Merge pull request #380 from ggozad/chore/zensical

New documentation site based on Zensical
This commit is contained in:
Yiorgis Gozadinos 2026-05-20 17:03:04 +03:00 committed by GitHub
commit 323668672f
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13 changed files with 392 additions and 344 deletions

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@ -4,25 +4,30 @@ on:
branches:
- main
permissions:
contents: write
contents: read
pages: write
id-token: write
concurrency:
group: pages
cancel-in-progress: false
jobs:
deploy:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Configure Git Credentials
run: |
git config user.name github-actions[bot]
git config user.email 41898282+github-actions[bot]@users.noreply.github.com
- uses: actions/setup-python@v5
- uses: astral-sh/setup-uv@v5
- run: uv sync --group dev
- run: uv run zensical build
- uses: actions/configure-pages@v5
- uses: actions/upload-pages-artifact@v3
with:
python-version: 3.x
- run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV
- uses: actions/cache@v4
with:
key: mkdocs-material-${{ env.cache_id }}
path: .cache
restore-keys: |
mkdocs-material-
- run: pip install mkdocs-material
- run: mkdocs gh-deploy --force
path: ./site
deploy:
needs: build
runs-on: ubuntu-latest
environment:
name: github-pages
url: ${{ steps.deployment.outputs.page_url }}
steps:
- id: deployment
uses: actions/deploy-pages@v4

2
.gitignore vendored
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@ -29,5 +29,5 @@ DEVNOTES.md
.mcpregistry_github_token
.mcpregistry_registry_token
# MkDocs site directory when doing local docs builds
# zensical site directory when doing local docs builds
site/

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@ -1,6 +1,10 @@
# Changelog
## [Unreleased]
### Changed
- Documentation generator swapped from `mkdocs-material` to `zensical`. Drops `mkdocs` / `mkdocs-material` dev deps, replaces `mkdocs.yml` with `zensical.toml`, adds `overrides/main.html` (OG/Twitter share meta) and `docs/stylesheets/extra.css`. `build-docs` workflow now runs `uv run zensical build` and publishes via the GitHub Pages artifact actions instead of `mkdocs gh-deploy`.
## [0.48.0] - 2026-05-20
### Added

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@ -133,12 +133,11 @@ See the [examples directory](examples/) for working examples:
Full documentation at: https://ggozad.github.io/haiku.rag/
- [Installation](https://ggozad.github.io/haiku.rag/installation/) - Provider setup
- [Architecture](https://ggozad.github.io/haiku.rag/architecture/) - System overview
- [Configuration](https://ggozad.github.io/haiku.rag/configuration/) - YAML configuration
- [CLI](https://ggozad.github.io/haiku.rag/cli/) - Command reference
- [Python API](https://ggozad.github.io/haiku.rag/python/) - Complete API docs
- [Skills](https://ggozad.github.io/haiku.rag/skills/) - The RAG and analysis skills the client wraps
- [Analysis](https://ggozad.github.io/haiku.rag/agents/analysis/) - Complex analytical tasks via code execution
- [Analysis skill](https://ggozad.github.io/haiku.rag/skills/analysis/) - Complex analytical tasks via code execution
- [Applications](https://ggozad.github.io/haiku.rag/apps/) - Chat TUI, web app, and inspector
- [Server](https://ggozad.github.io/haiku.rag/server/) - File monitoring and MCP
- [MCP](https://ggozad.github.io/haiku.rag/mcp/) - Model Context Protocol integration

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docs/img/hero.mp4 Normal file

