CiteIndex
CiteIndex, ingest sources with proper citation. PDF, URL, media, Office, DJVU.
Evidence-backed citation metadata, Merkle-verified integrity, CJK-first OCR. Optional verification traces accepted metadata corrections to source evidence.
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 paper.pdf --force-ocr # override PDF classification
citeindex -q paper.pdf # disable default debug logging
# Evidence-backed citation verification (Crossref exact DOI lookup)
citeindex paper.pdf --verify-citations --registry-contact-email you@example.org
# Ask a stronger provider-qualified model only to resolve remaining conflicts
citeindex paper.pdf --verify-citations --citation-verifier-model openai/gpt-5
Verification is opt-in. Crossref receives only an exact DOI, never document
text. A model correction is accepted only when it supplies a matching source
quote and stable locator; unavailable models leave the record unchanged for
review. Use --no-crossref to disable registry lookup or
--offline-verification to disable registry and verifier-model requests.
An independent harness audit is available only through an explicit Codex,
Claude Code, OpenCode, or Pi skill/command; running citeindex directly does
not auto-trigger one.
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)
Code Structure
citeindex/cli.pymaps CLI options intoIngestionConfig.citeindex/ingestion/master.pydetects input types, routes pipelines, verifies metadata, and persists results.citeindex/ingestion/pipelines/contains the digital PDF, scanned PDF, URL, media, GROBID, PageIndex, and metadata-extraction implementations.citeindex/ingestion/storage.pyandmarkdown_export.pywrite corpus artifacts and companion library Markdown..agents/,.claude/,.codex/,.opencode/, and.pi/expose the optional citation-evidence audit to supported agent harnesses.
Ingestion Pipelines
CiteIndex automatically detects the input type and routes to the correct pipeline:
PDF routing is based on usable existing text, not whether the file was born digital. Searchable scans with readable text layers use the digital pipeline, including invisible OCR text over full-page images. At least 90% of nonblank pages must have usable text; up to 10% may be image-only or sparse pages (such as illustrations or title pages). For example, 91 text pages and 9 image-only pages use the digital pipeline. Those image-only pages are kept in the document but are not OCR'd; text contained only in their images is not extracted. Completely blank pages do not count against the threshold.
Clearly garbled text still triggers OCR. These local quality checks cannot
detect every transcription error; use --force-ocr when the existing text is
wrong, or --force-digital to explicitly reuse it. Digital layout extraction
also disables automatic OCR in PyMuPDF4LLM.
Digital PDF
PDF → PyMuPDF4LLM layout/text (PyMuPDF fallback) + image extraction
→ page-paragraph document structure → GROBID references
→ PageIndex tree (default) → GROBID metadata / DSPy fallback
→ Merkle tree → section_tree + heading injection
→ store document.json and library Markdown
- PyMuPDF4LLM performs layout-aware extraction when enabled; raw PyMuPDF is the fallback
- GROBID extracts metadata and references when its service is available
- DSPy extracts citation metadata only when GROBID metadata is unavailable
- 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
→ pattern extraction with DSPy-priority metadata
→ document structure → Merkle tree → PageIndex tree (default)
→ 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/generateendpoint - PaddleOCR LayoutDetection (
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 mineruor--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
mineruis the default and recommended general-purpose backendglm-ocrrequires a local Ollama model plus PaddleOCR layout-detection dependencies--mineru-backendis 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-articleand--update-url-article
Media
Recognized media URL/local file → yt-dlp or local copy → 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) - Remote media routing recognizes YouTube, Vimeo, podcast, SoundCloud, and
youtu.behosts; other URLs use the article pipeline
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. Default DJVU conversion is limited to the first 10 pages.
Citation Enrichment Cascade
For digital PDF inputs, CiteIndex enriches metadata through a priority cascade:
- GROBID — deterministic metadata + references (primary)
- LLM extraction — DSPy-based citation parsing (fallback)
- PDF metadata — basic file metadata only (last resort)
Scanned PDFs do not use GROBID. Their structured OCR output is parsed with document-specific patterns, then DSPy values take priority when available.
With --verify-citations, the finalized draft follows this additional
evidence-first stage before CSL IDs, hashes, filenames, and Markdown are
written:
candidate CSL → DOI extraction → exact Crossref lookup
→ source quote + page/paragraph or URL snapshot evidence
→ deterministic reconciliation → optional conflict model
→ standardized CSL + verification report
Registry-only values are never applied automatically. They must also appear in
the original source evidence; otherwise CiteIndex records needs_review.
Configuration Reference
| Option | CLI Flag | Default | Description |
|---|---|---|---|
llm_model |
--llm |
ollama/glm-5.3-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 |
mineru_timeout |
--mineru-timeout |
3600 |
MinerU subprocess timeout in seconds, up to 3600 |
mineru_chunk_pages |
--mineru-chunk-pages |
auto |
Split large PDFs into adaptive MinerU chunks; use a page count to override or 0 to disable |
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/glm-5.3-flash:cloud |
LLM for PageIndex tree building |
force_pdf_kind |
--force-ocr, --force-digital |
auto | Override automatic PDF classification |
verify_citations |
--verify-citations |
False |
Enable evidence-backed metadata verification |
citation_verifier_model |
--citation-verifier-model |
none | Provider-qualified model used only for unresolved conflicts |
crossref_enabled |
--no-crossref |
True |
Disable exact DOI Crossref lookup |
offline_verification |
--offline-verification |
False |
Block Crossref and verifier-model requests (not normal ingestion fetching) |
registry_contact_email |
--registry-contact-email |
none | Optional polite Crossref contact email; not persisted |
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 |
on | Enable verbose/debug logging |
| (CLI only) | --quiet, -q |
off | Disable verbose/debug logging |
Output
Each ingestion produces a content-addressed corpus folder (for example, corpus/Author_2024_Title_a1b2c3d4e5f6/) and a companion library Markdown file.
Corpus artifacts (corpus/Author_2024_Title_<12-char-hash>/)
| File | Description |
|---|---|
csl.json |
Citation metadata (CSL-JSON with CiteIndex fields: 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 |
citation_verification.json |
Evidence, Crossref provenance/digest, accepted corrections, and needs_review items (when verification is enabled) |
source.html |
Fetched HTML snapshot used as URL evidence (URL articles only) |
images/ |
Extracted figures and illustrations when available |
Library markdown (library/Author_2024_Title_<12-char-hash>.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/).
Agent-harness final audit
Codex, OpenCode, Claude Code, and Pi can load the shared
citation-verification skill after ingestion. The audit reads the original
source and citation_verification.json, then returns quotation-backed repair
recommendations. It never edits persisted csl.json directly.
The CLI itself always performs the core verification when
--verify-citations is supplied. The additional agent audit runs only through
an explicit harness workflow (for example OpenCode /ingest-verified); a raw
citeindex subprocess cannot detect or launch an agent harness.
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 0.13.0). MIT. https://github.com/ajia/citeindex
BibTeX:
@software{citeindex2025,
author = {Yongjia, Yuan},
title = {CiteIndex: Ingest sources with proper citation},
version = {0.13.0},
year = {2025},
license = {MIT},
url = {https://github.com/ajia/citeindex},
}
License
MIT
Release files for citeindex 0.13.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| citeindex-0.13.2.tar.gz | 6.3 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| citeindex-0.13.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 6.5 MB
Release files / citeindex-0.13.2.tar.gz
| Download URL | citeindex-0.13.2.tar.gz |
|---|---|
| Size | 6.3 MB |
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