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PDF extraction pipeline for scientific papers

Project description

acatome-extract

PDF extraction and enrichment pipeline for scientific papers. Converts PDFs into structured, searchable bundles with block-level summaries and embeddings.

Features

  • Marker PDF extraction — structured block extraction with headings, tables, figures
  • Fitz fallback — recursive character chunking when Marker is unavailable
  • LLM enrichment — block and paper summaries via Ollama or litellm
  • Embeddings — sentence-transformer embeddings for semantic search
  • File watcheracatome-extract watch monitors an inbox folder
  • Bundle format.acatome companion files for sharing pre-built extractions
  • CLIacatome-extract command for extract, enrich, and watch workflows

Installation

uv pip install -e .

With GPU acceleration:

uv pip install -e ".[gpu]"

Usage

from acatome_extract.pipeline import extract

bundle = extract("/path/to/paper.pdf")

CLI

# Extract (RAKE summaries included automatically, no LLM needed)
acatome-extract extract paper.pdf
acatome-extract extract --type datasheet TI_LM317.pdf   # non-article types

# Enrich — embeddings only by default; add --summarize for LLM summaries
acatome-extract enrich /path/to/bundle
acatome-extract enrich --summarize /path/to/bundle       # enable LLM summaries
acatome-extract enrich --summarize --skip-existing dir/   # incremental LLM pass

# Watch — extract + embed + ingest; LLM summaries off by default
acatome-extract watch ~/papers/inbox
acatome-extract watch ~/papers/inbox --summarize          # enable LLM summaries

# Migrate old bundles to new summaries dict format + add RAKE
acatome-extract migrate ~/.acatome/papers
acatome-extract migrate ~/.acatome/papers --dry-run       # preview changes

# Supplements
acatome-extract attach parent-slug supplement.pdf --name s1

Summaries

Extraction always generates RAKE (extractive keyword) summaries — instant, no LLM required. LLM-based summaries are opt-in via --summarize and require an Ollama or litellm-compatible model.

RAKE summaries are used as the default for search and display. To add LLM summaries later:

acatome-extract enrich --summarize --skip-existing ~/.acatome/papers

Sidecar metadata

Place a <stem>.meta.json alongside any PDF to override metadata:

{"type": "datasheet", "title": "LM317 Regulator", "author": "Texas Instruments", "year": 2022}

Supported fields: type, title, author (string or list), year, doi, abstract, journal.

Dependencies

  • acatome-meta — metadata lookup and verification
  • marker-pdf — structured PDF extraction
  • litellm / Ollama — LLM-based enrichment

Testing

uv run python -m pytest tests/ -v

License

GPL-3.0-or-later — see LICENSE.

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