dASS (Desktop Assistant) is a powerful, multi-platform application built with Avalonia UI and .NET 10 that provides an intelligent LLM-powered assistant with a rich and extensible set of tools, multi-agent collaboration, semantic memory, MCP (Model Context Protocol) support, and a web-based chat UI for multi-user chatting.
- Multiple specialized agents with individual configurations
- Agent execution strategies: Sequential, Random, Adaptive, Mention-only, and Round-robin
- Agent read permissions - control what each agent can see in the conversation
- Per-agent generation settings: reasoning, persona, specialization, behaviour sliders and skills
- Filesystem operations - read, write, search, replace, copy, delete files and directories
- Web requests & search - fetch URLs, search the web, download files
- Document reading - PDF, DOCX, PPTX
- Image description - describe images using vision models when main agent cannot read images natively
- Mathematics - execute mathematical calculations using built-in evaluator and solver
- Databases - query SQLite and PostgreSQL databases via managed connections
- Random - dice rolls (for DnD), random numbers, GUIDs, list shuffling
- Human-in-the-Loop - file pickers, confirmation dialogs, choice selection
- Shell execution - with optional live and interactive terminal in the UI
- Interactive diff confirmation - preview file changes with color-coded diffs, accept or decline individual edits directly in the chat
- Time utilities - get current time, wait/delays
- Scripting - Python execution in configured
.venv/global environment, Lua via AsyncLua (async/await Lua interpreter with a wide range of API bindings) and C# scripts via Roslyn - Skills - SKILL.md-based capabilities that can be loaded on demand
- Meta tools - dynamic tools that can be created by the LLM using Python, Lua or C# when the original set of tools is not enough
- MCP - tools from external servers
Configure which tools each agent can use right from the agent settings:
- Memory blocks with configurable access modes (read-only, write, full) attached to chats and agents
- Facts with semantic search and episodic logs with keyword search
- Automatic memory recorder and reader - the assistant remembers important information about you and retrieves it when needed
- Tool behaviour system that analyses what tools will really do (when a file deletion tool will not find the target file, then the tool will not require confirmation, because it will do nothing). This also allows to auto-approve tools that just create new files and require confirmation when tools try to edit existing files
- Specifier engine - declarative per-tool policy rules that match tool arguments (including parsed shell commands), with configurable policy aggregation and per-tool overrides
- Secrets protection - DetectSecretsSharp prevents leakage of secrets when the LLM reads files
- Built-in Blazor-based Web UI that can be hosted on a local endpoint with optional password protection
- Multiple working directories - switch between project roots per chat
- Prompt manager - edit prompt components, personas, specializations and behaviour sliders via LLT files (located in
%LOCALAPPDATA%/.llmassist/templates) or via UI (LLT editor will be supported soon) - Zero-dependency web-search using an embedded version of SearXNG - SearXSharp, that scrapes multiple search engines (Google, Bing, DuckDuckGo and much more) concurrently. No API key needed!
- Localization - full UI localization with semantic keys and
.locfiles (invariant +ru-RU) - Built-in help viewer - localized documentation with GitHub-flavoured alerts rendered right in the app
- Chat summarization - long conversations are automatically summarized to fit the context window
When you want to expand your agent's functionality, you can give him a task - explore the API and create a meta tool in Lua, Python or C#. In this example, we'd create a tool that gives commit names based on current git context:
We got a tool that executes git diff process and puts it to the internal agent with a special system prompt, then displays the result to the main agent. Now try it in another chat:
And check the tool in the agent's settings:
If you want to edit, share or create tools by yourself, go to %LOCALAPPDATA%/.llmassist/metatools folder and edit .lua, .py and .csx files.
| Platform | Project |
|---|---|
| Windows / Linux / macOS | LLMDesktopAssistant.Desktop |
| Android | LLMDesktopAssistant.Android |
| Browser (WebAssembly) | LLMDesktopAssistant.Browser |
| Web chat UI (multi-user) | LLMDesktopAssistant.Blazor |
Unit and integration tests covering the core, tools, specifiers, localization, help and more live in tests/ (LLMDesktopAssistant.Tests and LLMDesktopAssistant.Desktop.Tests).
| Technology | Purpose |
|---|---|
| RCLLM | Lightweight LLM client library |
| LLTSharp | Metadata-rich and easy-readable prompt templates for LLM |
| AsyncLua | Extended Lua scripting engine with concurrency and async/await support |
| RCParsing | Lexerless parser used in various utilities, such as math evaluation tool (also used in LLTSharp and AsyncLua) |
| SearXSharp | C#-adapted SearXNG meta-search engine with 118+ engines supported |
| DetectSecretsSharp | C#-adapted yelp/detect-secrets used for preventing leakage of secrets when LLM is reading files |
Built on top of Avalonia UI 12, .NET 10 and a number of great open-source libraries: model providers via RCLLM (OpenAI, DeepSeek, OpenRouter, Novita, Ollama and any OpenAI-compatible endpoint), LiteDB for storage, Markdig for markdown rendering, ModelContextProtocol for MCP, and much more.
This project is licensed under the MIT License — see the LICENSE file for details.
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