AI4AII — Local AI frontend

AI4AII is a lightweight, AI frontend designed for fast, local large‑language‑model inference using llama.cpp. It provides a minimal, portable foundation for embedding LLM capabilities directly into native applications—without cloud dependencies, external services, or heavyweight frameworks.

The project focuses on privacy‑first AI, low‑latency inference, and clean integration with higher‑level systems such as digital humans, film engines, or conversational interfaces.

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Releases

Core Edition	Plus Edition	Premium Edition

✨ Overview

AI4All implements a compact Dart wrapper around llama.cpp, enabling:

• Local inference with GGUF models
• Simple prompt/response execution
• Configurable context, sampling, and runtime parameters
• Easy embedding into larger engines or UI layers
• Zero external dependencies beyond llama.cpp

AI4All acts as the “AI core” for applications that need deterministic, offline, and secure LLM behavior—ideal for real‑time agents, film pipelines, or embodied AI systems.

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🧩 Key Features

• Local LLM Inference
  Runs entirely on‑device using llama.cpp, ensuring privacy and predictable performance.

• Minimal C++ API
  Clean, header‑driven interface for loading models, sending prompts, and receiving responses.

• Configurable Runtime
  Supports context size, temperature, top‑k/top‑p, repeat penalties, and other generation parameters.

• Embeddable Architecture
  Designed to plug into engines, assistants, or digital human systems without heavy integration work.

• Deterministic & Reproducible
  Ideal for pipelines where consistent output matters (storyboards, shot generation, scripted agents).

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🔌 Integration Scenarios

AI4AII is designed to serve as the AI backbone for:

• Digital human interfaces (MetaHuman‑style agents)
• Cinematic AI systems using Unnu FilmMaker + UnnuFM
• Voice‑driven assistants using UnnuTTS
• Local creative tools (storyboarding, shot generation, script helpers)
• Offline conversational agents
• Privacy‑first enterprise applications

Its minimal footprint makes it ideal for embedding into real‑time or resource‑constrained environments.

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🛠️ Configuration

AI4AII exposes runtime parameters such as:

• context_size
• temperature
• top_k, top_p
• repeat_penalty
• max_tokens

These can be set per‑request or globally depending on your integration needs.

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📜 License

AI4All is released under the MIT License, allowing unrestricted use in commercial and non‑commercial applications.

If you want, I can also prepare a branch‑specific architecture diagram or a developer onboarding section that explains how AI4AII fits into your full Unnu ecosystem.