AIlice is a fully autonomous, general-purpose AI agent that uses an interactive agents call tree architecture to decompose complex tasks, supporting both open-source and commercial LLMs for research, coding, and system management.

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AIlice

AIlice Product Information

What is AIlice?

AIlice is a fully autonomous, general-purpose AI agent designed for developers, researchers, and system administrators who need a self-directed assistant that can handle complex, multi-step tasks. Built on the Interactive Agents Call Tree (IACT) architecture, AIlice decomposes tasks into dynamically constructed sub-agents, enabling it to research, code, manage systems, and perform academic literature reviews with high fault tolerance. It supports both open-source LLMs (like Qwen2.5-72B) and commercial models, and can run locally or via Docker for privacy.

What are the features of AIlice?

  • IACT Architecture
    Dynamically breaks down complex tasks into callable sub-agents with bidirectional communication, allowing error correction and contextual handoffs between agents.
  • Multi-Agent Cooperation
    Different agents (e.g., coder, researcher, search engine) can be assigned distinct LLMs, balancing cost and performance on a per-task basis.
  • Self-Expansion via Dynamic Modules
    AIlice can autonomously write and load new external interaction modules (ext-modules) or agent types, extending its capabilities through simple prompts.
  • Native Multimodal Support
    All agents handle rich media including images, video, audio, LaTeX formulas, and code highlighting, with automatic variable passing between agents.
  • MCP Tool Integration
    Wraps any MCP-compatible server (stdio or SSE) as a standard extension module, allowing AIlice to leverage a growing ecosystem of tools.
  • Voice Interaction
    Supports text-to-speech (TTS) and speech-to-text (STT) with configurable devices, enabling hands-free operation.

What are the use cases of AIlice?

  • Thematic research
    Ask AIlice to investigate a topic, gather sources, and produce a structured report with citations.
  • Automated coding and debugging
    Delegate software development tasks—clone repos, analyze architecture, write code, and run tests.
  • System administration
    Install software, configure environments, and run security scans on a target machine.
  • Academic literature review
    Search for recent papers, read them, and compile a summary of field progress.
  • Document generation
    Create formatted PDFs, LaTeX slides, or web pages with self-determined content and layout.

How to use AIlice?

  • Quick start
    Clone the repo, run pip install -e ., then launch AIlice with ailice --contextWindowRatio=0.2.
  • Configure an LLM
    Use --modelID with a prefix (e.g., anthropic:claude-sonnet-4) or set agentModelConfig in config.json for per-agent model selection.
  • Enable voice
    Add --speechOn=1 --ttsDevice=cuda --sttDevice=cuda to activate voice dialogue.
  • Run in Docker
    Build the image and use docker run with exposed ports; optionally add CUDA or GUI support.
  • Extend with MCP
    Add an MCP server to config.json using ailice_mcp_wrapper to bring in external tools.

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AIlice FAQ

What is AIlice?

AIlice is a fully autonomous, general-purpose AI agent that uses a multi-agent call tree architecture to decompose complex tasks and coordinate sub-agents using LLMs.

What LLMs does AIlice support?

It supports open-source models (e.g., Qwen2.5-72B, GLM-4.5) via Hugging Face or local inference, plus commercial models from Anthropic, Google, Mistral, Groq, and OpenAI-compatible APIs.

How does the IACT architecture improve reliability?

Sub-agents can request clarification from their callers when stuck, enabling fault tolerance and iterative problem-solving that traditional linear pipelines lack.

Can I run AIlice completely offline?

Yes. By using locally hosted open-source models (e.g., via LM Studio or Ollama) and disabling online services, AIlice can operate entirely offline, preserving privacy.

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