How do you trust AI when it extracts data from documents?

That’s been one of the biggest blockers to using AI in high-stakes business settings. If you can’t trace where the information came from… it’s hard to rely on it.

💥 Enter LlamaExtract — a new tool from LlamaIndex that extracts data with citations.

Now when AI pulls out key insights from a document, you can see exactly where it came from.

Read more here: https://www.llamaindex.ai/blog/get-citations-and-reasoning-for-extracted-data-in-llamaextract

#AI #GenAI #GenerativeAI #LlamaIndex

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/

Join me in-person or online as we apply lessons learned about AgenticRAG tomorrow evening. We have 3 presentations planned showing some custom agents we have coded. #AgenticAI, #DeepLearning #MachineLearning #AgenticRAG #LlamaIndex

https://www.meetup.com/deep-learning-adventures/events/306500825/

Интеграция DeepEval для тестирования LlamaIndex Workflow

Тестирование сложных систем, таких как LlamaIndex Workflow, включающих несколько шагов, извлечение данных и генерацию текста с помощью LLM, является нетривиальной задачей. Стандартные методы тестирования не всегда могут оценить семантическое качество и релевантность генерируемых ответов. DeepEval предоставляет набор инструментов и метрик, специально разработанных для оценки LLM-приложений, что делает его подходящим решением для тестирования LlamaIndex Workflow. Давайте разберем два подхода к интеграции DeepEval с LlamaIndex Workflow:

https://habr.com/ru/articles/897634/

#llamaindex #workflow #deepeval

🚀 Dive into the world of multi-agent orchestration with LlamaIndex's AgentWorkflow! 🧠📈 Learn how it simplifies complex scenarios through an easy-to-understand example. Check out my latest article!
#DataScience #AI #MachineLearning #DeepLearning #LlamaIndex
https://www.dataleadsfuture.com/diving-into-llamaindex-agentworkflow-a-nearly-perfect-multi-agent-orchestration-solution/

LangChain vs LlamaIndex: проектируем RAG и разбираемся, что выбрать для вашего проекта

Сегодня it-сообщество предлагает большое количество любопытных инструментов для создания RAG-систем. Среди них особенно выделяются два фреймворка — LangChain и LlamaIndex. Как понять, какой из них подходит лучше для вашего проекта? Давайте разбираться вместе!

https://habr.com/ru/companies/raft/articles/875758/

#llamaindex #langchain #llm #rag

Ich will mal ein paar #GenAI #RAG Tests machen und habe überlegt, mit welchem mir bekannten Korpus ich das machen könnte. Nachdem ab Dienstag erstmal dystopische Zeiten bevorstehen, habe ich mich für "Jonas, Der letzte Detektiv" entschieden (https://de.wikipedia.org/wiki/Der_letzte_Detektiv) entschieden, das habe ich in meiner Jugend immer Donnerstag Abend in Bayern 2 gehört 😎

Prozess: Download > Transkript mit #Whisper -> Vorbereitung mit #Llamaindex

GraphRAGでポケモン図鑑の構築に挑戦【LlamaIndex × Neptune 】
https://qiita.com/TKG_KM/items/42c31a852470ae4d28db?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #AWS #bedrock #Neptune #Streamlit #LlamaIndex

LlamaIndexでGraphRAGを作って、Bedrockのナレッジベースと精度比較！
https://qiita.com/har1101/items/a02d274cfb0c964d4e14?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #AWS #bedrock #LlamaIndex #KnowledgeBaseForAmazonBedrock #GraphRAG

🔥 Docling: AI-powered document processing! 🔥
🤯 PDFs & DOCXs in your AI workflow? Docling makes it easy! Converts to markdown & JSON for RAG and more. Blazing fast! 🚀

https://youtu.be/zSCxbqgqeJ8?si=mede5eJL_iGRFwAJ

#AI #Docling #DocumentProcessing #OpenSource #RAG #LlamaIndex #Efficiency #Workflows

Reverse engineering LlamaIndex has been a fascinating dive into understanding how its Workflow processes are structured to handle dynamic data retrieval and integration seamlessly. At its core, a LlamaIndex Workflow orchestrates the interaction between indexes, queries, and retrieval logic, ensuring efficient and context-aware results. By analyzing its modular design, I found that each task—whether building an index or querying it—is highly decoupled, enabling scalability and customization. The workflow’s use of adaptive heuristics and stateful operations allows it to fine-tune results in real-time while handling diverse data sources. This design not only ensures flexibility but also showcases how workflows in LlamaIndex intelligently manage complexity in knowledge retrieval tasks. Understanding these processes provides valuable insights for building robust, modular AI systems. #LlamaIndex #ReverseEngineering #AIWorkflows #KnowledgeRetrieval

Virtuoso Open Source (VOS) 7.2.14 is out!

