Build a Document Processing Pipeline
From raw PDFs to structured data: setup, implementation, testing, and deployment.
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Step 1: Environment Setup
DeepSeek-OCR requires a GPU with at least 8 GB . We use vLLM for efficient production serving.
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Step 2: PDF to Images
DeepSeek-OCR processes images, not PDFs. Convert pages first.
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Step 3: Basic OCR
Run DeepSeek-OCR via vLLM with temperature 0 for most output.
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Non-Determinism: Even with temperature=0, outputs may vary between runs. This is a known risk. Always add validation (Step 7).
Step 4: Table Extraction
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Step 5: Full ETL Pipeline
Combine extraction, OCR, table parsing, and loading into a single pipeline class.
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Step 6: Hybrid Routing
Route documents to different backends based on complexity and compliance needs.
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Step 7: Validation
Validate OCR output for , empty results, and repetition.
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Step 8: Deployment with vLLM
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Production Checklist:
- Health checks and monitoring on vLLM server
- Validation layer after every OCR call
- Hybrid routing for cost optimization
- Audit logging for compliance
- Retry with different resolution on failure