feat(benchmarking): add query pipeline with logging and tracing

Why:
- Need query pipeline to ask questions against chunked documents
- Need comprehensive logging for debugging

Changes:
- Query service: embed question → vector search → LLM answer
- Query routes: POST /queries, GET /queries/{id}
- Query models: QueryRequest, QueryResponse, RetrievedChunk
- Added QueryError exception class
- Added STEP 1-6 logging for full traceability

src/benchmarking/routes.py

@@ -0,0 +1,68 @@
+"""Query API routes.
+
+Endpoints:
+  POST   /queries              Ask a question against a strategy
+  GET    /queries/{id}         Retrieve a past query
+"""
+
+from fastapi import APIRouter
+
+from src.core.exceptions import QueryError
+from src.core.models import StrategyName
+from src.benchmarking import query_service
+from src.benchmarking.models import (
+    QueryRequest,
+    QueryResponse,
+    QueryDetailResponse,
+    RetrievedChunk,
+)
+
+router = APIRouter()
+
+
+@router.post("/queries", response_model=QueryResponse, status_code=201)
+async def create_query(request: QueryRequest):
+    """Ask a question against a document using a specific chunking strategy.
+
+    Pipeline: embed question → vector search → generate answer → store result.
+    """
+    result = query_service.run_query(
+        document_id=request.document_id,
+        strategy_name=request.strategy,
+        question=request.question,
+        top_k=request.top_k,
+    )
+
+    return QueryResponse(
+        query_id=result["query_id"],
+        document_id=result["document_id"],
+        strategy=result["strategy"],
+        question=result["question"],
+        answer=result["answer"],
+        retrieved_chunks=[
+            RetrievedChunk(**chunk) for chunk in result["retrieved_chunks"]
+        ],
+        latency_breakdown=result["latency_breakdown"],
+        token_usage=result["token_usage"],
+        created_at=result["created_at"],
+    )
+
+
+@router.get("/queries/{query_id}", response_model=QueryDetailResponse)
+async def get_query(query_id: str):
+    """Retrieve a past query by ID."""
+    result = query_service.get_query(query_id)
+    if result is None:
+        raise QueryError(f"Query not found: {query_id}")
+
+    return QueryDetailResponse(
+        id=result["id"],
+        document_id=result["document_id"],
+        strategy_name=result["strategy_name"],
+        question=result["question"],
+        answer=result["answer"],
+        retrieved_chunks=result["retrieved_chunks"],
+        latency_breakdown=result["latency_breakdown"],
+        token_usage=result["token_usage"],
+        created_at=result["created_at"],
+    )