Skip to content

wanghai-tech / hikoon-ACR

Go to a project
Toggle navigation
Toggle navigation pinning
Commit 35d883a8 35d883a8d0279174504cbf1f04fe30d31b5f0600 by cnb.bofCdSsphPA
Options

Make semantic feature enrichment runtime-aware on the song-centric path 

Constraint: Keep the current real-directory import path executable on this host while making semantic-lane readiness explicit instead of pretending the heavyweight runtime exists.
Rejected: Hardwire semantic enrichment to the local fallback without reporting missing runtime state | It hides the true blocker and weakens the upgrade path to real semantic models.
Confidence: high
Scope-risk: narrow
Directive: On this host, treat local_wavehash_embed as a fallback semantic backend and persist missing runtime evidence until torch/torchaudio/transformers are installed.
Tested: /usr/local/miniconda3/bin/python acr-engine/scripts/enrich_songcentric_manifest_with_local_features.py on the real wav smoke manifest; imported the v3 enriched manifest twice into postgres://d2:d2pass@127.0.0.1:5432/d2 schema acr_songcentric_test and verified counts stayed media_entity=9, audio_object=22, feature_fact=24, set_membership=9; report shows semantic_runtime_available=false and missing=[torch, torchaudio, transformers]; git diff --check; /usr/local/miniconda3/bin/python scripts/check_markdown_links.py --root docs returned OK for 11 active markdown files
Not-tested: real MERT/MuQ extraction on this host
1 parent 7e3b0136
Inline Side-by-side
Showing 7 changed files with 232 additions and 12 deletions
{"song": {"biz_key": "song_alpha", "title": "song alpha", "artist_name": "artist a"}, "asset": {"source_type": "official", "storage_uri": "/workspace/acr-engine/data/songcentric_builder_smoke/song_alpha/artist_a/clip1.wav", "storage_scheme": "file", "checksum": "path:/workspace/acr-engine/data/songcentric_builder_smoke/song_alpha/artist_a/clip1.wav", "codec": "wav", "sample_rate": 16000, "channels": 1, "duration_ms": 8000}, "windows": [{"start_ms": 0, "end_ms": 5000, "features": [{"feature_type": "fingerprint", "model_name": "chromaprint_matcher", "model_version": "phase1_local", "feature_set_name": "chromaprint_matcher_5s", "fingerprint_value": "dc0c731425f360787f462da693ff4a50", "checksum": "chromaprint:dc0c731425f36078", "metadata_json": {"hash_count": 2643, "hash_sample": [[1842187, 11], [1842188, 11], [1842189, 11], [1842201, 11], [1842212, 11], [1842213, 11], [1842214, 11], [1842438, 11]]}}, {"feature_type": "embedding", "model_name": "local_wavehash_embed", "model_version": "v1", "feature_set_name": "wavehash_embed_5s", "feature_schema_ver": "v1", "embedding_dim": 8, "embedding_uri": "inline://593c7a661cc87444:0:5000", "vector_table_name": "audio_embedding_vector_8_placeholder", "checksum": "emb:593c7a661cc87444", "metadata_json": {"energy": 30555200, "rate": 16000, "channels": 1, "semantic_backend": "local_fallback", "runtime_missing": ["torch", "torchaudio", "transformers"]}}]}, {"start_ms": 2500, "end_ms": 7500, "features": [{"feature_type": "fingerprint", "model_name": "chromaprint_matcher", "model_version": "phase1_local", "feature_set_name": "chromaprint_matcher_5s", "fingerprint_value": "dc0c731425f360787f462da693ff4a50", "checksum": "chromaprint:dc0c731425f36078", "metadata_json": {"hash_count": 2643, "hash_sample": [[1842187, 11], [1842188, 11], [1842189, 11], [1842201, 11], [1842212, 11], [1842213, 11], [1842214, 11], [1842438, 11]]}}, {"feature_type": "embedding", "model_name": "local_wavehash_embed", "model_version": "v1", "feature_set_name": "wavehash_embed_5s", "feature_schema_ver": "v1", "embedding_dim": 8, "embedding_uri": "inline://593c7a661cc87444:2500:7500", "vector_table_name": "audio_embedding_vector_8_placeholder", "checksum": "emb:593c7a661cc87444", "metadata_json": {"energy": 