24, 202323Aug 24, 202323
Vishal RajputinAIGuysRAG 2.0: Retrieval Augmented Language ModelsRAG 2.0 shows the true capabilities of Retrieval Systems and LLMsApr 169Apr 169
