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Claude
a219affd91
Introduce a pluggable search architecture with two backends: - VectorSearchProvider: Sentence-transformer embeddings (all-MiniLM-L6-v2) for true semantic search. Best quality, requires model download. - FuseSearchProvider: Fuse.js fuzzy text matching. Zero model download, instant startup, lightweight fallback. Auto-detection: if @xenova/transformers is available, uses vector; otherwise falls back to fuse. Override via SEARCH_BACKEND=vector|fuse env var. Architecture: SearchProvider (interface) ← tools.ts programs against this ├── VectorSearchProvider ← embeddings + cosine similarity └── FuseSearchProvider ← fuse.js weighted fuzzy match createSearchProvider() ← factory with auto-detect Also refactored knowledge-base.ts to be provider-agnostic (just loads documents) and removed the old monolithic vector-store.ts. https://claude.ai/code/session_01TBPsvvMBue9Ft7j3CfD4S2
Autopilot Monitor
Advanced monitoring and troubleshooting solution for Windows Autopilot deployments.
Overview
Autopilot Monitor provides real-time tracking, intelligent diagnostics, and automated troubleshooting for Windows Autopilot enrollment processes. It consists of:
- Bootstrap Script — PowerShell script deployed via Intune that starts monitoring early in the enrollment process
- Monitoring Agent — Lightweight .NET application that collects telemetry and evidence during enrollment
- Backend API — Azure Functions-based ingestion and processing pipeline
- Web Dashboard — Next.js application for real-time monitoring and fleet analytics
Architecture
For detailed information about the system architecture, components, and data flow, see Architecture Documentation.
Documentation
Full documentation is available at autopilotmonitor.com/docs
License
MIT License — see LICENSE for details