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# Setup PaddleOCR Models Cache
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GitHub Action to download and cache PaddleOCR ONNX models for CI testing and development.
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## Overview
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This action manages the setup of PaddleOCR PP-OCRv5 ONNX models used by the `kreuzberg-paddle-ocr` crate for optical character recognition testing. It:
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- Downloads three model types (detection, classification, recognition) from Hugging Face
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- Caches models per OS and CPU architecture (Linux x86_64, Linux ARM64, macOS, Windows)
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- Provides environment variables for downstream use
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- Outputs cache hit status and available model information
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- Gracefully handles download failures (continues with available models)
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## Models
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The action downloads pre-converted ONNX format models from the `Kreuzberg/paddleocr-onnx-models` Hugging Face repository:
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| Model Type | File | Size | Purpose |
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| -------------------- | ------------------------------------- | ------- | ----------------------------------------- |
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| Detection (det) | `PP-OCRv5_server_det_infer.onnx` | ~84 MB | Text location detection (PP-OCRv5 server) |
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| Classification (cls) | `ch_ppocr_mobile_v2.0_cls_infer.onnx` | ~0.6 MB | Text orientation classification |
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| Recognition (rec) | `rec/english/model.onnx` | ~8 MB | Text character recognition (PP-OCRv5) |
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**Total cache size: ~93 MB per OS/architecture combination**
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## Usage
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### Basic Usage
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```yaml
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- uses: ./.github/actions/setup-paddle-ocr-models
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```
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### With Custom Cache Suffix
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```yaml
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- uses: ./.github/actions/setup-paddle-ocr-models
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with:
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cache-key-suffix: my-paddle-ocr-v5
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```
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### Disable Caching
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For cross-architecture builds where caching doesn't help:
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```yaml
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- uses: ./.github/actions/setup-paddle-ocr-models
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with:
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cache-enabled: false
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```
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### Download Specific Models Only
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```yaml
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- uses: ./.github/actions/setup-paddle-ocr-models
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with:
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models: "det,rec" # Skip classification model
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```
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## Inputs
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| Name | Description | Required | Default |
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| ------------------ | --------------------------------------------------------------- | -------- | -------------------- |
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| `cache-enabled` | Enable model caching (set false for cross-arch builds) | No | `true` |
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| `models` | Comma-separated list of models to setup (det,cls,rec or subset) | No | `det,cls,rec` |
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| `cache-key-suffix` | Suffix for cache key to differentiate model sets | No | `paddle-ocr-v5-onnx` |
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## Outputs
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| Name | Description |
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| ------------------ | ---------------------------------------------------- |
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| `cache-hit` | Whether models were restored from cache (true/false) |
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| `cache-dir` | Path to the PaddleOCR model cache directory |
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| `models-available` | Comma-separated list of available models after setup |
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## Outputs as Environment Variables
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The action automatically exports:
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- `PADDLE_OCR_MODEL_CACHE`: Absolute path to model cache directory
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## Cache Strategy
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Models are cached using GitHub Actions cache with the following key structure:
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```text
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paddle-ocr-v5-onnx-{OS}-{ARCHITECTURE}-v4
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```
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Cache restoration order (restore-keys):
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1. Exact match: `paddle-ocr-v5-onnx-{OS}-{ARCHITECTURE}-v4`
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2. OS-Architecture: `paddle-ocr-v5-onnx-{OS}-{ARCHITECTURE}-`
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3. OS only: `paddle-ocr-v5-onnx-{OS}-`
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4. Any: `paddle-ocr-v5-onnx-`
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## Example: CI Rust Workflow Integration
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```yaml
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jobs:
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paddle-ocr-tests:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: ./.github/actions/setup-paddle-ocr-models
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id: paddle-models
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- name: Run PaddleOCR tests
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run: cargo test --package kreuzberg-paddle-ocr
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env:
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PADDLE_OCR_MODEL_CACHE: ${{ steps.paddle-models.outputs.cache-dir }}
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- name: Report cache status
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if: always()
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run: |
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echo "Cache hit: ${{ steps.paddle-models.outputs.cache-hit }}"
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echo "Available models: ${{ steps.paddle-models.outputs.models-available }}"
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```
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## Error Handling
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The action downloads models sequentially and will fail if a required model download fails. After downloading:
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- The verify step reports which models are actually available in the output
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- Downstream tests can check `models-available` to know what's available
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- If all models fail, tests can fall back to alternative behavior
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## Download Sources
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Models are downloaded from:
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```text
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https://huggingface.co/Kreuzberg/paddleocr-onnx-models/resolve/main/
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```
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If this repository becomes unavailable, the action will fail gracefully. Alternative sources can be configured by modifying the `MODEL_URL` environment variables in the action.
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## Troubleshooting
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### Models not being cached
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1. Check that `cache-enabled` is not set to `false`
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2. Verify GitHub Actions cache is not full (max 10 GB per repository)
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3. Check runner OS and architecture match cache keys
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4. View cache in repository settings (Settings → Actions → Caches)
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### Download timeouts
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If downloads timeout:
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- Increase the 300-second timeout in the action steps
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- Check Hugging Face API availability
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- Try reducing the number of models (`models: "det,rec"`)
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### Verifying models are present
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Check that all expected models exist in the correct directory structure:
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```bash
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ls -lh ~/.cache/kreuzberg/paddle-ocr/
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```
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Expected output:
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```text
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drwxr-xr-x det/
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drwxr-xr-x cls/
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drwxr-xr-x rec/
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ls -lh ~/.cache/kreuzberg/paddle-ocr/det/
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-rw-r--r-- model.onnx (~84 MB)
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ls -lh ~/.cache/kreuzberg/paddle-ocr/cls/
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-rw-r--r-- model.onnx (~0.6 MB)
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ls -lh ~/.cache/kreuzberg/paddle-ocr/rec/english/
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-rw-r--r-- model.onnx (~8 MB)
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-rw-r--r-- dict.txt
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```
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The directory structure must match what `ModelManager` expects in `model_manager.rs`.
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## Performance Impact
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- **First run (no cache)**: ~30-60 seconds (download time depends on network)
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- **Cached run**: <1 second (cache restore)
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- **Cache size**: ~93 MB per OS/architecture
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- **Network bandwidth**: ~93 MB download on cache miss
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## Related Actions
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- `.github/actions/setup-tesseract-cache` - Similar caching for Tesseract models
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- `.github/actions/cache-hf-fastembed` - Hugging Face model caching for fastembed
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- `.github/actions/setup-onnx-runtime` - ONNX Runtime setup for inference
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## See Also
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- [PaddleOCR Documentation](https://github.com/PaddlePaddle/PaddleOCR)
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- [kreuzberg-paddle-ocr crate](../../../crates/kreuzberg-paddle-ocr)
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- [ModelManager source](../../../crates/kreuzberg/src/paddle_ocr/model_manager.rs)
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