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@@ -99,7 +105,10 @@ After deployment, choose the processing method that fits your use case:
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For batch processing, automation, or evaluation workflows:
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```bash
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# Install CLI
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# Install CLI (with UV - recommended)
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cd idp_cli && uv sync
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# Or with pip
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cd idp_cli && pip install -e .
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# Process documents
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For detailed deployment and testing instructions, see the [Deployment Guide](./docs/deployment.md).
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## Dependency Management with UV
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This project uses [UV](https://github.com/astral-sh/uv) for fast, reliable Python dependency management. UV provides deterministic builds, improved caching, and significantly faster installation times compared to traditional pip.
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### Quick Start with UV
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```bash
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# Install UV (if not already installed)
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curl -LsSf https://astral.sh/uv/install.sh | sh
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# Install all dependencies
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uv sync
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# Activate the virtual environment
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source .venv/bin/activate # On macOS/Linux
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# or
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.venv\Scripts\activate # On Windows
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```
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### Working with Dependencies
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The project uses a centralized dependency management system:
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-**`pyproject.toml`** - Root project configuration with 20+ dependency groups for different Lambda functions
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-**`uv.lock`** - Lockfile with 234+ resolved packages for reproducible builds
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-**Dependency Groups** - Organized by Lambda function (e.g., `lambda-ocr`, `lambda-extraction`, `lambda-classification`)
SAM automatically uses UV to build Lambda functions via Makefiles in each function directory. See [Lambda Dependency Groups](./docs/lambda-dependency-groups.md) for the complete dependency mapping.
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### Development Workflows
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```bash
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# For local development
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uv sync # Install all dependencies
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# For notebook development
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uv sync --group notebooks # Install with Jupyter dependencies
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# For CLI development
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cd idp_cli && uv sync # Install CLI dependencies
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# For testing
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uv sync --group dev # Install with test dependencies
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pytest
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```
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### Publishing and Deployment
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The publish script automatically validates UV is installed:
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