Agentic RAG with VoyageAI, Gemini and LangGraph
Learn to build an agentic RAG system with LangChain, MyScaleDB, VoyageAI, and Tavily for dynamic Q&A that adapts to real-time data and knowledge base searches.
GenAI
RAGLangChain on LinkedIn: ✒️Kiroku is a multi-agent system that helps you organize and write…
✒️Kiroku is a multi-agent system that helps you organize and write documents Really complex agent (see the diagram below!) that HEAVILY involves a "human in…
LangGraphImplementing GraphReader with Neo4j and LangGraph
‼️ Important
GraphRAG
Neo4jlangchain-ai/open-canvas: 📃 A better UX for chat, writing content, and coding with LLMs.
📃 A better UX for chat, writing content, and coding with LLMs. - langchain-ai/open-canvas
UX/UIWeekend webinar to watch on-demand: Python Package: Accelerate with Knowledge Graphs.
❇️ Quickly build knowledge graphs from unstructured text documents
Easily implement knowledge graph retrievers combining graph traversals and vector…
— Neo4j (@neo4j)
SCIPE - Systematic Chain Improvement and Problem Evaluation
Related to LangChain
Evaluation
RAG Context Refinement Agent — LlamaIndex - Build Knowledge Assistants over your Enterprise Data
LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.
Multi-Agent Orchestrator framework
Manage multiple AI agents and handle complex conversations
Agents
Tutorial
Deep Dive
Building Blocks of LLM Report Generation: Beyond Basic RAG — LlamaIndex, Data Framework for LLM Applications
LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models (LLMs).
microsoft/generative-ai-for-beginners: 21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/ - microsoft/generative-ai-for-beginners
Creating a LLM-as-a-Judge That Drives Business Results –
A step-by-step guide with my learnings from 30+ AI implementations.
How to implement a ReAct flow using LangGraph (Studio)
This post will explain how you can implement complex agentic ReAct flows using LangGraph and LangGraph Studio. Basic Python knowledge is…
LlamaIndex on LinkedIn: We’re publishing 2 full-length tutorial videos showing you how to… | 12 comments
We’re publishing 2 full-length tutorial videos showing you how to implement various agentic RAG techniques - adding LLM layers to reason over inputs and post… | 12 comments on LinkedIn
Multi-Agent Workflow for Research 🧑🔬 and Powerpoint Generation 🎨
This weekend, check out one of the most comprehensive tutorials we’ve seen on building an e2e research agent with nested workflows for 1) research, and 2) generating a Powerpoint deck with human-in-the-loop.…
— LlamaIndex 🦙 (@llama_index)
Solutions
Ok, I’ll bite: What’s ColPali?
(And why should anyone working with RAG over PDFs care?)
ColPali makes information retrieval from complex document types - like PDFs - easier.
Information retrieval from PDFs is hard because they contain various components:
Text, images, tables,…
— Leonie (@helloiamleonie)
Multimodal RAGColPali is changing the game for PDF retrieval by eliminating the need for OCR and chunking methods 🚀
Inspired by ColBERT’s success with text, ColPali splits an image of a document into patches, which are then processed through a vision LLM called PaliGemma. The embeddings for…
— Victoria Slocum (@victorialslocum)
RAG Developer Attention! 🔔 Docling is a new library from that efficiently parses PDF, DOCX, and PPTX and exports them to Markdown and JSON. It supports advanced PDF understanding and seamless integration with and .
TL;DR:
🗂️ Parses numerous…
— Philipp Schmid (@_philschmid)
Neo4j Graph Store - LlamaIndex
How to add node retry policies
Build language agents as graphs
Agent Authentication with Arcade AI and LangGraph
Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.
MongoDB
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Create a Neo4j GraphRAG Workflow Using LangChain and LangGraph
Create a Neo4j GraphRAG workflow using LangChain and LangGraph, combining graph queries, vector search, and dynamic prompting for advanced RAG.
In this situation, we need to parse the question into the desired number of subqueries that perform a necessary task.
Low-Hanging Fruit for RAG Search - jxnl.co
Explore low-hanging fruit strategies to enhance your RAG search systems and improve user experience with practical techniques.
Using LangGraph and Graphiti — Zep Documentation
Building an agent with LangChain's LangGraph and Graphiti