--- license: mit tags: - aisafety - embeddings - vector-search - rrf - numerical-stability --- --- # Savant Engine SDK **Deterministic Geometric Governance for Embedding Pipelines** Savant Engine is a lightweight **Geometry Control SDK** designed to stabilize, audit, and govern vector embeddings produced by modern neural models. It introduces deterministic geometric guarantees without modifying model weights or semantic content. This SDK is model-agnostic and can wrap any embedding generator (Transformers, SentenceTransformers, local LLMs, or custom encoders). --- ## Why Savant? Modern embedding models can silently produce vectors with near-zero norms, leading to: - NaN / Inf cosine similarities - Reciprocal Rank Fusion (RRF) collapse - Silent numerical corruption in production systems Savant solves this by **owning the geometry**, not the model. --- ## Core Principles ### 🔹 Geometry-Owned Architecture The embedding manifold is governed by deterministic constraints, independent of the model’s internal distribution. ### 🔹 Silent Math Under nominal conditions, Savant introduces **zero distortion**. It only intervenes when geometric safety is violated. ### 🔹 Auditability All stabilization events are logged, converting silent failures into traceable engineering signals. --- ## Modules ### `savant_wrapper.py` Core stabilization wrapper that: - Intercepts embedding vectors - Enforces a minimum geometric norm (`r_min`) - Logs stabilization events deterministically ### `geometry_audit.py` Lightweight audit utilities for: - Recording stabilization events - Inspecting geometric health - Supporting safety-critical validation workflows ### `rrf_safe_similarity.py` Drop-in replacements for similarity operations: - Safe cosine similarity - RRF-compatible distance calculations - Guaranteed finite outputs --- ## Installation ```bash pip install savant-engine Or directly from Hugging Face: pip install git+https://huggingface.co/antonypamo/savant-engine Quick Start from savant_wrapper import SavantWrapper from sentence_transformers import SentenceTransformer model = SentenceTransformer("all-MiniLM-L6-v2") savant = SavantWrapper( embedder=model, r_min=1e-4 ) vec = savant.encode("Resonant Relational Framework") print(vec.shape) print(savant.audit_log) Design Intent Savant is not: a model a dataset a fine-tuned checkpoint Savant is: an SDK an infrastructure primitive a deterministic safety layer for AI systems Target Use Cases Reciprocal Rank Fusion (RRF) Vector databases Safety-critical AI pipelines Industrial / ISO-compliant ML systems Research validation and benchmarking License MIT License Author Antony Padilla Morales Costa Rica “The model generates meaning. Savant owns geometry.”