citeindex 0.12.4

Ingest sources with proper citation — PDF, URL, media, Office, DJVU

CiteIndex

CiteIndex, ingest sources with proper citation. PDF, URL, media, Office, DJVU.

Deterministic citation extraction, Merkle-verified integrity, CJK-first OCR. Every claim is traced, verified, and cited — no hallucinations.

Install

# Using uv (recommended)
uv pip install citeindex

# Or pip
pip install citeindex

CLI

# Ingest a PDF
citeindex paper.pdf

# Ingest a scanned PDF with the default MinerU backend
citeindex scanned.pdf --ocr-engine mineru

# Use the optional GLM-OCR backend via local Ollama
citeindex scanned.pdf --ocr-engine glm-ocr --ocr-model glm-ocr:latest

# Ingest a URL
citeindex https://example.com/article

# Crawl and ingest all articles from a site
citeindex https://example.com/articles --all-url-article --crawl-depth 2

# Crawl and re-ingest only changed pages
citeindex https://example.com/articles --update-url-article

# Options
citeindex paper.pdf --llm ollama/qwen3 --type thesis --is-primary
citeindex paper.pdf --text-direction vertical --vertical-lang ch
citeindex scanned.pdf --ocr-engine mineru --lang auto --page-range "1-10"
citeindex paper.pdf --no-layout  # disable column/footnote detection
citeindex -v paper.pdf           # verbose/debug logging

Python API

from citeindex import ingest, IngestionConfig, IngestionFailure, PipelineResult

# Simple
result = ingest("paper.pdf")
print(result["status"])  # "ok"

# With config
config = IngestionConfig(
    llm_model="ollama/qwen3",
    text_direction="vertical",
    is_primary=True,
)
result = ingest("paper.pdf", corpus_root="my_corpus", config=config)

Ingestion Pipelines

CiteIndex automatically detects the input type and routes to the correct pipeline:

Digital PDF

PDF → PyMuPDF (text + images) → GROBID / DSPy citation enrichment
    → page-paragraph document structure
    → PageIndex tree (default, LLM-driven)
    → section_tree + heading injection for document.json / library markdown
    → Merkle tree → store to corpus/

• GROBID extracts metadata and references deterministically
• PyMuPDF extracts page text directly from digital PDFs and pulls embedded images
• DSPy reconciles GROBID output with pattern extraction as fallback
• Builds page-based document structure and augments it with PageIndex section headings
• PageIndex builds LLM-driven section hierarchy, persists it to corpus, and feeds library markdown headings

Scanned PDF

PDF → scanned backend selector
    → MinerU (default) OR GLM-OCR + PaddleOCR LayoutDetection
    → normalized content_list / markdown / extracted figures
    → DSPy-backed metadata extraction
    → document structure + PageIndex tree (default)
    → Merkle tree → store only CiteIndex-native artifacts to corpus/

• MinerU is the default scanned backend
• GLM-OCR is an optional backend that runs through local Ollama using the native /api/generate endpoint
• PaddleOCR LayoutDetection (PP-DocLayoutV3 / PP-DocLayout_plus-L) supplies external region proposals for GLM-OCR from the start
• Scanned PDFs do not use GROBID; metadata is extracted from structured backend output via DSPy-backed extraction
• DSPy is allowed to overwrite pattern-extracted metadata fields for scanned documents
• PageIndex runs by default for scanned PDFs, just like digital PDFs
• Only extracted figures / illustrations are exported into the corpus images/ folder; raw backend artifacts are not preserved
• Supports --ocr-engine mineru or --ocr-engine glm-ocr

Scanned PDF Backend Selection

Use the scanned backend flags only for image-based PDFs:

