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cerebro-reranker/ β”œβ”€β”€ flake.nix # Entry point β”œβ”€β”€ flake.lock β”œβ”€β”€ modules/ β”‚ β”œβ”€β”€ reranker-service.nix # Core service β”‚ β”œβ”€β”€ ipfs-cluster.nix # Distributed model serving β”‚ β”œβ”€β”€ training-pipeline.nix # GCP training automation β”‚ β”œβ”€β”€ cache-layer.nix # Redis + IPFS cache β”‚ └── monitoring.nix # Observability stack β”œβ”€β”€ src/ β”‚ β”œβ”€β”€ reranker/ β”‚ β”‚ β”œβ”€β”€ server.py # FastAPI server β”‚ β”‚ β”œβ”€β”€ hybrid_engine.py # Hybrid reranking logic β”‚ β”‚ β”œβ”€β”€ models.py # Model management β”‚ β”‚ └── cache.py # IPFS-backed caching β”‚ β”œβ”€β”€ training/ β”‚ β”‚ β”œβ”€β”€ train.py # Fine-tuning pipeline β”‚ β”‚ └── export.py # ONNX export + quantization β”‚ └── lib/ β”‚ β”œβ”€β”€ scorer.rs # Rust FFI for fast scoring β”‚ └── ipfs_client.rs # IPFS pinning client β”œβ”€β”€ configs/ β”‚ β”œβ”€β”€ models.toml # Model registry β”‚ └── gcp-training.yaml # Vertex AI config └── scripts/ β”œβ”€β”€ setup-gcp.sh └── deploy.sh