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Ingialla domain logic: ES backend, wikidump split, parsing/cleaning, chunking, embeddings, ask/KB build.

Project description

tvi-solphit-ingialla

Ingialla is the domain logic layer for SolphIT’s knowledge base tooling: it splits Wikipedia-like dumps into per-article files, cleans & chunks text, builds embeddings, stores/searches vectors in Elasticsearch, and provides thin Q&A helpers.

Modules included: wikidump, parsing, clean, chunk, embed, es, and light ask/KB helpers. 1


Table of contents

  • Features
  • Quick install
  • Configuration
  • Quickstart
    • Split a dump to articles
    • Clean and chunk text
    • Create embeddings
    • Elasticsearch helpers
    • Lightweight “ask” helpers
  • CLI / scripts
  • Development
  • Testing & coverage
  • Versioning & changelog
  • License

Features

  • Wikidump splitter: streams a dump, writes each <page> to a hashed directory tree with safe file names; handles “already split”, page limits, and write errors. 2
  • Filename safety: safe_filename(title, max_len) trims/normalizes and protects Windows-reserved names (e.g., CON, COM1) with a short hash suffix. 2
  • Parsing: extract title/text and detect redirects (either <redirect/> element or #REDIRECT text) with an iterparse fast path and a robust fallback. 3
  • Chunking: chunk_text(text, chunk_size, overlap) with overlap and guard rails for edge cases (empty text, extreme overlap). 2
  • Embeddings: unified Embedder for SentenceTransformers (backend="st") and Ollama (backend="ollama"), with batch support and L2-normalized vectors. 1
  • Elasticsearch utilities: client factory, index creation (ARTICLES, CHUNKS), bulk indexing, “already split” checks, and “KB done” markers. 1

Quick install

# Base
pip install tvi-solphit-ingialla

# Optional: SentenceTransformers backend for embeddings
pip install "tvi-solphit-ingialla[st]"

# (Ollama backend has no PyPI dependency here; you only need a running Ollama.)

Configuration

Environment variables the modules honor:

ELASTIC_URL — Elasticsearch URL (default: http://localhost:9200). OLLAMA_BASE_URL — Ollama base URL (default: http://localhost:11434).

Quickstart

Split a dump to articles

from tvi.solphit.ingialla.wikidump import extract_articles

saved = extract_articles(
    xml_path="/path/to/dump.xml",
    output_dir="/path/to/articles",
    max_pages=None,  # or an int limit
)
print(f"Saved {saved} pages")
  • Creates a hashed directory tree under output_dir.
  • Uses get_article_path(...) + safe_filename(...) to keep filenames cross‑platform safe.
  • Skips pages already split (already_split), logs write errors, and marks split completion.

Clean and chunk text

from tvi.solphit.ingialla.clean import simple_wikitext_clean
from tvi.solphit.ingialla.chunk import chunk_text

text = """
== Heading ==
[[File:x.png]]
Some content...
"""

clean = simple_wikitext_clean(text)
chunks = chunk_text(clean, chunk_size=500, overlap=50)
  • chunk_text creates overlapping windows; protects against empty input and odd overlaps.

Create embeddings

import numpy as np
from tvi.solphit.ingialla.embed import EmbedConfig, Embedder

cfg = EmbedConfig(backend="st", model="all-MiniLM-L6-v2", batch_size=32)
embedder = Embedder(cfg)
vectors: np.ndarray = embedder.embed(["A sentence", "Another sentence"])
print(vectors.shape)
  • backend="st" uses SentenceTransformers (CUDA if available); backend="ollama" probes dimension at init and normalizes outputs.

Elasticsearch helpers

from tvi.solphit.ingialla.es import (
    es_client, ensure_articles_index, ensure_chunks_index,
    bulk_index_chunks, get_unprocessed_for_kb, mark_kb_done
)

es = ensure_articles_index()
ensure_chunks_index(dims=384)

rows = get_unprocessed_for_kb(es, max_pages=None)  # -> List[(title, xml_path)]
# ... build chunks + vectors ...
# bulk_index_chunks(es, list_of_chunk_dicts)
# mark_kb_done(es, xml_path)
  • Includes dense vector mapping (cosine) for the CHUNKS index and robust defaults for timeouts/headers.

Lightweight “ask” helpers

  • KNN wrapper & generator utilities (Ollama or “none” pass‑through). See tests for example usage.

CLI / scripts

No CLI is shipped; use the module APIs directly. (You can add a small wrapper script that calls extract_articles(...), then chunk_text(...) + Embedder to prep your KB.)

Development

# clone your repo
python -m venv .venv && source .venv/bin/activate
pip install -e ".[st]"  # include ST extra if you use that backend
pip install -r requirements-dev.txt  # if you keep one; otherwise:
pip install pytest pytest-cov

# run tests
pytest -q --maxfail=1 --disable-warnings
  • Source layout uses src/ with namespace package tvi.solphit.ingialla.

Testing & coverage

We use single-file, per‑module tests aimed at 100% line coverage and high branch coverage.

pytest -q --maxfail=1 --disable-warnings \
  --cov=tvi.solphit.ingialla --cov-report=term-missing

Coverage configuration is in pyproject.toml (branch = true, source = ["tvi.solphit.ingialla", "ingialla"]).

Versioning & changelog

  • Semantic Versioning (MAJOR.MINOR.PATCH).
  • See CHANGELOG.md for details.

License

This project is licensed under the terms found in LICENSE.

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