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@ -1,47 +1,3 @@
# haiku.rag
haiku.rag is an agentic RAG that runs locally and scales to production. Index PDFs, web pages, or whole directories. Ask questions and get cited answers. Build agents, skills, and MCP integrations on top.
haiku.rag is open-source first. The defaults run open models through [Ollama](https://ollama.com/) so the full pipeline works without external API keys. Any provider Pydantic AI supports works in its place.
Built on [LanceDB](https://lancedb.com/), [Pydantic AI](https://ai.pydantic.dev/), and [Docling](https://docling-project.github.io/docling/). Embedded database, no servers required.
## See it work
```bash
uv pip install haiku.rag
ollama pull qwen3-embedding:4b
ollama pull gpt-oss
haiku-rag init
haiku-rag add-src ~/Documents/some-paper.pdf
haiku-rag chat
```
The chat TUI is one way to interact with the database. `haiku-rag ask` and `haiku-rag search` cover one-shot CLI usage. Python integrations, skills, and the MCP server work against the same database.
## What it does
**Ingest.** PDFs, DOCX, HTML, images, and 40+ formats via Docling. Add files, URLs, or whole directories. Monitor folders and reindex on change.
**Search.** Hybrid retrieval (vector + full-text with reciprocal rank fusion), optional cross-encoder reranking, structure-aware context expansion. Image-as-query and cross-modal retrieval when configured with a multimodal embedder.
**Answer.** RAG skill with citations including page numbers, section headings, and visual grounding. Vision-capable models receive figure bytes alongside chunk text. Analysis skill with a sandboxed Python interpreter for aggregation and computation across documents.
**Integrate.** Use it from Python, the CLI, the [MCP server](mcp.md), or as composable [skills](skills/index.md) built on haiku.skills. Skills bundle tools, prompts, and state for use inside any Pydantic AI agent.
**Operate.** Embedded LanceDB by default. Also runs on S3, GCS, Azure, or LanceDB Cloud. Time-travel queries via LanceDB versioning. File-monitoring mode for production deployments.
## Where to go next
- [Quickstart](tutorial.md): install, index, chat.
- [Skills](skills/index.md): the rag and rag-analysis skills you compose into Pydantic AI agents.
- [Python API](python.md): use haiku.rag from code.
- [MCP server](mcp.md): expose haiku.rag to Claude Desktop or other AI assistants.
- [Tuning](tuning.md): improve retrieval quality.
- [Configuration](configuration/index.md): every setting.
## License
MIT. Source on [GitHub](https://github.com/ggozad/haiku.rag).
---
title: haiku.rag
---

47
docs/overview.md Normal file
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@ -0,0 +1,47 @@
# Overview
haiku.rag is an agentic RAG that runs locally and scales to production. Index PDFs, web pages, or whole directories. Ask questions and get cited answers. Build agents, skills, and MCP integrations on top.
haiku.rag is open-source first. The defaults run open models through [Ollama](https://ollama.com/) so the full pipeline works without external API keys. Any provider Pydantic AI supports works in its place.
Built on [LanceDB](https://lancedb.com/), [Pydantic AI](https://ai.pydantic.dev/), and [Docling](https://docling-project.github.io/docling/). Embedded database, no servers required.
## See it work
```bash
uv pip install haiku.rag
ollama pull qwen3-embedding:4b
ollama pull gpt-oss
haiku-rag init
haiku-rag add-src ~/Documents/some-paper.pdf
haiku-rag chat
```
The chat TUI is one way to interact with the database. `haiku-rag ask` and `haiku-rag search` cover one-shot CLI usage. Python integrations, skills, and the MCP server work against the same database.
## What it does
**Ingest.** PDFs, DOCX, HTML, images, and 40+ formats via Docling. Add files, URLs, or whole directories. Monitor folders and reindex on change.
**Search.** Hybrid retrieval (vector + full-text with reciprocal rank fusion), optional cross-encoder reranking, structure-aware context expansion. Image-as-query and cross-modal retrieval when configured with a multimodal embedder.
**Answer.** RAG skill with citations including page numbers, section headings, and visual grounding. Vision-capable models receive figure bytes alongside chunk text. Analysis skill with a sandboxed Python interpreter for aggregation and computation across documents.
**Integrate.** Use it from Python, the CLI, the [MCP server](mcp.md), or as composable [skills](skills/index.md) built on haiku.skills. Skills bundle tools, prompts, and state for use inside any Pydantic AI agent.
**Operate.** Embedded LanceDB by default. Also runs on S3, GCS, Azure, or LanceDB Cloud. Time-travel queries via LanceDB versioning. File-monitoring mode for production deployments.
## Where to go next
- [Quickstart](tutorial.md): install, index, chat.
- [Skills](skills/index.md): the rag and rag-analysis skills you compose into Pydantic AI agents.
- [Python API](python.md): use haiku.rag from code.
- [MCP server](mcp.md): expose haiku.rag to Claude Desktop or other AI assistants.
- [Tuning](tuning.md): improve retrieval quality.
- [Configuration](configuration/index.md): every setting.
## License
MIT. Source on [GitHub](https://github.com/ggozad/haiku.rag).

