feat(core): add core layer with config, clients, exceptions, models, and app factory

src/core/exceptions.py

@@ -0,0 +1,52 @@
+"""Custom exception classes and FastAPI exception handlers."""
+
+from fastapi import Request
+from fastapi.responses import JSONResponse
+
+
+class ChunkingError(Exception):
+    """Base exception for chunking-related errors."""
+
+
+class StrategyNotFoundError(ChunkingError):
+    """Raised when an unknown strategy name is requested."""
+
+
+class DocumentProcessingError(ChunkingError):
+    """Raised when a document cannot be parsed or processed."""
+
+
+class EnrichmentError(ChunkingError):
+    """Raised when the contextual enrichment LLM call fails."""
+
+
+class EmbeddingError(ChunkingError):
+    """Raised when the OpenAI embedding API call fails."""
+
+
+class QdrantError(ChunkingError):
+    """Raised when a Qdrant operation fails."""
+
+
+class BenchmarkError(Exception):
+    """Base exception for benchmarking-related errors."""
+
+
+class DryRunError(BenchmarkError):
+    """Raised when a dry-run estimation fails."""
+
+
+async def chunking_exception_handler(request: Request, exc: ChunkingError) -> JSONResponse:
+    """Handle all chunking-related errors."""
+    return JSONResponse(
+        status_code=400,
+        content={"detail": str(exc), "type": type(exc).__name__},
+    )
+
+
+async def benchmark_exception_handler(request: Request, exc: BenchmarkError) -> JSONResponse:
+    """Handle all benchmarking-related errors."""
+    return JSONResponse(
+        status_code=400,
+        content={"detail": str(exc), "type": type(exc).__name__},
+    )