Rodrigo Rodriguez (Pragmatismo)
037db5c381
- Add comprehensive documentation in botbook/ with 12 chapters - Add botapp/ Tauri desktop application - Add botdevice/ IoT device support - Add botlib/ shared library crate - Add botmodels/ Python ML models service - Add botplugin/ browser extension - Add botserver/ reorganized server code - Add bottemplates/ bot templates - Add bottest/ integration tests - Add botui/ web UI server - Add CI/CD workflows in .forgejo/workflows/ - Add AGENTS.md and PROD.md documentation - Add dependency management scripts (DEPENDENCIES.sh/ps1) - Remove legacy src/ structure and migrations - Clean up temporary and backup files
37 lines
2.8 KiB
Markdown
37 lines
2.8 KiB
Markdown
# Agent Workspaces
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General Bots supports an advanced "Agent Mode" UI where the interaction with an AI agent shifts from a simple chat interface to a fully realized multi-panel workspace. This design empowers users to monitor complex autonomous tasks in real-time, providing deep visibility into what the AI is doing.
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## Architectural Overview
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When an application logic branch triggers a computationally heavy or open-ended action (like `APP_CREATE` or deep research), the backend kicks off an **Agent Executor** process. This executor brings up a dedicated, highly isolated LXC container for that specific session.
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The Agent Executor communicates back to the frontend in real-time. This provides a transparent view of:
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1. **Thought Processes**: High-level textual reasoning of the agent.
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2. **Terminal Output**: Verbatim standard output and standard error from the LXC container.
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3. **Browser Output**: Visual previews of web applications being built or research being conducted, served via localhost proxies from within the container.
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## The Agent UI
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The main interface pivots from a standard 1-panel conversation to a complex multi-panel grid when "Agent Mode" is toggled from the Chat interface.
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This layout includes:
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- **Left Sidebar**: A collapsible "Agents & Workspaces" sidebar that summarizes the current state of active agents, their resource usage (quota), and provides drag-and-drop workspace organization.
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- **Center Chat**: A persistent interactive chat with the specific agent, allowing for ongoing refinement of the task.
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- **Right Hand Split Screens**:
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- **Top Right**: An active Browser Window. The agent can stream HTML rendering updates or host internal applications (`localhost`) from its LXC sandbox, exposing them visually to the user.
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- **Bottom Right**: A live Terminal feed streaming `stdout` and `stderr` directly from the bash environment of the underlying LXC container.
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## LXC Sandbox execution
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To prevent dependency collisions, protect the host operating system, and offer clean slate environments for arbitrary execution, every agent session spins up a temporary **Ubuntu 22.04 LXC container**.
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1. When the agent intent classifier matches a heavy task (e.g. `APP_CREATE`), the backend initiates the `ContainerSession` struct.
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2. An `lxc launch` command instantiates a fast, lightweight container instance.
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3. A bash shell is opened inside this container, and its I/O streams are piped back to the `TaskProgressEvent` broadcast channel using Tokio.
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4. The user sees the bash output instantly in the bottom-right terminal panel.
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5. On completion or failure, the container is forcibly stopped and deleted (`lxc delete --force`).
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This isolated environment gives agents the absolute freedom to execute package installations (like `npm install`), launch development servers, and write arbitrary code, entirely segregated from the primary `BotServer`.
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