# Default scanned backend
citeindex scanned.pdf --ocr-engine mineru

# Local GLM-OCR through Ollama
citeindex scanned.pdf --ocr-engine glm-ocr --ocr-model glm-ocr:latest

# Custom Ollama host
citeindex scanned.pdf --ocr-engine glm-ocr --ollama-host http://localhost:11434

• mineru is the default and recommended general-purpose backend
• glm-ocr requires a local Ollama model plus PaddleOCR layout-detection dependencies
• --mineru-backend is forwarded directly to the MinerU CLI backend selector

URL Article

URL → Playwright/requests (fetch) → trafilatura/readability (content)
    → Zotero (metadata) → in-page citation guidance (regex → DSPy fallback)
    → section-hierarchical paragraphs → PageIndex tree (optional)
    → hashes → Merkle tree → store to corpus/

• Playwright renders JavaScript-heavy pages (fallback to requests)
• trafilatura extracts clean markdown with heading structure (fallback to readability-lxml)
• Zotero extracts citation metadata via translation-server (title, authors, date, DOI)
• Discovers in-page citation guidance: 若要引用 / 引用格式 / Cite this / Zitierweise / Pour citer
• Parses citation strings with regex first, DSPy fallback for unparseable formats
• Citation guidance overrides Zotero/trafilatura metadata (more authoritative)
• Supports batch crawling with --all-url-article and --update-url-article

Media

URL/File → yt-dlp (download) → ffmpeg (audio) → WhisperX (transcription)
        → pyannote (diarization, optional) → CSL JSON
        → chunking → hashes → Merkle tree → store to corpus/

• yt-dlp downloads from YouTube, Vimeo, podcasts, etc.
• WhisperX transcribes with word-level timestamps
• pyannote speaker diarization (optional)
• Supports audio (.mp3, .wav, .m4a) and video (.mp4, .mkv, .webm)

Office & DJVU

Office documents (.docx, .doc, .rtf, .odt, .pptx, .ppt, .odp) are converted to PDF via LibreOffice, and DJVU (.djvu) via ddjvu, then routed to the digital or scanned PDF pipeline.

Citation Enrichment Cascade

For PDF inputs, CiteIndex enriches metadata through a priority cascade:

1. GROBID — deterministic metadata + references (primary)
2. LLM extraction — DSPy-based citation parsing (fallback)
3. PDF metadata — basic file metadata only (last resort)

For web pages with ambiguous metadata, a local Perplexica search API can fill missing citation fields (title, author, publisher).

Configuration Reference

Option	CLI Flag	Default	Description
llm_model	--llm	ollama/deepseek-v4-flash:cloud	LLM model (ollama/name or gemini/name)
ocr_engine	--ocr-engine	mineru	Scanned PDF OCR backend: mineru or glm-ocr
ocr_model	--ocr-model	glm-ocr:latest	Ollama model name used by model-backed OCR engines such as GLM-OCR
ollama_host	--ollama-host	http://localhost:11434	Ollama base URL for GLM-OCR requests
mineru_backend	--mineru-backend	pipeline	Backend value forwarded to the MinerU CLI
text_direction	--text-direction, -td	horizontal	horizontal, auto, or vertical
vertical_lang	--vertical-lang	ch	CJK language: ch (Chinese) or japan
lang	--lang, -l	auto	OCR language (auto-detect or Tesseract code)
page_range	--page-range, -p	1-5, -3	Pages to extract (e.g. "1-10", "1-5, -3")
doc_type_override	--type, -t	auto	book, thesis, journal, or bookchapter
use_layout_analysis	--no-layout	True	Disable column/footnote detection
is_primary	--is-primary	False	Line-level granularity (vs paragraph-level)
use_pageindex	--no-pageindex	True	PageIndex hierarchy is enabled by default; pass --no-pageindex to disable it
pageindex_model	--pageindex-model	ollama/deepseek-v4-flash:cloud	LLM for PageIndex tree building
citation_style	(API only)	chicago-author-date	CSL citation style for output
corpus_root	--corpus-root	corpus	Output directory for ingested artifacts
schema_version	--schema-version	1.0.0	Output schema version tag
(CLI only)	--crawl-depth	2	Max BFS crawl depth for --all-url-article
(CLI only)	--crawl-max-pages	100	Max pages for --all-url-article
(CLI only)	--verbose, -v	off	Enable verbose/debug logging

