feat: duration_ms-logging, bulk-semaphore und erweitertes README

- Pipeline-Stages (download/extract/embed/qdrant) loggen jetzt duration_ms
- bulk-import dispatcht mit Semaphore(4) statt unbounded → Backpressure
- README dokumentiert Webhook-Payload-Schema mit curl-Beispiel
- README enthaelt Recovery-Runbook (dim-mismatch, crash-recovery, single-file reindex)

app/ingest/pipeline.py

@@ -1,4 +1,5 @@
 import logging
+import time
 from datetime import datetime, timezone
 from functools import lru_cache
 from pathlib import PurePosixPath
@@ -49,6 +50,7 @@ async def process_file(file_path: str, event_type: EventType) -> None:
         )
         return
 
+    t0 = time.perf_counter()
     try:
         data = await download_file(
             settings.nextcloud_webdav_url,
@@ -59,7 +61,13 @@ async def process_file(file_path: str, event_type: EventType) -> None:
     except Exception as exc:
         logger.exception("download failed", extra={"event": "download_failed", "file": file_path, "error": str(exc)})
         return
+    download_ms = int((time.perf_counter() - t0) * 1000)
+    logger.info(
+        "download ok",
+        extra={"event": "download", "status": "ok", "file": file_path, "duration_ms": download_ms, "bytes": len(data)},
+    )
 
+    t0 = time.perf_counter()
     try:
         pages = extract(data, extension, filename=PurePosixPath(file_path).name)
     except UnsupportedFileType:
@@ -68,6 +76,11 @@ async def process_file(file_path: str, event_type: EventType) -> None:
     except Exception as exc:
         logger.exception("extract failed", extra={"event": "extract_failed", "file": file_path, "error": str(exc)})
         return
+    extract_ms = int((time.perf_counter() - t0) * 1000)
+    logger.info(
+        "extract ok",
+        extra={"event": "extract", "status": "ok", "file": file_path, "duration_ms": extract_ms, "pages": len(pages)},
+    )
 
     chunks: list[tuple[str, int, int]] = []  # (text, page, chunk_index)
     chunk_index = 0
@@ -87,11 +100,17 @@ async def process_file(file_path: str, event_type: EventType) -> None:
         delete_by_path(_qdrant_client(), settings.qdrant_collection, file_path)
         return
 
+    t0 = time.perf_counter()
     try:
         vectors = await embed_texts([c[0] for c in chunks], model=settings.ollama_embed_model)
     except Exception as exc:
         logger.exception("embed failed", extra={"event": "embed_failed", "file": file_path, "error": str(exc)})
         return
+    embed_ms = int((time.perf_counter() - t0) * 1000)
+    logger.info(
+        "embed ok",
+        extra={"event": "embed", "status": "ok", "file": file_path, "duration_ms": embed_ms, "chunks": len(vectors)},
+    )
 
     if len(vectors) != len(chunks):
         logger.error(
@@ -121,11 +140,19 @@ async def process_file(file_path: str, event_type: EventType) -> None:
         for vec, (text, page_num, idx) in zip(vectors, chunks)
     ]
 
+    t0 = time.perf_counter()
     qdrant = _qdrant_client()
     delete_by_path(qdrant, settings.qdrant_collection, file_path)
     upsert_chunks(qdrant, settings.qdrant_collection, points)
+    qdrant_ms = int((time.perf_counter() - t0) * 1000)
 
     logger.info(
         "ingested",
-        extra={"event": "ingest_done", "file": file_path, "chunks": len(points)},
+        extra={
+            "event": "ingest_done",
+            "status": "ok",
+            "file": file_path,
+            "chunks": len(points),
+            "duration_ms": qdrant_ms,
+        },
     )