PDF OCR using Gemini LLM
Extract text from PDFs using Google Gemini OCR. Use when extracting text from PDFs, performing OCR on scanned documents, or processing image-based PDFs.
Best use case
PDF OCR using Gemini LLM is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Extract text from PDFs using Google Gemini OCR. Use when extracting text from PDFs, performing OCR on scanned documents, or processing image-based PDFs.
Teams using PDF OCR using Gemini LLM should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/geminipdfocr/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How PDF OCR using Gemini LLM Compares
| Feature / Agent | PDF OCR using Gemini LLM | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Extract text from PDFs using Google Gemini OCR. Use when extracting text from PDFs, performing OCR on scanned documents, or processing image-based PDFs.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
## Purpose Use geminipdfocr to extract text from PDF documents via OCR (Google Gemini). ## Data and privacy **Full page images/files are sent to Google's API.** PDFs are split into single-page files and each page is uploaded to Google Gemini for OCR. There are no hidden exfiltration endpoints or other data collection. Do not use with highly sensitive documents unless you accept that content is sent to Google. ## Setup (venv installation) Before first use, create and activate the virtual environment: ```bash cd geminipdfocr && python -m venv venv && source venv/bin/activate && pip install -r requirements.txt ``` Set `GOOGLE_API_KEY` in your environment before running (e.g. `export GOOGLE_API_KEY=your-key`). ## How to use When requested to extract text or perform OCR on a PDF: 1. Run: `cd geminipdfocr && source venv/bin/activate && python -m geminipdfocr <path-to-pdf> [--json] [--output <file>]` 2. Use `--json` for structured data. 3. Use `--max-pages N` for testing or very long documents. 4. Use `--quiet` to suppress progress logs. ## Requirements - A valid PDF file path. - `GOOGLE_API_KEY` set in the process environment (e.g. `export GOOGLE_API_KEY=your-key`). ## CLI options | Option | Description | |--------|-------------| | `pdf_path` | One or more PDF file paths (positional) | | `--max-pages N` | Limit pages per PDF | | `--json` | Output structured JSON instead of plain text | | `--output FILE` | Write result to file (default: stdout) | | `--quiet` | Suppress INFO/DEBUG logs |
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