feat(ingestion): add DOCX/CSV/XLSX parsing and fixed-size chunking (ADR-0018)

Adds src/application/ingestion/ -- Persian normalization, DOCX body
walk with structural data/layout table classification, CSV/XLSX row
rendering, and fixed-size token chunking (cl100k_base, 400/60/512) --
as pure functions per ADR-0015, tested against real production
documents (asia_data_sample, kept out of the repo). ADR-0018 records
where this diverges from ADR-0004 (fixed-size default, no invented
headings/tree, structural table classification, header-provable
labeling only). Plan 001's scope line is corrected from CSV-only to
DOCX/XLSX/CSV, and CLAUDE.md's stale project-status paragraph is
updated to match current implementation state.

src/bootstrap/lifespan.py

@@ -2,8 +2,10 @@ from collections.abc import AsyncIterator, Callable
 from contextlib import AbstractAsyncContextManager, asynccontextmanager
 
 import structlog
+from anyio import to_thread
 from fastapi import FastAPI
 
+from src.application.ingestion import get_encoder
 from src.bootstrap.dependencies import AppResources
 from src.config import Settings
 from src.infrastructure.minio.client import create_client as create_minio_client
@@ -22,6 +24,15 @@ def create_lifespan(
         resolved_settings = settings or Settings()
         configure_logging(resolved_settings.logging)
 
+        # tiktoken fetches its vocabulary over the network on first use, so warm
+        # it here: a missing vocabulary should fail the process at boot, not the
+        # first upload. Blocking, hence the thread.
+        await to_thread.run_sync(get_encoder, resolved_settings.chunking.encoding_name)
+        logger.info(
+            "lifespan.tokenizer.loaded",
+            encoding=resolved_settings.chunking.encoding_name,
+        )
+
         db_engine = create_engine(resolved_settings.postgres)
         db_sessionmaker = create_sessionmaker(db_engine)
         logger.info("lifespan.postgres.engine.created")