sds-converter 0.1.0

CLI tool for converting SDS documents (PDF/Word) ↔ MHLW standard JSON. Powered by sds-converter-core.
sds-converter-0.1.0 is not a library.

sds-converter

CLI tool for bidirectional conversion between Safety Data Sheet (SDS) documents (Word/PDF) and the Japanese Ministry of Health, Labour and Welfare (MHLW) standard JSON format.

Supports Japanese, English, Simplified Chinese, and Traditional Chinese.

Embedding in your Rust project? Use sds-converter-core directly.

Installation

cargo install sds-converter

Commands

to-json — Convert PDF/Word → MHLW standard JSON

# Single file (Anthropic Claude, default)
export ANTHROPIC_API_KEY=sk-ant-...
sds-converter to-json --input input.pdf --output output.json

# Specify source language
sds-converter to-json --input sds_en.pdf --output output.json --lang en

# Batch mode — process a whole directory
sds-converter to-json --input-dir ./pdfs/ --output-dir ./json/ --lang ja

# OpenAI GPT (defaults to gpt-4o)
sds-converter to-json --input input.pdf --output output.json \
  --provider openai --api-key $OPENAI_API_KEY

# Google Gemini (defaults to gemini-2.0-flash)
sds-converter to-json --input input.pdf --output output.json \
  --provider gemini --api-key $GEMINI_API_KEY

# Local LLM via Ollama (any OpenAI-compatible endpoint)
sds-converter to-json --input input.pdf --output output.json \
  --provider openai --base-url http://localhost:11434/v1 \
  --model llama3.2 --api-key dummy

# From pre-extracted text (skip PDF parsing)
sds-converter to-json --input extracted.txt --output output.json --lang ja
Flag Default Description
--input — Input PDF, DOCX, or TXT file
--input-dir — Input directory (batch — processes all .pdf/.docx)
--output — Output JSON file
--output-dir — Output directory (batch — created if absent)
--provider anthropic LLM provider: anthropic, openai, gemini
--api-key env var API key (fallback: ANTHROPIC_API_KEY / OPENAI_API_KEY / GEMINI_API_KEY)
--model per-provider Model name (defaults: claude-sonnet-4-6 / gpt-4o / gemini-2.0-flash)
--base-url — Custom OpenAI-compatible endpoint (Ollama, vLLM, etc.)
--lang auto-detect Source document language: ja, en, zh-cn, zh-tw

to-docx — Convert MHLW standard JSON → Word document

# Single file
sds-converter to-docx --input output.json --output result.docx --lang ja

# Batch mode
sds-converter to-docx --input-dir ./json/ --output-dir ./docx/ --lang en
Flag Default Description
--input — Input JSON file
--input-dir — Input directory (batch — processes all .json)
--output — Output DOCX file
--output-dir — Output directory (batch)
--lang ja Output language: ja, en, zh-cn, zh-tw

extract-text — Extract raw text from PDF/DOCX

Extracts the text that the LLM would receive, without making any API call. Useful for inspecting extraction quality or running the LLM step separately.

# Save to file
sds-converter extract-text --input input.pdf --output extracted.txt

# Print to stdout
sds-converter extract-text --input input.pdf

# Then feed back into to-json
sds-converter to-json --input extracted.txt --output output.json --lang ja

validate — Check a JSON file for structural issues

# Human-readable output (exits 0 = OK, 1 = warnings found)
sds-converter validate --input output.json

# JSON array output for CI/scripting
sds-converter validate --input output.json --json

Checks that key sections (Identification, HazardIdentification, ToxicologicalInformation, etc.) are populated. Exits with code 1 if any issues are found.

Language Support

Language --lang Source documents Output DOCX headings
Japanese ja JIS Z 7253 compliant SDS JIS Z 7253
English en GHS/OSHA HazCom format GHS Rev.10 / ISO 11014
Simplified Chinese zh-cn GB/T 16483 format GB/T 16483-2012
Traditional Chinese zh-tw CNS 15030 format CNS 15030

Requirements

  • Rust 1.75+
  • An LLM API key (for to-json only)
    • Anthropic: set ANTHROPIC_API_KEY or use --api-key
    • OpenAI: set OPENAI_API_KEY or use --api-key
    • Google Gemini: set GEMINI_API_KEY or use --api-key
    • Local LLM (Ollama etc.): use --provider openai --base-url <url> --api-key dummy
  • Input files must be text-based PDF or DOCX
    • Encrypted PDFs are not supported
    • Scanned/image-only PDFs are not supported (no text to extract)

License

Licensed under either of:

  • Apache License, Version 2.0
  • MIT License

at your option.