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@ -0,0 +1,53 @@
.haiku-rag-hero {
padding: 2rem 0 2.5rem;
}
.haiku-rag-hero__inner {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 2.5rem;
align-items: center;
}
@media (max-width: 60em) {
.haiku-rag-hero__inner {
grid-template-columns: 1fr;
gap: 1.5rem;
}
}
.haiku-rag-hero__title {
font-family: var(--md-code-font, monospace);
font-size: 4.5rem;
font-weight: 700;
line-height: 1;
margin: 0 0 0.75rem;
color: var(--md-primary-fg-color);
letter-spacing: -0.02em;
}
.haiku-rag-hero__tagline {
font-size: 1.15rem;
line-height: 1.5;
color: var(--md-default-fg-color--light);
margin: 0 0 1.5rem;
}
.haiku-rag-hero__actions {
display: flex;
gap: 0.75rem;
flex-wrap: wrap;
}
.haiku-rag-hero__media img,
.haiku-rag-hero__media video {
display: block;
width: 100%;
height: auto;
border-radius: 0.5rem;
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.25);
}
body:has(.haiku-rag-hero) .md-main {
display: none;
}

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@ -1,107 +0,0 @@
site_name: haiku.rag
site_description: Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling.
site_url: https://ggozad.github.io/haiku.rag/
theme:
name: material
palette:
- media: "(prefers-color-scheme)"
toggle:
icon: material/lightbulb-auto
name: Switch to light mode
- media: "(prefers-color-scheme: light)"
scheme: default
primary: deep purple
accent: amber
toggle:
icon: material/lightbulb
name: Switch to dark mode
- media: "(prefers-color-scheme: dark)"
scheme: slate
primary: deep purple
accent: amber
toggle:
icon: material/lightbulb-outline
name: Switch to system preference
features:
- content.code.annotate
- content.code.copy
- content.code.select
- content.footnote.tooltips
- content.tabs.link
- content.tooltips
- navigation.footer
- navigation.indexes
- navigation.instant
- navigation.instant.prefetch
- navigation.instant.progress
- navigation.path
- navigation.tabs
- navigation.tabs.sticky
- navigation.top
- navigation.tracking
- search.highlight
- search.share
- search.suggest
- toc.follow
icon:
repo: fontawesome/brands/github-alt
# logo: img/icon-white.svg
# favicon: img/favicon.png
language: en
repo_name: ggozad/haiku.rag
repo_url: https://github.com/ggozad/haiku.rag
plugins:
# Material for MkDocs
search:
nav:
- Get started:
- index.md
- Quickstart: tutorial.md
- Installation: installation.md
- Use it:
- CLI: cli.md
- Chat: chat.md
- Skills:
- skills/index.md
- RAG skill: skills/rag.md
- Analysis skill: skills/analysis.md
- Custom skills: skills/custom.md
- Configure:
- configuration/index.md
- Providers: configuration/providers.md
- Search and question answering: configuration/qa.md
- Document processing: configuration/processing.md
- Storage: configuration/storage.md
- Prompts: configuration/prompts.md
- Tuning: tuning.md
- Production:
- Server: server.md
- MCP: mcp.md
- Remote processing: remote-processing.md
- Develop:
- Python: python.md
- Custom pipelines: custom-pipelines.md
- Toolsets: tools.md
- Web app: apps.md
- Reference:
- Benchmarks: benchmarks.md
- Development: development.md
- Changelog: changelog.md
markdown_extensions:
- admonition
- attr_list
- pymdownx.details
- pymdownx.highlight:
anchor_linenums: true
line_spans: __span
pygments_lang_class: true
use_pygments: true
- pymdownx.inlinehilite
- pymdownx.snippets:
base_path: ["."]
- pymdownx.superfences:
custom_fences:
- name: mermaid
class: mermaid
format: !!python/name:pymdownx.superfences.fence_code_format

