With the LangChain library, you can conveniently generate Cypher queries, enabling an efficient retrieval of information from Neo4j. By Tomaz Bratanic.
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 modular, allowing us to use any LLM in any available modules, such as chains, tools, memory, or agents.
Further in the article:
- What is a knowledge graph
- Setting up Neo4j environment
- Knowledge Graph Cypher Search
Graph databases are an excellent tool for retrieving or analyzing the connections between various entities like people and organizations. In this blog post, we looked at a simple shortest path use case, where the number of relationships and the sequence of relationship types is unknown beforehand. These types of queries are virtually impossible in a vector database and could also be quite complicated in a SQL database. Nice one!
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