Semantic Router is a superfast decision-making layer for LLMs and agents. Instead of waiting for slow LLM generations to make tool-use decisions, it uses semantic vector space to route requests based on meaning.

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What is Semantic Router?

Semantic Router enables:

  • Faster decisions: Make routing decisions in milliseconds rather than seconds
  • Lower costs: Avoid expensive LLM inference for simple routing tasks
  • Better control: Direct conversations, queries, and agent actions with precision
  • Full flexibility: Use cloud APIs or run everything locally

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Key Features

  • Simple API: Set up routes with just a few lines of code
  • Dynamic routes: Generate parameters and trigger function calls
  • Multiple integrations: Works with Cohere, OpenAI, Hugging Face, FastEmbed, and more
  • Vector store support: Integrates with Pinecone and Qdrant for persistence
  • Multi-modal capabilities: Route based on image content, not just text
  • Local execution: Run entirely on your machine with no API dependencies

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Version 0.1 Released

Semantic Router v0.1 is now available! If you’re migrating from an earlier version, please see our migration guide.

​
Getting Started

For a quick introduction to using Semantic Router, check out our quickstart guide.

​
Execution Options

Semantic Router supports multiple execution modes:

  • Cloud-based: Using OpenAI, Cohere, or other API-based embeddings
  • Hybrid: Combining local embeddings with API-based LLMs
  • Fully local: Run everything on your machine with models like Llama and Mistral

​
Resources

Semantic Router is a superfast decision-making layer for LLMs and agents. Instead of waiting for slow LLM generations to make tool-use decisions, it uses semantic vector space to route requests based on meaning.

​
What is Semantic Router?

Semantic Router enables:

  • Faster decisions: Make routing decisions in milliseconds rather than seconds
  • Lower costs: Avoid expensive LLM inference for simple routing tasks
  • Better control: Direct conversations, queries, and agent actions with precision
  • Full flexibility: Use cloud APIs or run everything locally

​
Key Features

  • Simple API: Set up routes with just a few lines of code
  • Dynamic routes: Generate parameters and trigger function calls
  • Multiple integrations: Works with Cohere, OpenAI, Hugging Face, FastEmbed, and more
  • Vector store support: Integrates with Pinecone and Qdrant for persistence
  • Multi-modal capabilities: Route based on image content, not just text
  • Local execution: Run entirely on your machine with no API dependencies

​
Version 0.1 Released

Semantic Router v0.1 is now available! If you’re migrating from an earlier version, please see our migration guide.

​
Getting Started

For a quick introduction to using Semantic Router, check out our quickstart guide.

​
Execution Options

Semantic Router supports multiple execution modes:

  • Cloud-based: Using OpenAI, Cohere, or other API-based embeddings
  • Hybrid: Combining local embeddings with API-based LLMs
  • Fully local: Run everything on your machine with models like Llama and Mistral

​
Resources