Off-grid LLM over Radio
A platform that integrates Large Language Models (LLMs) with Meshtastic mesh communication networks to enable off-grid AI interactions and automated task execution through radio communication.
https://github.com/pham-tuan-binh/radio-llm?ref=aipure
Product Information
Updated:Dec 18, 2024
What is Off-grid LLM over Radio
Off-grid LLM over Radio is an innovative solution that bridges the gap between AI language models and mesh network communications when traditional internet connectivity is unavailable. Built on the Meshtastic protocol, this platform allows users to interact with LLMs through radio devices, making AI assistance accessible in remote or disconnected environments. The system supports both general conversational interactions and specific task execution capabilities like emergency service calls and sensor data retrieval, all while maintaining message history for context-aware responses.
Key Features of Off-grid LLM over Radio
Off-grid LLM over Radio is a platform that integrates Large Language Models with Meshtastic mesh communication networks, enabling AI interactions in areas without internet connectivity. The system allows for bi-directional communication, automated responses, and task execution through radio networks while maintaining message history and context-awareness, making it particularly valuable for remote or emergency situations.
Mesh Network Integration: Seamlessly connects with Meshtastic mesh communication network for distributed coverage and reliable message transmission
Automated Message Management: Handles automatic message chunking for long responses exceeding 200 characters and maintains message history for context-aware interactions
Tool Execution Framework: Enables LLM to execute specific tasks like emergency service calls and sensor data retrieval through defined tools and commands
Node-Specific Information Handling: Tracks and incorporates device-specific data like battery levels, location, and last heard time for enhanced contextual awareness
Use Cases of Off-grid LLM over Radio
Emergency Response: Provides automated emergency service access and coordination in areas with limited or no cellular coverage
Remote Field Operations: Supports teams working in remote locations with AI-assisted decision making and communication capabilities
Disaster Recovery: Enables communication and AI assistance during natural disasters when traditional infrastructure is compromised
Off-Grid Research: Assists scientific expeditions and research teams in remote locations with AI-powered analysis and communication
Pros
Functions without internet connectivity
Scalable mesh network coverage
Integration with multiple device types and interfaces
Cons
Limited by radio bandwidth and range
Performance constraints with smaller LLM models
Currently limited tool functionality
How to Use Off-grid LLM over Radio
Install Prerequisites: Install Python 3.8+, Meshtastic Python library, Ollama LLM Python SDK, and PubSub library using pip install -r requirements.txt
Set Up Hardware: Connect your Meshtastic radio device via USB to your computer or configure it for TCP network access
Clone Repository: Clone the radio-llm repository from GitHub (https://github.com/pham-tuan-binh/radio-llm)
Configure Interface: Choose and configure the appropriate interface in the code - either Serial (USB), TCP (network), or BLE (Bluetooth) connection to your Meshtastic device
Set Up Ollama Model: Install your preferred LLM model in Ollama and update the model name in model/config.yaml file
Run the Platform: Execute the main script to start the LLM-radio integration platform
Interact with LLM: Send messages over the Meshtastic mesh network using either normal messages or '/tool your_message' command to activate tool functionality
Optional: Add Custom Tools: Create custom tools by defining them in model/tool_handler.py, registering in model/tool_registry.py, and describing in config.yaml
Off-grid LLM over Radio FAQs
Radio-LLM is a platform that integrates Large Language Models (LLMs) with Meshtastic mesh communication networks, allowing users to interact with an LLM over radio for automated responses and execute tasks like calling emergency services or retrieving sensor information.
Off-grid LLM over Radio Video
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