ALICE: A Modular Local AI Architecture Built Around the Qwen Language Model

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ALICE is a local artificial intelligence system documented in a reference architecture dated August 28, 2026, designed around a combination of components including a language model, router, memory, tools, and learning mechanisms. The system uses Qwen2.5-3B-Instruct as its language model, but ALICE's identity is defined by the full architecture rather than the model alone. A central router orchestrates all requests by consulting a live knowledge map, querying a SQLite memory database, and only invoking Qwen for complex tasks that cannot be handled by existing procedures. ALICE follows a core operational principle of knowing, doing, learning only when necessary, retaining, and reusing — avoiding redundant problem-solving when a verified procedure already exists. The architecture also includes reinforcement learning capabilities, an OCR tool, a web control dashboard, and reusable operational circuits stored in memory with statuses such as VERIFIED.

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