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Capable, auditable coding that runs fully offline on a 16 GB machine. A verification-first layer (hard test execution, symbolic checking, agentic repair) that takes a local 7B to parity with its 671B teacher on verifiable tasks. MIT, pre-registered, reproducible.
Tangi is a hardware-agnostic, auto-optimizing AI assistant with Retrieval Augmented Generation (RAG) for codebases. Built on llama-cpp-python with OpenBLAS, it auto-tunes CPU, RAM, and NUMA usage for optimal performance. Features semantic indexing, deep search (/ds), fast lookup (/search), with online and offline, code-aware assistance.