Integrate the newly added vector index into LangChain to enhance your RAG applications — Since the advent of ChatGPT six months ago, the technology landscape has undergone a transformative shift. ChatGPT’s exceptional capacity for generalization has diminished the requirement for specialized deep learning teams and extensive training datasets to create custom NLP models. This has democratized access to a range of NLP tasks, such…

LLMs occasionally mess up the relationship direction in Cypher statements, but we can fix that — In the time of LLMs, it is becoming increasingly popular to implement Retrieval-Augmented Generation (RAG) applications, where you feed additional information to an LLM at query time to increase its ability to generate valid, accurate, and up-to-date answers. …

Understanding data points through the context of their relationships — This is the fourth blog post of Neo4j’s NaLLM project. We started this project to explore, develop, and showcase practical uses of these LLMs in conjunction with Neo4j. As part of this project, we will construct and publicly display demonstrations in a GitHub repository, providing an open space for our…

Retrieve information that spans across multiple documents — This is the third blog post of Neo4j’s NaLLM project. We started this project to explore, develop, and showcase practical uses of these LLMs in conjunction with Neo4j. As part of this project, we will construct and publicly display demonstrations in a GitHub repository, providing an open space for our…

OpenAI and VertexAI endpoints are now available as APOC Extended procedures — Probably a day doesn’t go by that you don’t hear about new and exciting things happening in the Large Language Model (LLM) space. …

What are the limitations of LLMs, and how to overcome them — This is the second blog post of Neo4j’s NaLLM project. We started this project to explore, develop, and showcase practical uses of these LLMs in conjunction with Neo4j. As part of this project, we will construct and publicly display demonstrations in a GitHub repository, providing an open space for our…

How to optimize prompts for Cypher statement generation to retrieve relevant information from Neo4j in your LLM applications — Last time, we looked at how to get started with Cypher Search in the LangChain library and why you would want to use knowledge graphs in your LLM applications. In this blog post, we will continue to explore various use cases for integrating knowledge graphs into LLM and LangChain applications…

With the LangChain library, you can conveniently generate Cypher queries, enabling an efficient retrieval of information from Neo4j. — If you have developed or plan to implement any solution that uses Large Language Models, you have most likely heard of the LangChain library. LangChain library is the most widely known Python library used to develop applications that use LLMs in one or another capabilities. It is designed to be…

Will we still need to learn query languages in the future? — Large language models have great potential to translate a natural language into a query language. For example, some people use GPT models to translate text to SQL, while others use GPT models to construct SPARQL queries. I prefer exploring how to translate natural language to Cypher query language. Context-Aware Knowledge Graph Chatbot With GPT-4 and Neo4j Learn how to implement a chatbot that bases its answers on the information retrieved from a graph database.medium.com