ROS Package bob_llm

The bob_llm package provides a ROS 2 node (llm node) that acts as a powerful interface to an external Large Language Model (LLM). It operates as a stateful service that maintains a conversation, connects to any OpenAI-compatible API, and features a robust tool execution system.

Features

• OpenAI-Compatible: Connects to any LLM backend that exposes an OpenAI-compatible API endpoint (e.g., Ollama, vLLM, llama-cpp-python, commercial APIs).
• Stateful Conversation: Maintains chat history to provide conversational context to the LLM.
• Dynamic Tool System: Dynamically loads Python functions from user-provided files and makes them available to the LLM. The LLM can request to call these functions to perform actions or gather information.
• Anthropic Agent Skills: Full support for the Anthropic Agent Skills specification, enabling modular, self-contained capabilities with documentation and execution logic.
• High Performance Streaming: Optimized byte-stream parsing ensures zero-latency delivery of reasoning tokens and response chunks directly from the socket (no internal buffering).
• Reasoning/Thinking Support: Real-time extraction and publishing of model reasoning (e.g., from Gemma 2 or DeepSeek) to a dedicated topic.
• Interactive Chat CLI: Includes a premium terminal interface with Markdown rendering and multi-line support.
• Multi-modality: Supports multimodal input (e.g., images) via JSON prompts.
• Lightweight: The node core requires only standard Python libraries (requests, rich, prompt_toolkit).

Installation

1. Clone the Repository Navigate to your ROS 2 workspace’s src directory and clone the repository:

    cd ~/ros2_ws/src
    git clone https://github.com/bob-ros2/bob_llm.git
    

1. Install Dependencies The node requires a few Python packages. It is recommended to install these within a virtual environment.

    pip install requests PyYAML rich prompt_toolkit
    

1. Build and Source

    cd ~/ros2_ws
    colcon build --packages-select bob_llm
    source install/setup.bash
    

Usage

1. Start the Brain (LLM Node)

Ensure your LLM server is active and the api_url in your params file is correct.

ros2 run bob_llm llm --ros-args --params-file /path/to/your/ros2_ws/src/bob_llm/config/node_params.yaml

2. Enter Interactive Chat

Interact with Bob through a dedicated, interactive terminal client.

# Start standard chat
ros2 run bob_llm chat

# Start with premium boxed UI (visual panels)
ros2 run bob_llm chat --panels

CLI Arguments for chat

Chat Configuration

The chat client supports the following ROS parameters and environment variables:

• queue_size (Integer): ROS parameter to control the subscription queue depth.
• CHAT_QUEUE_SIZE (Environment Variable): Default value for the queue_size parameter (default: 1000).

Example usage:

export CHAT_QUEUE_SIZE=2000
ros2 run bob_llm chat --topic_in /user_query --topic_out /llm_stream --panels

Chat Example

```text Chat for https://github.com/bob-ros2/bob_llm Usage: Press Enter to send, or Alt+Enter for a new line.

YOU: Was kannst du über dieses System sagen?

[*] SKILL: list_nodes({})

LLM: Ich sehe folgende aktive Komponenten im System:

• /llm (Das Gehirn)

File truncated at 100 lines see the full file

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