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samples: add agentic (#22938)
<!--Delete sections as needed --> ## Description Add agentic AI samples https://deploy-preview-22938--docsdocker.netlify.app/reference/samples/agentic-ai/ ## Related issues or tickets ENGDOCS-2782 ## Reviews <!-- Notes for reviewers here --> <!-- List applicable reviews (optionally @tag reviewers) --> - [ ] Editorial review --------- Signed-off-by: Craig <craig.osterhout@docker.com>
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@ -35,4 +35,4 @@ Learn how to containerize different types of services by walking through Officia
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## Other samples
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[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)
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[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)
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---
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title: Agentic AI samples
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description: Docker samples for agentic AI.
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service: agentic-ai
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---
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@ -350,4 +350,98 @@ samples:
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description: Get started with AI and ML using Docker, Neo4j, LangChain, and Ollama
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services:
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- python
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- aiml
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- aiml
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# Agentic AI ----------------------------
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- title: Agent-to-Agent
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url: https://github.com/docker/compose-for-agents/tree/main/a2a
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description: >
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This app is a modular AI agent runtime built on Google's Agent
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Development Kit (ADK) and the A2A (Agent-to-Agent) protocol. It wraps a
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large language model (LLM)-based agent in an HTTP API and uses
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structured execution flows with streaming responses, memory, and tools.
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It is designed to make agents callable as network services and
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composable with other agents.
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services:
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- python
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- aiml
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- agentic-ai
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- title: ADK Multi-Agent Fact Checker
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url: https://github.com/docker/compose-for-agents/tree/main/adk
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description: >
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This project demonstrates a collaborative multi-agent system built with
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the Agent Development Kit (ADK), where a top-level Auditor agent coordinates
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the workflow to verify facts. The Critic agent gathers evidence via live
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internet searches using DuckDuckGo through the Model Context Protocol (MCP),
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while the Reviser agent analyzes and refines the conclusion using internal
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reasoning alone. The system showcases how agents with distinct roles and
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tools can collaborate under orchestration.
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services:
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- python
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- aiml
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- agentic-ai
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- title: DevDuck agents
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url: https://github.com/docker/compose-for-agents/tree/main/adk-cerebras
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description: >
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A multi-agent system for Go programming assistance built with Google
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Agent Development Kit (ADK). This project features a coordinating agent
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(DevDuck) that manages two specialized sub-agents (Bob and Cerebras)
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for different programming tasks.
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services:
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- python
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- aiml
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- agentic-ai
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- title: Agno
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url: https://github.com/docker/compose-for-agents/tree/main/agno
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description: >
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This app is a multi-agent orchestration system powered by LLMs (like Qwen
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and OpenAI) and connected to tools via a Model Control Protocol (MCP)
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gateway. Its purpose is to retrieve, summarize, and document GitHub
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issues—automatically creating Notion pages from the summaries. It also
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supports file content summarization from GitHub.
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services:
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- python
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- aiml
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- agentic-ai
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- title: CrewAI
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url: https://github.com/docker/compose-for-agents/tree/main/crew-ai
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description: >
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This project showcases an autonomous, multi-agent virtual marketing team
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built with CrewAI. It automates the creation of a high-quality, end-to-end
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marketing strategy — from research to copywriting — using task delegation,
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web search, and creative synthesis.
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services:
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- python
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- aiml
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- agentic-ai
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- title: SQL Agent with LangGraph
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url: https://github.com/docker/compose-for-agents/tree/main/langgraph
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description: >
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This project demonstrates a zero-config AI agent that uses LangGraph to
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answer natural language questions by querying a SQL database — all
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orchestrated with Docker Compose.
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services:
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- python
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- aiml
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- agentic-ai
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- title: Spring AI Brave Search Example - Model Context Protocol (MCP)
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url: https://github.com/docker/compose-for-agents/tree/main/spring-ai
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description: >
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This example demonstrates how to create a Spring AI Model Context Protocol
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(MCP) client that communicates with the Brave Search MCP Server. The
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application shows how to build an MCP client that enables natural language
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interactions with Brave Search, allowing you to perform internet searches
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through a conversational interface. This example uses Spring Boot
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autoconfiguration to set up the MCP client through configuration files.
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services:
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- java
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- aiml
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- agentic-ai
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- title: MCP UI with Vercel AI SDK
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url: https://github.com/docker/compose-for-agents/tree/main/a2a
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description: >
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Start an MCP UI application that uses the Vercel AI SDK to provide a
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chat interface for local models, provided by the Docker Model Runner,
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with access to MCPs from the Docker MCP Catalog.
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services:
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- aiml
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- agentic-ai
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