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

pip install citeindex
# Add only the engines you use, for example:
pip install 'citeindex[ocr-mineru,layout]'

The default install handles digital PDFs and ordinary HTML URLs. Scanned PDFs need ocr-mineru (MinerU's pipeline backend) or ocr-paddle with --ocr-engine glm-ocr. Media transcription with WhisperX needs media; the separate Wenbi environment needs only media-wenbi here. JavaScript-rendered pages need web-browser plus playwright install chromium, while --all-url-article needs crawl. The legacy OCR helpers need ocr-legacy. Enhanced PDF layout extraction uses layout; otherwise it falls back to the built-in heuristic. Install several extras together as needed.

CLI

# Ingest a PDF
citeindex paper.pdf

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

# Opt in to Wenbi raw ASR with an explicit local provider
citeindex lecture.mp4 --media-asr-backend wenbi --wenbi-asr-provider funasr

# Or keep Wenbi dependencies isolated in Wenbi's own environment
citeindex lecture.mp4 --media-asr-backend wenbi --wenbi-asr-provider funasr \
  --wenbi-python ../wenbi/.venv/bin/python

# 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

# Explicit alternative engine for digital PDFs; requires a running GROBID service
citeindex paper.pdf --citation-engine grobid

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.

Benchmarking

The pilot benchmark measures extraction and evidence verification only; it does not evaluate document question answering. Keep reviewed source manifests, predictions, reports, and copied source files local because they may contain private or licensed material.

# First create candidate rows; this does not invent gold labels.
python benchmarks/citations/prepare_manifest.py \
  /home/ajiap/Downloads/Orthodox-China \
  benchmarks/citations/manifest.jsonl --limit 40

# Run all manifest rows serially; every attempted source becomes a prediction row.
python benchmarks/citations/ingest.py benchmarks/citations/manifest.jsonl \
  benchmarks/citations/predictions/dspy.jsonl

# Score host metadata against the human-reviewed labels.
python benchmarks/citations/run.py benchmarks/citations/manifest.jsonl \
  benchmarks/citations/predictions/dspy.jsonl

The 40-source pilot composition, annotation contract, modality-specific controls, and reporting gates are documented in docs/plans/2026-09-14-multimodal-citation-benchmark.md. Validate independent reviewers before scoring with python benchmarks/citations/validate_manifest.py manifest.jsonl; create a reproducible split with python benchmarks/citations/split.py manifest.jsonl split-manifest.jsonl; compare saved reports with python benchmarks/citations/compare.py baseline.json candidate.json. After a reviewed run, this section will be updated with the commit, corpus denominators, per-modality results, evidence-validity rate, failure rate, and cost/latency summary; it will not publish source-private rows.

Current result: no valid accuracy measurement yet. Human-reviewed labels, adjudication, and live baseline/candidate runs remain pending. The runner keeps append-only attempts, locks each output file, defaults to 5,400 seconds per source, and supports --retry-failed. Missing token/cost telemetry is reported as unknown, never zero. Do not interpret JSONL line counts as unique sources.

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.py maps CLI options into IngestionConfig.
• citeindex/ingestion/master.py detects 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.py and markdown_export.py write 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 → DSPy citation extraction
    → PageIndex tree (default) → optional explicit GROBID engine
    → Merkle tree → section_tree + heading injection
    → store document.json and library Markdown

• PyMuPDF4LLM performs layout-aware extraction when enabled; raw PyMuPDF is the fallback
• DSPy is the default citation metadata engine for digital PDFs
• GROBID is an explicitly selected alternative requiring a separate service
• 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/generate endpoint
• 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 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 / in-page citation guidance (candidates) → web-specific DSPy + source evidence
    → 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
• Web-specific DSPy uses original HTML text/metadata, preserves bibliographic subtype and date precision, and requires field quotations.
• Regex/provider candidates remain unverified without evidence; access and revision dates are not publication dates.
• Supports batch crawling with --all-url-article and --update-url-article

Media

Recognized media URL/local file → yt-dlp or local copy → ffmpeg (audio) → WhisperX (transcription)
        → pyannote (diarization, optional) → media-specific DSPy + source evidence → 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)
• Preserves speaker/interviewee, interviewer, host, director and producer roles; uploader is not automatically author, nor platform publisher.
• Recording duration (dimensions) is separate from quotation timestamps. Failed transcription leaves an empty transcript, not invented quotation text.
• Each web/media extraction uses one bounded DSPy call (12,000 source-text characters); unsupported metadata stays missing or unverified. No live accuracy claim follows from this contract.
• Supports audio (.mp3, .wav, .m4a) and video (.mp4, .mkv, .webm)
• Remote media routing recognizes YouTube, Vimeo, podcast, SoundCloud, and youtu.be hosts; 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 uses DSPy citation extraction by default. A separately installed GROBID service is available only when explicitly selected with --citation-engine grobid; it is never an automatic fallback.

Extraction targets the ingested source's own citation metadata—not works cited inside it. DSPy uses original source blocks and validates quote spans; this does not by itself prove correct work/edition attribution. PDF metadata remains a last-resort, unverified identity hint.

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

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>/)

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

Citation

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

APA:

ajia. (2025). CiteIndex: Ingest sources with proper citation (Version 0.13.3). MIT. https://github.com/ajia/citeindex

BibTeX:

@software{citeindex2025,
  author  = {Yongjia, Yuan},
  title   = {CiteIndex: Ingest sources with proper citation},
  version = {0.13.3},
  year    = {2025},
  license = {MIT},
  url     = {https://github.com/ajia/citeindex},
}

License

MIT