Learn how to use Langtrace with Neo4j GraphRAG for Retrieval Augmented Generation with knowledge graphs
Neo4j GraphRAG enables developers to build graph retrieval augmented generation (GraphRAG) applications using the power of Neo4j and Python. As a first-party library, it offers a robust, feature-rich, and high-performance solution, with the added assurance of long-term support and maintenance directly from Neo4j.Here’s how to use it with Langtrace:
With Langtrace, the following operations are automatically traced:Knowledge Graph Building:
-Document ingestion and processing
-Entity extraction and relationship creation
-Vector embedding generationSearch and Retrieval:
Vector similarity search operations
Subgraph extraction for context
Retrieved document chunks
LLM Generation:
Prompt construction with retrieved context
Model completion generation
Response processing
View all these trace details in the Langtrace dashboard: