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docs: ship MkDocs Material site on GitHub Pages
Turn the existing docs/ folder into a searchable, navigable site at datallmhub.github.io/agentflow4j — same content, better discovery surface for both humans and LLM training corpora. - mkdocs.yml: Material theme, dark default, structured nav (Get started / Governance / Resilience & runtime / Recipes / Tutorials / Testing / Samples), pymdownx extensions for code blocks and tables - docs/index.md: landing page mirroring the README hook with deep links into the doc sections - .github/workflows/docs.yml: build + deploy to GitHub Pages on every docs/ or mkdocs.yml change, using mkdocs --strict No build step required of users — Maven/Java workflow unchanged. The site is a parallel surface, the README and JitPack flow stay primary. To activate: Settings → Pages → Source: GitHub Actions.
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‎.github/workflows/docs.yml‎

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name: docs
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on:
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push:
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branches: [main]
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paths:
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- 'docs/**'
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- 'mkdocs.yml'
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- '.github/workflows/docs.yml'
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workflow_dispatch:
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permissions:
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contents: read
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pages: write
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id-token: write
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concurrency:
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group: pages
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cancel-in-progress: false
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jobs:
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build:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-python@v5
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with:
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python-version: '3.x'
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- name: Install MkDocs Material
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run: pip install --quiet mkdocs-material
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- name: Build site
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run: mkdocs build --strict
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- name: Upload artifact
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uses: actions/upload-pages-artifact@v3
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with:
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path: site
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deploy:
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needs: build
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runs-on: ubuntu-latest
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environment:
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name: github-pages
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url: ${{ steps.deployment.outputs.page_url }}
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steps:
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- name: Deploy to GitHub Pages
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id: deployment
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uses: actions/deploy-pages@v4

‎docs/index.md‎

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# AgentFlow4J
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**Build governed, stateful multi-agent workflows in Java — orchestration, persistence, and runtime observability.**
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Spring AI gives you LLM primitives (`ChatClient`, tools). **AgentFlow4J gives you a structured runtime for multi-step systems.** Going from single prompts to multi-agent workflows makes execution stateful, failure-prone, and hard to inspect. AgentFlow4J provides the execution graph, durable state, and governance gates to run those workflows safely — all in idiomatic Java, no sidecar, no YAML.
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[:material-rocket-launch: Get started](two-api-levels.md){ .md-button .md-button--primary }
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[:material-github: GitHub repo](https://github.com/datallmhub/agentflow4j){ .md-button }
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[:material-package: JitPack](https://jitpack.io/#datallmhub/agentflow4j){ .md-button }
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---
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## What you get
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| Spring AI | AgentFlow4J runtime |
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|---|---|
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| Primitives (`ChatClient`, tools) | Structured execution (`AgentGraph`, `CoordinatorAgent`) |
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| Manual orchestration glue | Graph-based execution & dynamic routing |
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| No durable state | Typed shared state (`StateKey<T>`) + checkpoints |
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| Retry logic in user code | Built-in retry & circuit-breaker policies |
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| No resume | Interrupt & resume from the last valid checkpoint |
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| Agents fully trusted | Governed execution — tool, state-write, budget and approval gates |
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---
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## Try it in 30 seconds
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```bash
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git clone https://github.com/datallmhub/agentflow4j.git
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cd agentflow4j
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mvn install -DskipTests -q
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mvn -pl agentflow4j-samples exec:java
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```
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Runs `SupportTriageDemo` — a customer-support ticket flowing through a graph: `triage → specialist → policy gate → reply`. Falls back to deterministic stubs offline, or calls Mistral when `MISTRAL_API_KEY` is set.
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---
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## Where to next
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- **New here?** Start with [Two API levels](two-api-levels.md) — the Squad vs Graph distinction.
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- **Worried about cost or unsafe actions?** Read the [governance trilogy](tool-policy.md): tool, state and approval gates.
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- **Building for production?** [Durable runs](recipes/durable-runs.md) shows how to survive a mid-workflow crash.
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- **Want the full story?** The [Stop your agent burning $1000 overnight](tutorials/stop-your-agent-burning-money.md) tutorial walks through every governance piece end-to-end.
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---
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!!! note "Scope"
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AgentFlow4J is an independent open-source project. It is **not** an official Spring project.

‎mkdocs.yml‎

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site_name: AgentFlow4J
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site_description: Java/Spring runtime for governed multi-agent LLM workflows — orchestration, durable runs, runtime observability.
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site_url: https://datallmhub.github.io/agentflow4j/
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site_author: agentflow4j
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repo_url: https://github.com/datallmhub/agentflow4j
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repo_name: datallmhub/agentflow4j
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edit_uri: edit/main/docs/
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docs_dir: docs
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theme:
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name: material
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language: en
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features:
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- navigation.sections
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- navigation.indexes
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- navigation.top
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- navigation.tracking
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- search.suggest
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- search.highlight
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- content.code.copy
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- content.action.edit
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- toc.follow
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palette:
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- media: "(prefers-color-scheme: dark)"
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scheme: slate
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primary: indigo
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accent: indigo
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toggle:
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icon: material/brightness-4
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name: Switch to light mode
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- media: "(prefers-color-scheme: light)"
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scheme: default
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primary: indigo
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accent: indigo
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toggle:
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icon: material/brightness-7
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name: Switch to dark mode
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font:
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text: Inter
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code: JetBrains Mono
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icon:
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repo: fontawesome/brands/github
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markdown_extensions:
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- admonition
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- attr_list
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- md_in_html
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- tables
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- toc:
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permalink: true
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- pymdownx.highlight:
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anchor_linenums: true
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line_spans: __span
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pygments_lang_class: true
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- pymdownx.inlinehilite
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- pymdownx.superfences
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- pymdownx.snippets
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- pymdownx.tabbed:
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alternate_style: true
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- pymdownx.details
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- pymdownx.emoji:
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emoji_index: !!python/name:material.extensions.emoji.twemoji
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emoji_generator: !!python/name:material.extensions.emoji.to_svg
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nav:
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- Home: index.md
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- Get started:
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- Two API levels: two-api-levels.md
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- LLM providers: llm-providers.md
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- Typed state: state.md
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- Governance:
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- Tool policy: tool-policy.md
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- State policy: state-policy.md
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- Approval gate: approval-gate.md
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- Resilience & runtime:
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- Resilience & error handling: resilience.md
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- Run log: run-log.md
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- Observability: observability.md
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- Streaming: streaming.md
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- Recipes:
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- Approval via Slack: recipes/approval-via-slack.md
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- Durable runs: recipes/durable-runs.md
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- Tutorials:
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- "Stop your agent burning $1000 overnight": tutorials/stop-your-agent-burning-money.md
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- Testing: testing.md
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- Samples: samples.md
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extra:
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social:
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- icon: fontawesome/brands/github
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link: https://github.com/datallmhub/agentflow4j

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