diff --git a/content/reference/samples/_index.md b/content/reference/samples/_index.md index 49c769ba4b..eb07f7f3a9 100644 --- a/content/reference/samples/_index.md +++ b/content/reference/samples/_index.md @@ -35,4 +35,4 @@ Learn how to containerize different types of services by walking through Officia ## Other samples -[AI/ML](../samples/ai-ml.md) \| [Cloudflared](../samples/cloudflared.md) \| [Elasticsearch / Logstash / Kibana](../samples/elasticsearch.md) \| [Minecraft](../samples/minecraft.md) \| [NGINX](../samples/nginx.md) \| [Pi-hole](../samples/pi-hole.md) \| [Plex](../samples/plex.md) \| [Traefik](../samples/traefik.md) \| [WireGuard](../samples/wireguard.md) +[Agentic AI](../samples/agentic-ai.md) \| [AI/ML](../samples/ai-ml.md) \| [Cloudflared](../samples/cloudflared.md) \| [Elasticsearch / Logstash / Kibana](../samples/elasticsearch.md) \| [Minecraft](../samples/minecraft.md) \| [NGINX](../samples/nginx.md) \| [Pi-hole](../samples/pi-hole.md) \| [Plex](../samples/plex.md) \| [Traefik](../samples/traefik.md) \| [WireGuard](../samples/wireguard.md) diff --git a/content/reference/samples/agentic-ai.md b/content/reference/samples/agentic-ai.md new file mode 100644 index 0000000000..58421ca486 --- /dev/null +++ b/content/reference/samples/agentic-ai.md @@ -0,0 +1,5 @@ +--- +title: Agentic AI samples +description: Docker samples for agentic AI. +service: agentic-ai +--- diff --git a/data/samples.yaml b/data/samples.yaml index deae29f0a7..7516139e48 100644 --- a/data/samples.yaml +++ b/data/samples.yaml @@ -350,4 +350,98 @@ samples: description: Get started with AI and ML using Docker, Neo4j, LangChain, and Ollama services: - python - - aiml \ No newline at end of file + - aiml +# Agentic AI ---------------------------- + - title: Agent-to-Agent + url: https://github.com/docker/compose-for-agents/tree/main/a2a + description: > + This app is a modular AI agent runtime built on Google's Agent + Development Kit (ADK) and the A2A (Agent-to-Agent) protocol. It wraps a + large language model (LLM)-based agent in an HTTP API and uses + structured execution flows with streaming responses, memory, and tools. + It is designed to make agents callable as network services and + composable with other agents. + services: + - python + - aiml + - agentic-ai + - title: ADK Multi-Agent Fact Checker + url: https://github.com/docker/compose-for-agents/tree/main/adk + description: > + This project demonstrates a collaborative multi-agent system built with + the Agent Development Kit (ADK), where a top-level Auditor agent coordinates + the workflow to verify facts. The Critic agent gathers evidence via live + internet searches using DuckDuckGo through the Model Context Protocol (MCP), + while the Reviser agent analyzes and refines the conclusion using internal + reasoning alone. The system showcases how agents with distinct roles and + tools can collaborate under orchestration. + services: + - python + - aiml + - agentic-ai + - title: DevDuck agents + url: https://github.com/docker/compose-for-agents/tree/main/adk-cerebras + description: > + A multi-agent system for Go programming assistance built with Google + Agent Development Kit (ADK). This project features a coordinating agent + (DevDuck) that manages two specialized sub-agents (Bob and Cerebras) + for different programming tasks. + services: + - python + - aiml + - agentic-ai + - title: Agno + url: https://github.com/docker/compose-for-agents/tree/main/agno + description: > + This app is a multi-agent orchestration system powered by LLMs (like Qwen + and OpenAI) and connected to tools via a Model Control Protocol (MCP) + gateway. Its purpose is to retrieve, summarize, and document GitHub + issues—automatically creating Notion pages from the summaries. It also + supports file content summarization from GitHub. + services: + - python + - aiml + - agentic-ai + - title: CrewAI + url: https://github.com/docker/compose-for-agents/tree/main/crew-ai + description: > + This project showcases an autonomous, multi-agent virtual marketing team + built with CrewAI. It automates the creation of a high-quality, end-to-end + marketing strategy — from research to copywriting — using task delegation, + web search, and creative synthesis. + services: + - python + - aiml + - agentic-ai + - title: SQL Agent with LangGraph + url: https://github.com/docker/compose-for-agents/tree/main/langgraph + description: > + This project demonstrates a zero-config AI agent that uses LangGraph to + answer natural language questions by querying a SQL database — all + orchestrated with Docker Compose. + services: + - python + - aiml + - agentic-ai + - title: Spring AI Brave Search Example - Model Context Protocol (MCP) + url: https://github.com/docker/compose-for-agents/tree/main/spring-ai + description: > + This example demonstrates how to create a Spring AI Model Context Protocol + (MCP) client that communicates with the Brave Search MCP Server. The + application shows how to build an MCP client that enables natural language + interactions with Brave Search, allowing you to perform internet searches + through a conversational interface. This example uses Spring Boot + autoconfiguration to set up the MCP client through configuration files. + services: + - java + - aiml + - agentic-ai + - title: MCP UI with Vercel AI SDK + url: https://github.com/docker/compose-for-agents/tree/main/a2a + description: > + Start an MCP UI application that uses the Vercel AI SDK to provide a + chat interface for local models, provided by the Docker Model Runner, + with access to MCPs from the Docker MCP Catalog. + services: + - aiml + - agentic-ai \ No newline at end of file