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| name | description |
|---|---|
| dgx-spark-multi-agent-chatbot | Deploy a multi-agent chatbot system and chat with agents on your Spark — on NVIDIA DGX Spark. Use when setting up multi-agent-chatbot on Spark hardware. |
Build and Deploy a Multi-Agent Chatbot
Deploy a multi-agent chatbot system and chat with agents on your Spark
This playbook shows you how to use DGX Spark to prototype, build, and deploy a fully local multi-agent system. With 128GB of unified memory, DGX Spark can run multiple LLMs and VLMs in parallel — enabling interactions across agents.
At the core is a supervisor agent powered by gpt-oss-120B, orchestrating specialized downstream agents for coding, retrieval-augmented generation (RAG), and image understanding. Thanks to DGX Spark's out-of-the-box support for popular AI frameworks and libraries, development and prototyping are fast and frictionless. Together, these components demonstrate how complex, multimodal workflows can be executed efficiently on local, high-performance hardware.
Outcome: You will have a full-stack multi-agent chatbot system running on your DGX Spark, accessible through your local web browser. The setup includes:
- LLM and VLM model serving using llama.cpp servers and TensorRT LLM servers
- GPU acceleration for both model inference and document retrieval
- Multi-agent system orchestration using a supervisor agent powered by gpt-oss-120B
- MCP (Model Context Protocol) servers as tools for the supervisor agent
Full playbook: /home/runner/work/dgx-spark-playbooks/dgx-spark-playbooks/nvidia/multi-agent-chatbot/README.md