In Knowledge Graphs for RAG, our latest short course, you’ll explore how knowledge graphs work, how to build with them, and create better retrieval augmented generation applications.
You’ll build a knowledge graph of text documents from scratch, write advanced Cypher queries to retrieve relevant information from the graph and format it for inclusion in your prompt to a large language model, and much more.
Hello everyone,
I’ve encountered an issue while exploring the “Knowledge Graphs for RAG” course by deeplearning.ai, specifically with the genai.vector.encode function used for vector embeddings. This feature, as it turns out, is only available in the Neo4J Enterprise Edition. You can see the detailed exchange on my GitHub issue here: https://github.com/neo4j/docker-neo4j/issues/489 .
This limitation could hinder our practical application of the course’s teachings, especially for those without access to the Enterprise version. It’s a significant concern for learners looking to fully engage with the course content on a hands-on level.
I believe addressing this accessibility issue could greatly enhance our learning experience. Perhaps, as a community, we can convey the importance of making such tools available in the community editon to Neo4j.
Best regards,
Joris