35
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@ -0,0 +1,35 @@
{% extends "base.html" %}
{% block extrahead %}
<meta property="og:type" content="website">
<meta property="og:title" content="{% if page.title and page.title != config.site_name %}{{ page.title }} {{ config.site_name }}{% else %}{{ config.site_name }}{% endif %}">
<meta property="og:description" content="{{ config.site_description }}">
<meta property="og:url" content="{{ page.canonical_url }}">
<meta property="og:image" content="{{ config.site_url }}img/chat-qa.png">
<meta name="twitter:card" content="summary_large_image">
<meta name="twitter:image" content="{{ config.site_url }}img/chat-qa.png">
{% endblock %}
{% block hero %}
{% if page.url == "" %}
<section class="haiku-rag-hero">
<div class="md-typeset md-grid">
<div class="haiku-rag-hero__inner">
<div class="haiku-rag-hero__text">
<h1 class="haiku-rag-hero__title">haiku.rag</h1>
<p class="haiku-rag-hero__tagline">Opinionated agentic RAG powered by <a href="https://lancedb.com/">LanceDB</a>, <a href="https://ai.pydantic.dev/">Pydantic AI</a>, and <a href="https://docling-project.github.io/docling/">Docling</a>. Runs locally, scales to production.</p>
<div class="haiku-rag-hero__actions">
<a class="md-button md-button--primary" href="tutorial/">Get started</a>
<a class="md-button" href="overview/">Learn more</a>
</div>
</div>
<div class="haiku-rag-hero__media">
<video autoplay loop muted playsinline preload="auto" poster="img/chat-qa.png">
<source src="img/hero.mp4" type="video/mp4">
</video>
</div>
</div>
</div>
</section>
{% endif %}
{% endblock %}

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@ -71,8 +71,7 @@ dev = [
"haiku.rag-evals",
"datasets>=4.8.4",
"obstore>=0.9,<0.10",
"mkdocs>=1.6.1",
"mkdocs-material>=9.7.6",
"zensical",
"pre-commit>=4.5.1",
"pydantic-ai-slim[anthropic]",
"pydantic-ai-slim[bedrock]",

260
uv.lock
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@ -1479,8 +1453,6 @@ tui = [
dev = [
{ name = "datasets" },
{ name = "haiku-rag-evals" },
{ name = "mkdocs" },
{ name = "mkdocs-material" },
{ name = "obstore" },
{ name = "pre-commit" },
{ name = "pydantic-ai-slim", extra = ["anthropic", "bedrock", "google", "groq"] },
@ -1491,6 +1463,7 @@ dev = [
{ name = "pytest-xdist" },
{ name = "ruff" },
{ name = "ty" },
{ name = "zensical" },
]
[package.metadata]
@ -1506,8 +1479,6 @@ provides-extras = ["tui", "s3", "cross-encoder"]
dev = [
{ name = "datasets", specifier = ">=4.8.4" },
{ name = "haiku-rag-evals", editable = "evaluations" },
{ name = "mkdocs", specifier = ">=1.6.1" },
{ name = "mkdocs-material", specifier = ">=9.7.6" },
{ name = "obstore", specifier = ">=0.9,<0.10" },
{ name = "pre-commit", specifier = ">=4.5.1" },
{ name = "pydantic-ai-slim", extras = ["anthropic"] },
@ -1521,6 +1492,7 @@ dev = [
{ name = "pytest-xdist", specifier = ">=3.8.0" },
{ name = "ruff", specifier = ">=0.15.9" },
{ name = "ty", specifier = ">=0.0.28" },
{ name = "zensical" },
]
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[[package]]
name = "zeroentropy"
version = "0.1.0a11"