30555200, "rate": 16000, "channels": 1, "semantic_backend": "local_fallback", "runtime_missing": ["torch", "torchaudio", "transformers"]}}]}, {"start_ms": 3000, "end_ms": 8000, "features": [{"feature_type": "fingerprint", "model_name": "chromaprint_matcher", "model_version": "phase1_local", "feature_set_name": "chromaprint_matcher_5s", "fingerprint_value": "dc0c731425f360787f462da693ff4a50", "checksum": "chromaprint:dc0c731425f36078", "metadata_json": {"hash_count": 2643, "hash_sample": [[1842187, 11], [1842188, 11], [1842189, 11], [1842201, 11], [1842212, 11], [1842213, 11], [1842214, 11], [1842438, 11]]}}, {"feature_type": "embedding", "model_name": "local_wavehash_embed", "model_version": "v1", "feature_set_name": "wavehash_embed_5s", "feature_schema_ver": "v1", "embedding_dim": 8, "embedding_uri": "inline://593c7a661cc87444:3000:8000", "vector_table_name": "audio_embedding_vector_8_placeholder", "checksum": "emb:593c7a661cc87444", "metadata_json": {"energy": 30555200, "rate": 16000, "channels": 1, "semantic_backend": "local_fallback", "runtime_missing": ["torch", "torchaudio", "transformers"]}}]}], "memberships": [{"set_type": "reference_set", "set_name": "phase1_hot_reference_v1", "member_type": "asset", "priority": 100}]}
{"song": {"biz_key": "song_beta", "title": "song beta", "artist_name": "artist b"}, "asset": {"source_type": "official", "storage_uri": "/workspace/acr-engine/data/songcentric_builder_smoke/song_beta/artist_b/clip2.wav", "storage_scheme": "file", "checksum": "path:/workspace/acr-engine/data/songcentric_builder_smoke/song_beta/artist_b/clip2.wav", "codec": "wav", "sample_rate": 16000, "channels": 1, "duration_ms": 6000}, "windows": [{"start_ms": 0, "end_ms": 5000, "features": [{"feature_type": "fingerprint", "model_name": "chromaprint_matcher", "model_version": "phase1_local", "feature_set_name": "chromaprint_matcher_5s", "fingerprint_value": "d8fc2442b4ec3ce5ae180c5845cffccb", "checksum": "chromaprint:d8fc2442b4ec3ce5", "metadata_json": {"hash_count": 2202, "hash_sample": [[2763289, 23], [2763524, 23], [2763541, 23], [2763549, 23], [2763566, 23], [2763801, 23], [2764050, 23], [2764075, 23]]}}, {"feature_type": "embedding", "model_name": "local_wavehash_embed", "model_version": "v1", "feature_set_name": "wavehash_embed_5s", "feature_schema_ver": "v1", "embedding_dim": 8, "embedding_uri": "inline://4ed2ccfa55b10b88:0:5000", "vector_table_name": "audio_embedding_vector_8_placeholder", "checksum": "emb:4ed2ccfa55b10b88", "metadata_json": {"energy": 30555680, "rate": 16000, "channels": 1, "semantic_backend": "local_fallback", "runtime_missing": ["torch", "torchaudio", "transformers"]}}]}, {"start_ms": 1000, "end_ms": 6000, "features": [{"feature_type": "fingerprint", "model_name": "chromaprint_matcher", "model_version": "phase1_local", "feature_set_name": "chromaprint_matcher_5s", "fingerprint_value": "d8fc2442b4ec3ce5ae180c5845cffccb", "checksum": "chromaprint:d8fc2442b4ec3ce5", "metadata_json": {"hash_count": 2202, "hash_sample": [[2763289, 23], [2763524, 23], [2763541, 23], [2763549, 23], [2763566, 23], [2763801, 23], [2764050, 23], [2764075, 23]]}}, {"feature_type": "embedding", "model_name": "local_wavehash_embed", "model_version": "v1", "feature_set_name": "wavehash_embed_5s", "feature_schema_ver": "v1", "embedding_dim": 8, "embedding_uri": "inline://4ed2ccfa55b10b88:1000:6000", "vector_table_name": "audio_embedding_vector_8_placeholder", "checksum": "emb:4ed2ccfa55b10b88", "metadata_json": {"energy": 30555680, "rate": 16000, "channels": 1, "semantic_backend": "local_fallback", "runtime_missing": ["torch", "torchaudio", "transformers"]}}]}], "memberships": [{"set_type": "reference_set", "set_name": "phase1_hot_reference_v1", "member_type": "asset", "priority": 100}]}
