agent-as-a-router
The official implementations of Agent-as-a-Router: Agentic Model Routing for Coding Tasks.
What is it?
What it is
Agent-as-a-Router (ACRouter) is an agentic model routing implementation designed for coding tasks that optimizes the tradeoff between performance and cost.
Why it exists
It exists to provide a reproducible framework for agentic model routing, offering a way to route programming problems to different backend models based on task complexity to maximize performance per dollar spent.
Who should use it
AI engineers building agentic workflowsDevelopers looking to optimize LLM cost-performance tradeoffsResearchers studying model routing for coding tasksDevOps engineers implementing gateway-level model routingUsers of Claude Code or Codex looking for intelligent model switching
Who should avoid it
Users looking for a simple LLM wrapper without routing logicDevelopers who do not want to manage model/provider configurationsUsers who cannot use Python/Conda environments
How it works
A quick walkthrough in plain English
How agent-as-a-router works
Step 1 of 3
You interact with it
Open agent-as-a-router, send a request, or connect it to your stack.
Features
Advantages
- Optimizes the balance between model performance and operational cost
- Provides reproducible research implementations and reference outputs
- Highly extensible with support for custom benchmarks and models
- Ready-to-use demos for both API-based and CLI-based workflows
- Includes comprehensive datasets and pricing matrices for evaluation
Disadvantages
- Requires specific environment setup (Conda, Python 3.11)
- Live verification may require additional dependencies like Docker or Apptainer
- Complexity in configuration for custom inference-time integration
Installation
native
conda create -n acrouter python=3.11 -y conda activate acrouter python -m pip install --upgrade pip setuptools wheel python -m pip install -r requirements.txt python -m pip install -e . python -m unittest discover -s tests
FAQ
What is the primary purpose of ACRouter?
ACRouter is an agentic model routing implementation designed for coding tasks. It routes tasks to different backend models to optimize the tradeoff between performance and cost.
Do I need API keys to reproduce the main benchmark results?
No. Offline reproduction of the main results does not require API keys or live model calls, as it uses cached reference outputs.
How can I integrate ACRouter into my existing workflow?
You can integrate it via runtime integrations for tools like Claude Code or cc-switch, or by importing the ACRouter class directly into your Python code for custom inference-time routing.
Where can I find the CodeRouterBench dataset?
The dataset is available on Hugging Face under the repository 'Lance1573/CodeRouterBench'.
How do I run the provided demos?
You can run the API Coding Solver demo by setting your OPENROUTER_API_KEY and executing the solve.py script, or use the commercial CLI router demo to route prompts to tools like Codex or Claude Code.
Featured in Videos
YouTube tutorials and walkthroughs for agent-as-a-router
Alternatives
Similar projects ranked by category, topics, and text overlap.