133
zensical.toml Normal file
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[project]
site_name = "haiku.rag"
site_description = "Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling."
site_url = "https://ggozad.github.io/haiku.rag/"
repo_url = "https://github.com/ggozad/haiku.rag"
repo_name = "ggozad/haiku.rag"
site_author = "Yiorgis Gozadinos"
copyright = "Copyright &copy; 2025&ndash;2026 Yiorgis Gozadinos"
extra_css = ["stylesheets/extra.css"]
nav = [
{ "Get started" = [
"index.md",
{ Overview = "overview.md" },
{ Quickstart = "tutorial.md" },
{ Installation = "installation.md" },
] },
{ "Use it" = [
{ CLI = "cli.md" },
{ Chat = "chat.md" },
] },
{ Skills = [
"skills/index.md",
{ "RAG skill" = "skills/rag.md" },
{ "Analysis skill" = "skills/analysis.md" },
{ "Custom skills" = "skills/custom.md" },
] },
{ Configure = [
"configuration/index.md",
{ Providers = "configuration/providers.md" },
{ "Search and question answering" = "configuration/qa.md" },
{ "Document processing" = "configuration/processing.md" },
{ Storage = "configuration/storage.md" },
{ Prompts = "configuration/prompts.md" },
{ Tuning = "tuning.md" },
] },
{ Production = [
{ Server = "server.md" },
{ MCP = "mcp.md" },
{ "Remote processing" = "remote-processing.md" },
] },
{ Develop = [
{ Python = "python.md" },
{ "Custom pipelines" = "custom-pipelines.md" },
{ Toolsets = "tools.md" },
{ "Web app" = "apps.md" },
] },
{ Reference = [
{ Benchmarks = "benchmarks.md" },
{ Development = "development.md" },
{ Changelog = "changelog.md" },
] },
]
[project.theme]
custom_dir = "overrides"
font.code = "JetBrains Mono"
features = [
"content.action.view",
"content.code.annotate",
"content.code.copy",
"content.code.select",
"content.footnote.tooltips",
"content.tabs.link",
"content.tooltips",
"navigation.footer",
"navigation.indexes",
"navigation.instant",
"navigation.instant.prefetch",
"navigation.instant.progress",
"navigation.path",
"navigation.tabs",
"navigation.tabs.sticky",
"navigation.top",
"navigation.tracking",
"search.highlight",
"search.share",
"search.suggest",
"toc.follow",
]
[project.theme.icon]
repo = "fontawesome/brands/github-alt"
[[project.theme.palette]]
media = "(prefers-color-scheme)"
toggle.icon = "material/lightbulb-auto"
toggle.name = "Switch to light mode"
[[project.theme.palette]]
media = "(prefers-color-scheme: light)"
scheme = "default"
primary = "deep purple"
accent = "amber"
toggle.icon = "material/lightbulb"
toggle.name = "Switch to dark mode"
[[project.theme.palette]]
media = "(prefers-color-scheme: dark)"
scheme = "slate"
primary = "deep purple"
accent = "amber"
toggle.icon = "material/lightbulb-outline"
toggle.name = "Switch to system preference"
[project.markdown_extensions.admonition]
[project.markdown_extensions.attr_list]
[project.markdown_extensions."pymdownx.details"]
[project.markdown_extensions."pymdownx.inlinehilite"]
[project.markdown_extensions."pymdownx.highlight"]
anchor_linenums = true
line_spans = "__span"
pygments_lang_class = true
use_pygments = true
[project.markdown_extensions."pymdownx.snippets"]
base_path = ["."]
[project.markdown_extensions."pymdownx.superfences"]
custom_fences = [
{ name = "mermaid", class = "mermaid", format = "pymdownx.superfences.fence_code_format" },
]
[[project.extra.social]]
icon = "fontawesome/brands/github"
link = "https://github.com/ggozad/haiku.rag"
name = "haiku.rag on GitHub"
[[project.extra.social]]
icon = "simple/pypi"
link = "https://pypi.org/project/haiku.rag/"
name = "haiku.rag on PyPI"