{
"schema": "acr_songcentric_test",
"manifest": "acr-engine/data/pgvector_eval/music20/songcentric_directory_manifest_with_features_v3.jsonl",
"imported": [
{
"song_id": 8,
"asset_id": 16,
"window_ids": [
17,
18,
19
],
"feature_ids": [
20,
11,
21,
13,
22,
15
],
"membership_ids": [
8
]
},
{
"song_id": 9,
"asset_id": 20,
"window_ids": [
21,
22
],
"feature_ids": [
23,
17,
24,
19
],
"membership_ids": [
9
]
}
],
"counts": {
"media_entity": 9,
"audio_object": 22,
"feature_fact": 24,
"set_membership": 9
},
"window_lineage_sample": {
"window_id": 22,
"asset_id": 20,
"song_id": 9,
"title": "song beta",
"start_ms": 1000,
"end_ms": 6000
},
"feature_lineage_sample": {
"feature_type": "fingerprint",
"model_name": "chromaprint_matcher",
"model_version": "phase1_local",
"feature_set_name": "chromaprint_matcher_5s",
"window_id": 22,
"song_id": 9,
"title": "song beta"
}
}
\ No newline at end of file
{
"schema": "acr_songcentric_test",
"manifest": "acr-engine/data/pgvector_eval/music20/songcentric_directory_manifest_with_features_v3.jsonl",
"imported": [
{
"song_id": 8,
"asset_id": 16,
"window_ids": [
17,
18,
19
],
"feature_ids": [
20,
11,
21,
13,
22,
15
],
"membership_ids": [
8
]
},
{
"song_id": 9,
"asset_id": 20,
"window_ids": [
21,
22
],
"feature_ids": [
23,
17,
24,
19
],
"membership_ids": [
9
]
}
],
"counts": {
"media_entity": 9,
"audio_object": 22,
"feature_fact": 24,
"set_membership": 9
},
"window_lineage_sample": {
"window_id": 22,
"asset_id": 20,
"song_id": 9,
"title": "song beta",
"start_ms": 1000,
"end_ms": 6000
},
"feature_lineage_sample": {
"feature_type": "fingerprint",
"model_name": "chromaprint_matcher",
"model_version": "phase1_local",
"feature_set_name": "chromaprint_matcher_5s",
"window_id": 22,
"song_id": 9,
"title": "song beta"
}
}
\ No newline at end of file
{
"input_manifest": "/workspace/acr-engine/data/pgvector_eval/music20/songcentric_directory_manifest.jsonl",
"output_manifest": "/workspace/acr-engine/data/pgvector_eval/music20/songcentric_directory_manifest_with_features_v3.jsonl",
"rows": 2,
"wav_windows_seen": 5,
"features_added": 10,
"matcher_fingerprint_count": 5,
"fallback_fingerprint_count": 0,
"semantic_runtime_available": false,
"semantic_runtime_missing": [
"torch",
"torchaudio",
"transformers"
],
"semantic_runtime_ready_count": 0,
"semantic_fallback_count": 5
}
\ No newline at end of file
......@@ -3,6 +3,7 @@ from __future__ import annotations
import argparse
import hashlib
import importlib
import json
import wave
from pathlib import Path
......@@ -22,6 +23,20 @@ def load_jsonl(path: Path):
yield json.loads(line)
def module_available(name: str) -> bool:
try:
importlib.import_module(name)
return True
except Exception:
return False
def semantic_runtime_available() -> tuple[bool, list[str]]:
required = ['torch', 'torchaudio', 'transformers']
missing = [m for m in required if not module_available(m)]
return (len(missing) == 0, missing)
def read_wav_stats(path: Path, start_ms: int, end_ms: int) -> dict:
with wave.open(str(path), 'rb') as wf:
rate = wf.getframerate()
......@@ -57,6 +72,40 @@ def extract_matcher_fingerprint(path: Path, start_ms: int, end_ms: int) -> dict
return None
def build_semantic_feature(stats: dict, start_ms: int, end_ms: int, runtime_ok: bool, missing: list[str]) -> dict:
if runtime_ok:
return {
'feature_type': 'embedding',
'model_name': 'semantic_runtime_ready_placeholder',
'model_version': 'awaiting_real_adapter',
'feature_set_name': 'semantic_runtime_ready_5s',
'feature_schema_ver': 'v1',
'embedding_dim': 8,
'embedding_uri': f"runtime-ready://{stats['digest'][:16]}:{start_ms}:{end_ms}",
'vector_table_name': 'audio_embedding_vector_8_placeholder',
'checksum': f"emb:{stats['digest'][:16]}",
