PDF Ingestion Pipeline
Production-grade document processing with security, scalability, and reliability
Document Processing Pipeline
Step-by-step breakdown of how documents are ingested and made searchable
Upload & Validation
File type verification, size limits, security scanning
Text Extraction
Extract text content using OCR when needed
Intelligent Chunking
Context-aware document segmentation
Embedding Generation
Convert chunks to vector embeddings
Vector Storage
Store embeddings in Qdrant with metadata
Indexing & Search
Build searchable indexes
Security: All documents processed in sandboxed containers with resource limits
Production Features
Security
- • Sandboxed processing containers
- • File validation & malware scanning
- • Resource limits & timeouts
- • User namespace isolation
Scalability
- • Batch processing for efficiency
- • Horizontal scaling support
- • Queue-based processing
- • Auto-scaling infrastructure
Reliability
- • Retry mechanisms with backoff
- • Error handling & recovery
- • Progress tracking & resumability
- • Health checks & monitoring
Cost Optimization
- • Embedding caching
- • Batch API calls
- • Efficient chunking
- • Pay-per-use infrastructure
Multi-Tenant Architecture
The system supports multiple users with complete data isolation:
- • Database: Row-level security (RLS) ensures users only see their data
- • Vector DB: Namespace isolation per user (
user_{user_id}) - • Storage: User-specific S3 prefixes
- • Cache: User-scoped cache keys
- • Quotas: Per-user rate limits and resource quotas