{"id":"aurelio-labs-semantic-router","name":"semantic-router","af_score":59.0,"security_score":56.0,"reliability_score":31.2,"what_it_does":"semantic-router is a Python decision/routing layer that selects a route (e.g., intent, task, tool-use path) by embedding the incoming utterance(s) into a vector space and matching them against route utterance embeddings, returning the best-matching Route (or None if no match). It supports multiple encoder backends (e.g., OpenAI, Cohere, Hugging Face, FastEmbed, local/HF+Torch/llama-cpp) and can integrate with vector indexes such as Pinecone and Qdrant; it also advertises multimodal routing via optional vision/multimodal paths.","best_when":"You want low-latency, embedding-based routing of user queries to predefined flows, and you can provide (or run) an embedding model backend (cloud or local).","avoid_when":"You need a standard HTTP/hosted service interface (REST/GraphQL/gRPC) or strict enterprise governance features are not otherwise handled by your own deployment.","last_evaluated":"2026-03-29T18:04:31.418919+00:00","has_mcp":false,"has_api":false,"auth_methods":["Environment-variable API keys for encoder backends (e.g., OPENAI_API_KEY, COHERE_API_KEY) as shown in README"],"has_free_tier":false,"known_gotchas":["Authentication and network calls depend on the selected encoder backend; misconfigured API keys will fail at runtime.","Routing can return None when no route matches (as shown in README), so downstream agents must handle missing route results.","Using remote encoders ties behavior/cost to external services and potential latency spikes unless you provision local models."],"error_quality":0.0}