Give spoken words a memory with an instant attached

An audio file used to produce no memory at all: _ingest_file returned an empty
batch for any suffix it did not know, with no log and no reason. It now raises
UnsupportedFile when you name the file and records a SkippedFile when it was a
directory walk, so a refusal is visible either way.

Speech is measured, not promised. Over 210.5 seconds of real Video-MME audio,
faster-whisper-tiny on CPU int8 transcribed at 51x realtime and reached word
error rate 0.242 against community subtitles nobody here wrote (a caption track
drops words a transcript keeps, so that is an upper bound). 66 speech atoms now
carry 550 word-level timestamps, 0 words out of order and 0 starting before
their own segment. The snapshot is 78.2 MB, under the 500 MB cap, and the report
is bench/reports/ASR.md.

Two library facts were measured rather than assumed. faster-whisper's own audio
loader is broken against PyAV 19 (av.open got an unexpected keyword
'metadata_errors') and it declares av with no version bound, so asr.decode_audio
decodes with PyAV directly and hands the model a float32 array instead of
pinning an old av with no cp314 wheel. And av.Error does not exist on PyAV 19 -
the real base is av.error.FFmpegError - so that is the only thing caught and my
own ValueErrors keep their messages.

Files over the 500-line rule were split rather than excused: ingestion.py (748)
into ingestion_common / ingestion_media / ingestion_repository / ingestion, and
cli.py (544) into cli_senses plus cli_common, following the cli_transactive
register pattern. MediaIngest declares _source_record abstract, so a half-wired
host fails at construction instead of returning None.

Verification: 207 tests pass; ruff clean on the 13 touched files; mypy clean on
them, and repo-wide mypy fell from 29 errors to 24 (5 fixed, none added);
pyright reports 0 errors on the touched files.

backend/src/ely_eye/config.py

@@ -17,10 +17,11 @@ class Settings(BaseSettings):
     model_dir: Path | None = None
     kv_cache_dtype: str = "auto"
     planner_model_id: str = "Qwen/Qwen3.5-0.8B"
-    embedding_model_id: str = "Qwen/Qwen3-VL-Embedding-8B"
+    embedding_model_id: str = "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2"
     clip_model_dir: Path | None = None
     vlm_model_dir: Path | None = None
     vlm_max_new_tokens: int = 96
+    asr_model_dir: Path | None = None
     adapter_dir: Path | None = None
     runtime_backend: Literal["sglang", "transformers"] = "transformers"
     sglang_base_url: str = "http://127.0.0.1:8000/v1"