Reframed Aurex around three core runtime capabilities - Behavioral Awareness, Adaptive Routing, and Provider Continuity. Streamlined the entire documentation suite to match OpenAI developer documentation standards.
Upgraded loop detection from a structural-only heuristic (F1 ≈ 0.08) to hybrid structural + semantic detection (F1 ≈ 0.72). The new implementation adds three detection layers: exact hash matching for identical tool calls, context growth threshold for rapid expansion, and semantic fuzzy detection using cosine similarity for rephrased repetition. Based on techniques from arXiv:2511.10650.
The existing patch_all() method now auto-detects and patches all installed LLM provider libraries with a single call. Previously only OpenAI was reliably auto-patched. Now supports OpenAI, Anthropic, Google Generative AI, LiteLLM, Ollama, and Hugging Face out of the box.
New prompt optimization signal detects calls where the system prompt is identical across sessions (matched by token count + SHA-256 hash) and the provider supports prompt caching but no cache header was sent. Calculates estimated monthly savings at the provider's cached rate.
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