Gemini OCR CLI

A command-line tool for OCR processing using Google Gemini's vision capabilities. Process PDFs and images to extract text, tables, equations, and figures.

Choosing an OCR tool

This is one of five OCR CLI tools with a shared design: clean Markdown output, batch processing, and figure extraction. Pick based on your constraints:

Tool	Engine	Runs	Cost	Best for
deepseek-ocr-cli	DeepSeek vision	Local (Ollama / vLLM)	Free	General-purpose local OCR with multi-backend flexibility
gemini-ocr-cli (this repo)	Google Gemini	Cloud API	Free tier / Pay-per-use	Fast cloud OCR with concurrent processing
marker-ocr-cli	Marker (Surya + Texify)	Local	Free	Academic papers with equations, tables, complex layouts
mistral-ocr-cli	Mistral OCR API	Cloud API	~$1/1k pages	Structured extraction (tables, headers, footers)
nougat-ocr-cli	Meta Nougat	Local (GPU)	Free	Academic papers, GPU-accelerated batch processing

Installation

Requires Python 3.11+ and a Google Gemini API key.

pip install gemini-ocr-cli

Or from source:

git clone https://github.com/r-uben/gemini-ocr-cli.git
cd gemini-ocr-cli
uv sync

Quick start

# Set your API key
export GEMINI_API_KEY="your_key_here"

# Process a single file
gemini-ocr document.pdf

# Process a directory
gemini-ocr ./documents -o ./results

# Preview what would be processed (no API calls)
gemini-ocr ./documents --dry-run

# Process 4 files concurrently
gemini-ocr ./documents -w 4

Options

Usage: gemini-ocr [OPTIONS] INPUT_PATH

Options:
  -o, --output-dir PATH           Output directory (default: <input_parent>/ocr/)
  --api-key TEXT                  Gemini API key (or set GEMINI_API_KEY env var)
  --model TEXT                    Model to use (default: gemini-3-flash-preview)
  --task [convert|extract|table|describe_figure]
                                  OCR task type (default: convert)
  --prompt TEXT                   Custom prompt for OCR processing

  --per-page                      Force page-by-page OCR (one call/page).
  --whole-pdf                     Force whole-PDF OCR (one call/document), NO
                                  truncation fallback.
                                  (default: auto = whole-PDF with auto-fallback)
  --include-images/--no-images    Extract embedded figures (default: True)

  -w, --workers N                 Concurrent workers for batch processing (default: 1)
  --reprocess                     Reprocess already-processed files
  --dry-run                       List files without calling the API
  -q, --quiet                     Print only output .md paths (for scripting)
  -v, --verbose                   Enable verbose/debug output
  --info                          Show configuration and system info
  --env-file PATH                 Path to .env file
  --version                       Show version
  --help                          Show this message

Output structure

gemini-ocr follows the shared OCR-CLI output contract. The default output root is an ocr/ folder next to the input (-o overrides it). Each source document gets one aggregated folder that mirrors the input subtree, keyed by the input-relative path (not the basename), so two intro.pdf files in different directories never collide:

<input_parent>/ocr/
├── a/
│   └── intro/
│       ├── intro.md            # all pages, separated by "## Page N" headers
│       ├── figures/            # figure_<N>_page<P>.png (normalised to PNG)
│       │   └── figure_1_page2.png
│       └── metadata.json       # per-document provenance sidecar
├── b/
│   └── intro/                  # same basename, different subtree — no collision
│       └── intro.md
└── metadata.json               # rolled-up index keyed by input-relative path

The markdown body is clean (no YAML frontmatter); all provenance lives in the JSON sidecars. Each metadata.json entry records {status, checksum, model, backend, processing_time, timestamp, output_path, pages, mode, fell_back_from_whole_pdf}. Failures are recorded with status: "failed", and the process exits non-zero if any file or page fails (uniform across single-file and batch).

PDF processing modes

PDFs can be processed in three modes; the output structure is identical across all three (one <stem>.md with ## Page N headers, dual-level metadata, figures). The mode actually used is recorded per document in metadata (mode), together with whether an auto run fell back (fell_back_from_whole_pdf):

• auto (default). Uploads the whole PDF once and OCRs it in a single call (the model is asked to begin each page with a ## Page N header, which is split back into pages). If that response looks truncated, the document is automatically re-processed page-by-page and that result is used instead, with a one-line note printed and the fallback recorded in metadata (mode: "per_page", fell_back_from_whole_pdf: true). Truncation is detected from real signals, with no hardcoded page-count threshold: (a) a length-limited finish reason (MAX_TOKENS / LENGTH); (b) fewer ## Page N markers recovered than the PDF's actual page count (PyMuPDF, i.e. a dropped tail); (c) a missing end-of-document completeness sentinel (the model is asked to emit a terminal <!-- OCR-END --> line; its absence means the body was cut mid-page even on a clean STOP, and the sentinel is stripped from the saved markdown); or (d) a multi-page PDF whose response carries zero ## Page N markers (markerless collapse to a single blob). This is the cost/quality-preferred default for academic PDFs: one call per document, full document context, but no silently truncated tails on long papers.
• --per-page. Forces page-by-page OCR: each page is rendered to an image and OCR'd in its own call (N calls per document). Honest per-page failure tracking (one page can fail without sinking the document) at higher cost.
• --whole-pdf. Forces a single whole-PDF call with no truncation fallback. Cheapest, but a long document may be silently truncated; use only when you explicitly accept that risk.

gemini-ocr paper.pdf              # auto: whole-PDF, auto-fallback on truncation
gemini-ocr paper.pdf --per-page   # force page-by-page (N calls, per-page failures)
gemini-ocr paper.pdf --whole-pdf  # force single call, no fallback (truncation risk)

API key resolution

Priority order:

1. --api-key CLI argument
2. GEMINI_API_KEY environment variable
3. GOOGLE_API_KEY environment variable (fallback)
4. .env file in current directory

Configuration

All CLI options can also be set via environment variables or a .env file:

CLI flag	Environment variable	Default
--api-key	GEMINI_API_KEY	(required)
--model	GEMINI_MODEL	gemini-3-flash-preview
--per-page / --whole-pdf	GEMINI_PDF_MODE (auto|per_page|whole_pdf)	auto
--include-images	GEMINI_INCLUDE_IMAGES	true
--workers	GEMINI_MAX_WORKERS	1
--verbose	GEMINI_VERBOSE	false
	GEMINI_MAX_FILE_SIZE_MB	50
	GEMINI_MAX_RETRIES	3
	GEMINI_RETRY_BASE_DELAY	1.0

CLI flags override environment variables when explicitly passed.

Development

# Install dev dependencies
uv sync --extra dev

# Run tests
uv run pytest

# Lint
uv run ruff check .

# Format
uv run ruff format .

# Type check
uv run mypy gemini_ocr/ --ignore-missing-imports

Limitations

• Maximum file size: 50 MB (configurable via GEMINI_MAX_FILE_SIZE_MB)
• Supported formats: PDF, JPG, JPEG, PNG, WEBP, GIF, BMP, TIFF

License

MIT License - see LICENSE for details.