Best of Neo4j — July 2024

  1. 1
    Article
    Avatar of tdsTowards Data Science·2y

    Everything You Need to Know About Graph Databases & Neo4j

    Graph databases, with Neo4j being the most prominent example, offer significant advantages for modeling and accessing relationship data compared to traditional relational databases. They are particularly useful in complex scenarios such as uncovering connections in the Panama Papers, managing airport operations, and optimizing public transport routes. Neo4j, known for its ease of use, performance, and extensibility, has evolved significantly since its inception and now supports various practical applications while catering to developers with tools like the Cypher query language.

  2. 2
    Article
    Avatar of mlnewsMachine Learning News·2y

    The Neo4j LLM Knowledge Graph Builder: An AI Tool that Creates Knowledge Graphs from Unstructured Data

    Neo4j LLM Knowledge Graph Builder is an AI tool that transforms unstructured data into detailed knowledge graphs using advanced machine learning models like OpenAI, Gemini, and Llama3. It supports various data formats including PDFs, web pages, and video transcripts. The tool allows users to customize the extraction schema and offers advanced querying techniques such as GraphRAG. It can be deployed on Google Cloud Run or locally using Docker Compose and is integrated with the LangChain framework for enhanced data retrieval.

  3. 3
    Article
    Avatar of scottlogicScott Logic·2y

    Building a Multi Agent Chatbot Without LangChain

    Developers are working on InferGPT, a personalized chatbot that knows its users and offers tailored responses. Instead of relying on LangChain, the team opted for React, FastAPI, and Neo4j to create a multi-agent system where each agent solves specific tasks using a large language model (LLM) and various tools. The backend design emphasizes minimizing LLM overuse, with traditional strategies connecting agents. This project aims to enhance the chatbot's engagement by inferring user preferences and involves iterative testing and future improvements in user interaction and agent creation.

  4. 4
    Article
    Avatar of tdsTowards Data Science·2y

    Integrating Microsoft GraphRAG into Neo4j

    Learn how to integrate Microsoft GraphRAG with Neo4j to store and analyze data, along with implementing local and global retrievers using LangChain and LlamaIndex. Steps include configuration of knowledge graph extraction, importing data into Neo4j, and setting up retrievers. Uses dataset 'A Christmas Carol' to demonstrate the process. Code available on GitHub.

See all Neo4j archives