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