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Yiorgis Gozadinos da6cdfbc51
Resolve file:// URIs to paths through url2pathname 
urlparse().path keeps the leading slash in front of a Windows drive, so
file:///C:/docs/a.pdf read as \C:\docs\a.pdf and the ingester reported
"File does not exist" for every file it discovered. url2pathname is the
stdlib conversion that strips it, per platform.

Four sites each decided both "is this local" and "what path is this":
FSSource._uri_to_path and supports, resolve_adhoc_fetcher,
create_document_from_source and check_source_accessible, and convert.
is_local_uri and uri_to_path in haiku.rag.uri own those two decisions now,
which closes two more cases of the same root cause. A bare C:\docs\a.pdf
parses with scheme "c", so add-src raised "No source adapter for URI scheme
'c'" and convert silently treated the path as raw text. And convert and
check_source_accessible never percent-decoded at all, so a file named
a[b] c.md read as missing on Linux and macOS too.

A file URI's host is reattached after conversion rather than passed to
url2pathname, which as of 3.14 rejects a non-local authority off Windows.
file:////server/share is the empty-authority spelling of a UNC path, its
host being the first path segment, so that host is normalised into the
authority before conversion. Output is identical on 3.12, 3.13 and 3.14.

The ad-hoc FS fetcher roots at the path's own anchor rather than "/", which
on Windows is only the current drive.

test_uri.py runs on ubuntu, macos and windows across 3.13 and 3.14 without
the project installed: --noconftest because the repo conftest imports
dependencies that job does not need, and -o addopts= to drop the
repository's -n auto. The Windows legs are what cover the drive conversion.

Fixes #574.
2026-08-21 10:22:26 +03:00
..
haiku/rag Resolve file:// URIs to paths through url2pathname 2026-08-21 10:22:26 +03:00
LICENSE Restructure into uv workspace to support minimal and full installations 2025-11-04 17:59:12 +02:00
pyproject.toml vb 2026-08-20 15:48:23 +03:00
README.md Give the docs an architecture page and one extras list 2026-08-20 15:07:06 +03:00

README.md

haiku.rag-slim

Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling - Core package with minimal dependencies.

haiku.rag-slim is the core package for users who want to install only the dependencies they need. Document processing (docling), and reranker support are all optional extras.

For most users, we recommend installing haiku.rag instead, which includes all features out of the box.

Installation

Python 3.12 or newer required

Minimal Installation

uv pip install haiku.rag-slim

Core functionality with OpenAI/Ollama support, MCP server, and Logfire observability. Document processing (docling) is optional.

With Document Processing

uv pip install haiku.rag-slim[docling]

Adds support for 40+ file formats including PDF, DOCX, HTML, and more.

Available Extras

docling, tui, voyageai, cohere, zeroentropy, cross-encoder, jina, s3, ingester, and one per model provider: anthropic, google, groq, mistral, bedrock, vertexai. Ollama and any OpenAI-compatible endpoint need no extra.

What each provides, and which ones the full haiku.rag package already includes: Installation.

# Common combinations
uv pip install 'haiku.rag-slim[docling,anthropic,cross-encoder]'
uv pip install 'haiku.rag-slim[docling,groq]'

Usage

See the main haiku.rag repository for:

  • Quick start guide
  • CLI examples
  • Python API usage
  • MCP server setup

Documentation

Full documentation: https://ggozad.github.io/haiku.rag/