The community members are discussing the routing mechanism used by the LlamaIndex library. The original poster wonders if LlamaIndex uses a semantic router or still relies on LLM generations for tool-use decisions, noting that semantic routers are faster.
The comments reveal that LlamaIndex has an embedding-based router, but some community members express concerns about the reliability and configuration complexity of embedding-based routing. They suggest that using an LLM for routing may be more generalizable, though slower.
The community members also discuss the similarities and differences between the LlamaIndex router and the semantic router mentioned in the original post, noting that they both use embeddings and may have similar performance characteristics.
There is no explicitly marked answer in the comments, but the discussion provides insights into the routing mechanisms used by LlamaIndex and the trade-offs between different approaches.
Hi Everyone, Does llama index use semantic router to route queries or it still uses LLM generations to make tool-use decisions, semantic router is lot faster i guess, wondering if llama index has integration to it https://github.com/aurelio-labs/semantic-router
Its the same idea, so the performance will be similar yes. Semantic router lets you give multiple examples though, while the llama index router uses embeddings based on a single description
