The Refinery (Semantic-Sift)
Semantic-Sift is the flagship intelligence engine of the Context Design ecosystem. It serves as a specialized high-density refinery that transforms noisy, unreasoning-ready data into high-fidelity context.
The Engine: Multi-Stage Distillation
Sift employs a multi-layered kernel designed for technical precision:
- The Heuristic Sieve: High-speed regex-based incineration of timestamps, UUIDs, progress bars, and repetitive boilerplate.
- The Semantic Engine: A neural distillation layer utilizing LLMLingua-2 to prune linguistic filler while preserving 95% of core semantic meaning.
- The Ranking Engine: A local re-ranking layer that scores and surfaces only the highest-value document chunks for a specific query.
Dual Engine Routing
Semantic-Sift features a Hybrid Engine strategy to balance performance and scale:
- Rust Sift-Core: An ultra-low-latency sidecar for everyday tasks and code files (under 30k characters).
- Python PyTorch: A heavy-duty engine with Flash Attention for massive document batches and multi-modal ingestion.
Universal Ingestion
Supports high-fidelity conversion of binary formats to structured Markdown:
- Documents: PDF, DOCX, PPTX
- Data: XLSX, CSV
- Web: HTML, ZIP
Performance Benchmarks
| Scenario | Input Profile | Output | Reduction |
|---|---|---|---|
| AWS Framework (PDF) | 1.9M Chars / 14MB | High-Density MD | Surgical |
| Natural Language | Conversational Prose | Core Intent | ~50.0% |
| GitHub Actions (CI) | Verbose Build Logs | Clean Stack Trace | 47.5% |
| System Logs (HDFS) | 100k Lines of Logs | Error Signatures | 32.5% |
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