Our high-performance, multi-model #VirtuosoRDBMS supports:

• Relational tables & graphs
• #SQL, #SPARQL & #GraphQL
• Seamless AI integration w/ #LangChain & #LlamaIndex via #HTTP, #ODBC, or #JDBC

🧵Read on for links etc..

🚀 Comprehensive Guide to Building with #Groq API

🔧 Key Components:
• Complete examples for building chatbots, RAG systems & #SQL applications using #LangChain, #LlamaIndex & #DuckDB
• Integration tutorials with popular tools like #Streamlit, #Portkey, #JigsawStack & #E2B
• Ready-to-use #Replit examples for quick experimentation with different #LLM implementations
• Step-by-step guides for setting up #CodeGPT in VSCode with #Groq

💡 Featured Implementations:
• Text-to-SQL applications with JSON mode & function calling
• Presidential speeches RAG with #Pinecone
• Stock market analysis using #Llama3 function calling
• Newsletter summarizer using #Composio
• #CrewAI machine learning assistant

🛠️ Perfect for developers looking to leverage Groq's lightning-fast inference speeds in production applications.

📖 Full documentation & examples available at: https://github.com/groq/groq-api-cookbook

Learn how to build AI RAG apps with the ObjectBox LlamaIndex Integration using Google's Gemini in this hands-on tutorial from Shubham Panchal

https://shubham0204.github.io/blogpost/programming/objectbox-llamaindex

#localAI #vectordatabase #edgeAI #llamaindex #RAG

🧠 #LlamaCloud è un ambiente cloud che permette di rendere usabile #LlamaIndex attraverso un'interfaccia web. In poche parole permette di creare sistemi #RAG in modo più semplice. Attualmente è in versione alpha, ma lascia intuire applicazioni potenti.
⚙️ L'immagine è un esempio di una pipeline RAG multimodale basata su dati complessi non strutturati, che consente di analizzare, indicizzare, interrogare elementi visivi in slide deck di marketing, contratti legali, report finanziari, ecc..

#AI

🧠 #LlamaParse è un nuovo progetto in grado di elaborare informazioni sui documenti, comprendendo anche elementi visuali e tabelle.
💡 Supporta documenti in qualunque formato: PDF, docx, pptx, xlrx, HTML.
👉 Il sistema si integra direttamente con #LlamaIndex.
⚙️ Lo schema custom ha ancora qualche problema, ma è una versione beta che promette molto bene.

🔗 Il progetto: https://github.com/run-llama/llama_parse

#AI #GenAI #GenerativeAI  #IntelligenzaArtificiale #LLM

話題のGraphRAGにAWSで挑戦しよう！（LlamaIndexとNeptuneに入門）
https://qiita.com/minorun365/items/a62dec701bef17cf7562?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #AWS #bedrock #Neptune #LlamaIndex #GraphRAG

🧠 #Opik è un nuovo sistema open source per il tracciamento e la valutazione delle applicazioni basate sui #LLM.
👉 Permette di tenere traccia di tutte le interazioni, e si interfaccia nativamente con #OpenAI, #LangChain, #LlamaIndex, #Ollama, e molti altri sistemi.
👉 Consente di individuare facilmente se il modello introduce informazioni fuori contesto, e di confrontare versioni diverse dell'applicazione, fino alla produzione.
🔗 Il progetto: https://github.com/comet-ml/opik

#AI #GenAI #GenerativeAI 

LlamaIndexとNeo4jでGraphRAGを作る（勝手にPANKRATION 2024延長線）
https://qiita.com/moritalous/items/d76bb199b865b746309b?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #neo4j #OpenAI #bedrock #LlamaIndex #GraphRAG

RAGの検索を評価するranxを使ってみた
https://dev.classmethod.jp/articles/evaluating-rag-retrieve-with-ranx/

#dev_classmethod #RAG #AI #OpenAI #Amazon_Bedrock #LlamaIndex #AIチャットボット #生成AI