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docs: add project description subtitle to README and academic foundations
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- docs/academic_foundations.md +2 -0
README.md
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# 🎯 InferRoute: High-Availability LLM Inference Gateway & Observability Router
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<p align="center">
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<img src="https://img.shields.io/badge/License-MIT-emerald.svg" alt="License">
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<img src="https://img.shields.io/badge/Python-3.12%20%7C%203.13-blue.svg" alt="Python Version">
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# 🎯 InferRoute: High-Availability LLM Inference Gateway & Observability Router
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InferRoute is built upon robust theoretical frameworks for cost-performance trade-offs and multi-tier cascading inference.
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<p align="center">
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<img src="https://img.shields.io/badge/License-MIT-emerald.svg" alt="License">
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<img src="https://img.shields.io/badge/Python-3.12%20%7C%203.13-blue.svg" alt="Python Version">
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docs/academic_foundations.md
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# 📖 Academic Foundations: FrugalGPT & RouterBench Integration
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InferRoute's core routing architecture is built on the theoretical and mathematical foundations of two landmark papers in LLM cost-performance optimization:
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1. **FrugalGPT**: *"FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance"* (Chen et al., Stanford University, 2023).
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# 📖 Academic Foundations: FrugalGPT & RouterBench Integration
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InferRoute is built upon robust theoretical frameworks for cost-performance trade-offs and multi-tier cascading inference.
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InferRoute's core routing architecture is built on the theoretical and mathematical foundations of two landmark papers in LLM cost-performance optimization:
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1. **FrugalGPT**: *"FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance"* (Chen et al., Stanford University, 2023).
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