Output

Each ingestion produces a corpus folder (e.g., corpus/Author_2024_Title/) and a companion library markdown file:

Corpus artifacts (corpus/Author_2024_Title/)

File	Description
csl.json	Citation metadata (CSL-JSON with ci_* extensions: content_hash, merkle_root, source_type, ingestion_timestamp)
document.json	Structured document tree — pages, paragraphs, and section_tree for URL articles and PageIndex-augmented PDFs
pageindex_tree.json	Persisted CiteIndex/PageIndex hierarchy with page ranges and summaries when PageIndex runs
merkle.json	SHA-256 Merkle tree for integrity verification
transcript.json	Timestamped transcript with speaker segments (media only)
media_metadata.json	Source media metadata (media only)
ingestion_output.json	Full ingestion result with all pipeline outputs

Library markdown (library/Author_2024_Title.md)

Human-readable markdown with YAML front-matter, inline citation, page/section/timestamp headers with CSL-level detail, full extracted text, and footnotes. When PageIndex is available, digital PDFs emit section headings into the markdown instead of only flat page labels. Written to library/ (sibling of corpus/).

Ingestion log (corpus/ingestion_log.jsonl)

Appended on every ingestion with input_ref, resource_type, csl_id, merkle_root, and ingestion_timestamp.

URL content hashes (corpus/_url_content_hashes.json)

Persisted URL → content-hash mapping used by --update-url-article for change detection.

Return Value

The ingest() function returns a dict:

{
    "schema_version": "1.0.0",
    "status": "ok",                    # "ok" or "blocked"
    "document_path": "corpus/Author_2024_Title",
    "standardized_csl_json": { ... },  # Full CSL-JSON with ci_ extensions
    "sub_pipeline_outputs": { ... },   # Raw pipeline results
    "ingestion_log_entry": { ... },     # Log entry with merkle_root
    "library_md_path": "library/Author_2024_Title.md",
}

# On failure:
{
    "status": "blocked",
    "source_id": "unknown",
    "stage": "detect_resource_type",
    "error_code": "unsupported_input",
    "error_message": "Unsupported input: ...",
    "next_action": "Provide PDF, URL, or media file",
}

Batch URL Ingestion Return

The ingest_all_urls() method (triggered by --all-url-article / --update-url-article) returns:

{
    "status": "ok",
    "root_url": "https://example.com/articles",
    "discovered": 25,      # total article URLs found
    "ingested": 20,        # newly ingested
    "updated": 2,           # re-ingested (content changed)
    "skipped": 3,           # unchanged (--update-url-article only)
    "failed": 0,            # errors
    "results": [            # per-URL status list
        {"url": "...", "status": "ok"},
        {"url": "...", "status": "unchanged"},
        ...
    ]
}

Supported Formats

Format	Extension / Protocol
Digital PDF	.pdf (with embedded text)
Scanned PDF	.pdf (image-based, OCR applied)
URL Article	http:// / https://
Media	.mp3, .wav, .m4a, .mp4, .mkv, .webm
Office	.docx, .doc, .rtf, .odt, .pptx, .ppt, .odp
DJVU	.djvu

Citation

If you use CiteIndex in your work, please cite it:

APA:

ajia. (2025). CiteIndex: Ingest sources with proper citation (Version 0.12.0). MIT. https://github.com/ajia/citeindex

BibTeX:

@software{citeindex2025,
  author  = {Yongjia, Yuan},
  title   = {CiteIndex: Ingest sources with proper citation},
  version = {0.12.1},
  year    = {2025},
  license = {MIT},
  url     = {https://github.com/ajia/citeindex},
}

License

MIT