The neo4j-generation template is designed to convert plain text into structured knowledge graphs.
This template pairs LLM-based knowledge graph extraction with Neo4j AuraDB, a fully managed cloud graph database.
You can create a free instance on [Neo4j Aura](https://neo4j.com/cloud/platform/aura-graph-database?utm_source=langchain&utm_content=langserve).
By using OpenAI's language model, it can efficiently extract structured information from text and construct a knowledge graph in Neo4j.
When you initiate a free database instance, you'll receive credentials to access the database.
This package is flexible and allows users to guide the extraction process by specifying a list of node labels and relationship types.
This template is flexible and allows users to guide the extraction process by specifying a list of node labels and relationship types.
For more details on the functionality and capabilities of this package, please refer to [this blog post](https://blog.langchain.dev/constructing-knowledge-graphs-from-text-using-openai-functions/).
For more details on the functionality and capabilities of this package, please refer to [this blog post](https://blog.langchain.dev/constructing-knowledge-graphs-from-text-using-openai-functions/).