An edge-deployed AI crewmate for marine safety and situational awareness.
chatty-buoy is a locally-hosted, multimodal AI assistant designed for NVIDIA Jetson hardware. It acts as an always-on watchstander that monitors NMEA data, transcribes VHF radio traffic, and analyzes visual feeds in real-time.
It keeps a vigilant eye on the horizon so you don't have to—though it may occasionally offer an unsolicited critique of your docking maneuvers.
No cloud. No subscription. No latency. Just 100% local intelligence.
For a detailed breakdown of the system capabilities, service orchestration, and Jetson Thor integration, please refer to the Quintessential Architecture.
micromamba (Environment: chatty-buoy)ngc CLI (Install manually if you need to download new Riva models).
Step A: Application Infrastructure (Docker) Starts Riva (ASR), Triton (Cortex), and Postgres (Memory).
docker compose up -d
Step B: Voice Synthesis The voice service uses Chatterbox-Turbo (350M) by default for expressive, low-latency speech.
src/voice/Kokoro-FastAPI for ultra-low resource environments.Step C: The Agent Interact with the system.
micromamba run -n chatty-buoy python3 src/agent_reflex.py
Step D: Watchstander Vision Dashboard
The containerized Watchstander automatically observes bounding box events, requests scene summaries from Cosmos-Vision, logs Sentinel telemetry, and provides historical video clip playback.
Access the interactive web feed live at: http://localhost:8080
We are currently in Phase 3 (Situational Awareness). See Roadmap for the journey ahead, including NMEA integration, Sonar analysis, and Vision capabilities.
MIT
34 commits
Python
93.0%
Shell
6.2%
An edge-deployed AI crewmate for marine safety and situational awareness.
chatty-buoy is a locally-hosted, multimodal AI assistant designed for NVIDIA Jetson hardware. It acts as an always-on watchstander that monitors NMEA data, transcribes VHF radio traffic, and analyzes visual feeds in real-time.
It keeps a vigilant eye on the horizon so you don't have to—though it may occasionally offer an unsolicited critique of your docking maneuvers.
No cloud. No subscription. No latency. Just 100% local intelligence.
For a detailed breakdown of the system capabilities, service orchestration, and Jetson Thor integration, please refer to the Quintessential Architecture.
micromamba (Environment: chatty-buoy)ngc CLI (Install manually if you need to download new Riva models).
Step A: Application Infrastructure (Docker) Starts Riva (ASR), Triton (Cortex), and Postgres (Memory).
docker compose up -d
Step B: Voice Synthesis The voice service uses Chatterbox-Turbo (350M) by default for expressive, low-latency speech.
src/voice/Kokoro-FastAPI for ultra-low resource environments.Step C: The Agent Interact with the system.
micromamba run -n chatty-buoy python3 src/agent_reflex.py
Step D: Watchstander Vision Dashboard
The containerized Watchstander automatically observes bounding box events, requests scene summaries from Cosmos-Vision, logs Sentinel telemetry, and provides historical video clip playback.
Access the interactive web feed live at: http://localhost:8080
We are currently in Phase 3 (Situational Awareness). See Roadmap for the journey ahead, including NMEA integration, Sonar analysis, and Vision capabilities.
MIT
34 commits
Python
93.0%
Shell
6.2%