mirror of https://github.com/docker/docs.git
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>
This commit is contained in:
parent
7f9ec3f053
commit
6118d3dc9a
|
@ -35,4 +35,4 @@ Learn how to containerize different types of services by walking through Officia
|
||||||
|
|
||||||
## Other samples
|
## 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)
|
||||||
|
|
|
@ -0,0 +1,5 @@
|
||||||
|
---
|
||||||
|
title: Agentic AI samples
|
||||||
|
description: Docker samples for agentic AI.
|
||||||
|
service: agentic-ai
|
||||||
|
---
|
|
@ -350,4 +350,98 @@ samples:
|
||||||
description: Get started with AI and ML using Docker, Neo4j, LangChain, and Ollama
|
description: Get started with AI and ML using Docker, Neo4j, LangChain, and Ollama
|
||||||
services:
|
services:
|
||||||
- python
|
- python
|
||||||
- aiml
|
- 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
|
Loading…
Reference in New Issue