'metadata_json': {'semantic_backend': 'runtime_ready_placeholder'},
}
return {
'feature_type': 'embedding',
'model_name': 'local_wavehash_embed',
'model_version': 'v1',
'feature_set_name': 'wavehash_embed_5s',
'feature_schema_ver': 'v1',
'embedding_dim': 8,
'embedding_uri': f"inline://{stats['digest'][:16]}:{start_ms}:{end_ms}",
'vector_table_name': 'audio_embedding_vector_8_placeholder',
'checksum': f"emb:{stats['digest'][:16]}",
'metadata_json': {
'energy': stats['energy'],
'rate': stats['rate'],
'channels': stats['channels'],
'semantic_backend': 'local_fallback',
'runtime_missing': missing,
},
}
def main() -> int:
parser = argparse.ArgumentParser()
parser.add_argument('--input-manifest', required=True)
......@@ -71,11 +120,16 @@ def main() -> int:
if report_path:
report_path.parent.mkdir(parents=True, exist_ok=True)
runtime_ok, missing_runtime = semantic_runtime_available()
rows = []
feature_count = 0
wav_windows_seen = 0
matcher_fp_count = 0
fallback_fp_count = 0
semantic_runtime_ready_count = 0
semantic_fallback_count = 0
for row in load_jsonl(in_path):
asset = row['asset']
asset_path = Path(asset['storage_uri'])
......@@ -107,18 +161,13 @@ def main() -> int:
'metadata_json': {'energy': stats['energy'], 'bytes_read': stats['bytes_read']},
}
fallback_fp_count += 1
emb = {
'feature_type': 'embedding',
'model_name': 'local_wavehash_embed',
'model_version': 'v1',
'feature_set_name': 'wavehash_embed_5s',
'feature_schema_ver': 'v1',
'embedding_dim': 8,
'embedding_uri': f"inline://{stats['digest'][:16]}:{window['start_ms']}:{window['end_ms']}",
'vector_table_name': 'audio_embedding_vector_8_placeholder',
'checksum': f"emb:{stats['digest'][:16]}",
'metadata_json': {'energy': stats['energy'], 'rate': stats['rate'], 'channels': stats['channels']},
}
emb = build_semantic_feature(stats, window['start_ms'], window['end_ms'], runtime_ok, missing_runtime)
if runtime_ok:
semantic_runtime_ready_count += 1
else:
semantic_fallback_count += 1
features.extend([fp, emb])
feature_count += 2
rows.append(row)
......@@ -132,6 +181,10 @@ def main() -> int:
'features_added': feature_count,
'matcher_fingerprint_count': matcher_fp_count,
'fallback_fingerprint_count': fallback_fp_count,
'semantic_runtime_available': runtime_ok,
'semantic_runtime_missing': missing_runtime,
'semantic_runtime_ready_count': semantic_runtime_ready_count,
'semantic_fallback_count': semantic_fallback_count,
}
if report_path:
report_path.write_text(json.dumps(report, ensure_ascii=False, indent=2))
......
## 2026-06-04
- 升级 `enrich_songcentric_manifest_with_local_features.py` 为 runtime-aware 语义适配器选择：当前 host 上因缺少 `torch/torchaudio/transformers`，semantic lane 明确写入 `local_wavehash_embed` fallback，并把缺失依赖固化到 report/metadata 中。
- 升级 `enrich_songcentric_manifest_with_local_features.py`：目录链中的 fingerprint 现优先复用仓库内 `ChromaprintMatcher`，并在 live PostgreSQL 上验证 5 个 wav windows 全部命中 matcher 路径、`fallback_fingerprint_count=0`。
- 新增 `acr-engine/scripts/enrich_songcentric_manifest_with_local_features.py`，可对真实 wav 目录生成的 manifest 自动补本地 deterministic fingerprint/embedding，再导入 `feature_fact`；已在 live PostgreSQL 上验证 `audio files -> manifest -> features -> import` 闭环与幂等性。
......
......@@ -312,6 +312,20 @@ flowchart TD
这说明当前目录链里的 exact lane 已经不只是临时 hash，而是优先接上了仓库现有 fingerprint 提取能力。
### 4.9 目录链中的 semantic lane 运行时选择
当前 `enrich_songcentric_manifest_with_local_features.py` 对 semantic lane 采用 **runtime-aware** 选择：
- 如果 `torch / torchaudio / transformers` 可用，则预留真实 semantic adapter 入口
- 如果不可用，则明确落到 `local_wavehash_embed` fallback，并把缺失依赖写进 metadata/report
本轮 fresh evidence：
- `semantic_runtime_available = false`
- `semantic_runtime_missing = ["torch", "torchaudio", "transformers"]`
- `semantic_fallback_count = 5`
这说明当前 host 上 semantic lane 还未接真实模型，但链路已经具备明确的运行时分流与可审计证据。
---
## 5. 最常用 SQL 样例
......