Synergizing RAG and Reasoning: A Systematic Review
By synergizing retrieval mechanisms with advanced reasoning, LLMs can now tackle increasingly complex problems. This paper presents a systematic review of the collaborative interplay between RAG and reasoning, clearly defining "reasoning" within the RAG context.
Новы пост:
Як зрабіць RAG-сістэму без воблака і ключоў —
AI, які разумее твае PDF-кі. Усё лакальна:
phi-4 для эмбэдынгаў, gemma3 для адказаў, Qdrant як база.
Інструкцыя + код + параўнанні
Build your own local RAG with Ramalama and granite model https://medium.com/@nicolabertoli92/build-your-own-local-rag-with-ramalama-and-granite-model-d5d89e612114
#Ramalama #aiml #rag
Citegeist is a free tool that helps you find articles related to a topic you are interested in. You need to seed it by entering the abstract of a relevant article or by uploading a relevant article. Citegeist not only finds related articles, but it generates a short report with info from the related articles also!
Citegeist works by using RAG info retrieval on the arxiv corpus of research papers.
#research #science #2ndOrderSearch
#Citegeist #arxivTools #RAG
Neo4j treibt mit GraphRAG, Vektor-Indizes & Agentic RAG die #KI-Entwicklung voran. Ob #LangChain, #LlamaIndex, #SpringAI oder #VertexAI – das neue Python-Paket und das Model Context Protocol (MCP) verknüpfen Graphdaten nahtlos mit #LLM-Anwendungen.
#Neo4j #GenAI #RAG #GraphQL #Cypher #VectorSearch #AgenticAI
https://www.bigdata-insider.de/leistungssprung-bei-graph-datenbanken-mit-ki-integration-cloud-skalierung-und-terabyte-graphen-a-2307ed20cfaf562a1a0094b712b5be95/
I finally cobbled all my thoughts about retrieval-augmented generation, or RAG, together in one place. So many people claimed it was so easy, but it's not.
This post is a high level overview of my lessons learned and some suggestions for you if you go down this path. 
Understand RAG at Easter? 
Why not use the time to learn something new — and build your own local PDF chatbot?
Learn how chunking, embeddings and vector search work in practice - with LangChain, FAISS, Ollama and Mistral running entirely on your machine (no API key required).
Perfect for beginners - here's the full guide & GitHub repo 
step-by-step guide: https://bit.ly/3EfOHB9 GitHub Repo: https://bit.ly/3EtqYgK
If you're trying to figure out how the heck vector searches work (for retrieval-augmented generation, or RAG), this set of slides will get you up to speed incredibly quickly.
https://pamelafox.github.io/my-py-talks/pgvector-python/
Thanks to @pamelafox for putting this together. 
From #FreeCodeCamp: "How to Build a Local #RAG App with #Ollama and #ChromaDB in the R Programming Language"
https://www.freecodecamp.org/news/build-a-local-rag-app-with-ollama-and-chromadb-in-r/
Want to improve your RAG (Retrieval-Augmented Generation) pipeline?
Our latest blog breaks down four retrieval techniques to boost accuracy, relevance and performance in your GenAI systems.
Read more: https://ter.li/fcr52o
8/9 The 'Goal': Dissemination of IPCC Reports and #climatechange lit using #semantification as a basis. #ClimateKG is aimed at being a service for indexing and publishing. Status: Prototype (PoC) #1: 'IPCC Reports and City Climate Change Plans: Proof of concept prototype - Open Climate Reader' https://semanticclimate.github.io/city-open-climate-reader/ - Currently interfaces are for search and #RAG #LLM - all built on #openscience based #digitalsoveriegn tech. The goal sits off in future, over the horizon - but its we're going
Simplify AI data integration with RamaLama and RAG
https://developers.redhat.com/articles/2025/04/03/simplify-ai-data-integration-ramalama-and-rag
#genai #container #podman #rag
KI-Chatbots & Online-Kataloge?
24. April, 09:00–13:00
Tillmann Scheel (AboutSomethinK/ASK) & Moritz Mutter (VÖBB) erklären:
- Wie RAG Sprachmodelle mit externen Wissensquellen (Bibliothekskatalogen) verknüpft
- Technologiegrenzen: Kontextignoranz, Widersprüche, unpräzise Daten
- KI-Praxistauglichkeit für Datensammlungen
-„Meta-Prompting“-Strategien zur Optimierung von Chatbots
https://dgi-info.de/event/ki-chatbots-zur-erschliessung-von-online-katalogen/
Took a little step outside the comfort zone today and published a blog post in Python.
Here's several ways you can create vector embeddings for all your RAG needs in Python: https://www.datastax.com/blog/how-to-create-vector-embeddings-in-python
Discover how multi-model retrieval augmented generation (#RAG) techniques are revolutionizing AI by integrating text, images, and audio for deeper contextual understanding.
Learn more: https://bit.ly/43Ebf8S
Unlock the power of RAG (Retrieval-Augmented Generation) and learn how to build smarter AI apps with LangChain — practical insights, real-world use cases, and hands-on tips with Kim Wee Teh at #FOSSASIASummit2025
Click here https://youtu.be/9X3ljJjAjqo?si=6ofwoOQWOuanoQgq to watch on the FOSSASIA YouTube channel
#RAG #LangChain #LLM #AI #FOSSASIA
#Podcast Tipp: schöner, Beginner-friendly Einstieg in #MCP, der neue heisse 
nach #RAG in #GenAI: https://podcasts.apple.com/de/podcast/latent-space-the-ai-engineer-podcast/id1674008350?i=1000702137438
Wie kann #KI die Arbeit zivilgesellschaftlicher Organisationen unterstützen?
In unserem nächsten Espresso-Talk am 15. April von 12 bis 12.45 Uhr gibt Jonas aus unserem #CDL-Team eine Einführung in zentrale Begriffe und Konzepte rund um generative Sprachmodelle:
Was sind Large Language Models (#LLM)? Was bedeutet Retrieval-Augmented Generation (#RAG)? Was sind Agents im Zusammenhang mit LLMs? Wie werden LLMs in Informationsangeboten eingesetzt?
Mehr unter: https://community.civic-data.de/s/willkommens-space/calendar/entry/view?id=310
In questo test, in una SERP di #Google in cui compare #AI Overviews, ho preso i contenuti nelle prime 12 posizioni e ho creato un piccolo #RAG usando #LangChain, #Chroma DB e #GPT4o. Inviandolo la query al RAG, ottengo una risposta simile a quella proposta da AI Overviews. 
Chiaramente Google usa anche query correlate ("fan-out") e il Knowledge Graph per espandere i risultati.
