ENTUM-AI/AgentRouter

⚡ AgentRouter

Ultra-fast intent classification for LLM query routing. Classifies user queries into 10 intent categories in <5ms on GPU.

Built on MiniLM (33M params) — small enough for CPU inference, fast enough for real-time routing.

🚀 Usage

from transformers import pipeline

router = pipeline("text-classification", model="ENTUM-AI/AgentRouter")

router("Write a Python function to sort a list")
# [{'label': 'code_generation', 'score': 0.98}]

router("Why am I getting a TypeError?")
# [{'label': 'code_debugging', 'score': 0.97}]

router("Translate hello to Spanish")
# [{'label': 'translation', 'score': 0.99}]

router("What is quantum computing?")
# [{'label': 'information_retrieval', 'score': 0.96}]

🏷️ Intent Classes

🔍 Use Cases

• —LLM routing — route queries to specialized models or tools
• —Agent frameworks — decide which tool to invoke
• —Cost optimization — use cheap models for simple intents, expensive for complex
• —Latency optimization — skip heavy pipelines for general chat

⚠️ Limitations

• —English only
• —10 fixed intent categories