Make build-index failures observable so root-cause analysis can proceed from real logs

Constraint: The live build-index investigation was blocked by stdout/stderr buffering that left log files at 0 bytes during long runs
Rejected: Keep diagnosing from progress files alone | they do not preserve traceback or stage-transition context
Confidence: high
Scope-risk: narrow
Directive: Preserve flush-on-progress behavior while chasing the remaining real-path build-index root cause
Tested: Verified tiny repro /tmp/chroma_repro_tiny12 writes live logs and traceback with RC=1 after flush=True change
Not-tested: No final fix for the real-path build-index exit yet

@@ -88,6 +88,7 @@
   - `refs_done=4420/8000`
   - `refs_done=4420/8000`
 - 当前仍未出现 `reference_*` 或 `evaluate.py`。
 - 当前仍未出现 `reference_*` 或 `evaluate.py`。
 - 因此下一轮工作重心必须切到：**排查 build-index 异常退出**，而不是继续把它当作纯线性慢任务。
 - 因此下一轮工作重心必须切到：**排查 build-index 异常退出**，而不是继续把它当作纯线性慢任务。
+- 已完成一个低风险修复：关键 `print()` 已加 `flush=True`，并已用极小样本 `RC=1` 失败复现验证日志/traceback 可实时落盘，不再出现 `0 bytes` 日志黑箱。
 - 下一次值得提交的事件：
 - 下一次值得提交的事件：
   1. 找到明确失败证据/退出原因
   1. 找到明确失败证据/退出原因
   2. 成功小样本复现并补日志
   2. 成功小样本复现并补日志

@@ -24,7 +24,7 @@ def cmd_generate_data(args):
         segment_duration=args.segment_duration,
         segment_duration=args.segment_duration,
         seed=args.seed,
         seed=args.seed,
     )
     )
-    print(f"[done] dataset generated at {args.output}")
+    print(f"[done] dataset generated at {args.output}", flush=True)
 
 
 
 
 def build_chroma_index(data_dir: Path, output_dir: Path, checkpoint_every_refs: int = 0):
 def build_chroma_index(data_dir: Path, output_dir: Path, checkpoint_every_refs: int = 0):
@@ -37,7 +37,7 @@ def build_chroma_index(data_dir: Path, output_dir: Path, checkpoint_every_refs:
         checkpoint_every_refs=checkpoint_every_refs,
         checkpoint_every_refs=checkpoint_every_refs,
         progress_path=str(output_dir / 'chromaprint_progress.json'),
         progress_path=str(output_dir / 'chromaprint_progress.json'),
     )
     )
-    print(f"[done] chromaprint index built: hashes={matcher.num_hashes}, postings={matcher.index_size}")
+    print(f"[done] chromaprint index built: hashes={matcher.num_hashes}, postings={matcher.index_size}", flush=True)
     return matcher
     return matcher
 
 
 
 
@@ -58,7 +58,7 @@ def build_embedding_index(
         checkpoint_every_refs=checkpoint_every_refs,
         checkpoint_every_refs=checkpoint_every_refs,
         resume=resume,
         resume=resume,
     )
     )
-    print(f"[done] embedding index built: {len(ref_ids)} refs")
+    print(f"[done] embedding index built: {len(ref_ids)} refs", flush=True)
     return embedder, ref_embs, ref_ids
     return embedder, ref_embs, ref_ids
 
 
 
 
@@ -67,12 +67,12 @@ def cmd_build_index(args):
     out_dir = Path(args.output)
     out_dir = Path(args.output)
     out_dir.mkdir(parents=True, exist_ok=True)
     out_dir.mkdir(parents=True, exist_ok=True)
 
 
-    print(f"[build-index] starting chromaprint index: data={data_dir} output={out_dir}")
+    print(f"[build-index] starting chromaprint index: data={data_dir} output={out_dir}", flush=True)
     build_chroma_index(data_dir, out_dir, checkpoint_every_refs=args.chromaprint_checkpoint_every_refs)
     build_chroma_index(data_dir, out_dir, checkpoint_every_refs=args.chromaprint_checkpoint_every_refs)
     print(
     print(
         f"[build-index] starting embedding index: model={args.model} device={args.device} "
         f"[build-index] starting embedding index: model={args.model} device={args.device} "
         f"resume={args.resume} checkpoint_every_refs={args.checkpoint_every_refs}"
         f"resume={args.resume} checkpoint_every_refs={args.checkpoint_every_refs}"
-    )
+    , flush=True)
     build_embedding_index(
     build_embedding_index(
         data_dir,
         data_dir,
         Path(args.model),
         Path(args.model),
@@ -108,7 +108,7 @@ def cmd_recognize(args):
             engine.load_metadata(str(p))
             engine.load_metadata(str(p))
 
 
     result = engine.recognize(args.query, top_n=args.top_n)
     result = engine.recognize(args.query, top_n=args.top_n)
-    print(json.dumps(result, ensure_ascii=False, indent=2))
+    print(json.dumps(result, ensure_ascii=False, indent=2), flush=True)
 
 
 
 
 def cmd_full_demo(args):
 def cmd_full_demo(args):
@@ -125,7 +125,7 @@ def cmd_full_demo(args):
             segment_duration=args.segment_duration,
             segment_duration=args.segment_duration,
             seed=args.seed,
             seed=args.seed,
         )
         )
-        print(f"[done] dataset generated at {data_dir}")
+        print(f"[done] dataset generated at {data_dir}", flush=True)
 
 
     model_path = model_dir / 'best_model.pt'
     model_path = model_dir / 'best_model.pt'
     if not model_path.exists():
     if not model_path.exists():
@@ -136,7 +136,7 @@ def cmd_full_demo(args):
             '--data', str(data_dir), '--output', str(model_dir),
             '--data', str(data_dir), '--output', str(model_dir),
             '--device', args.device, '--epochs', '3', '--batch-size', '8'
             '--device', args.device, '--epochs', '3', '--batch-size', '8'
         ]
         ]
-        print('[full-demo] training model:', ' '.join(cmd))
+        print('[full-demo] training model:', ' '.join(cmd), flush=True)
         subprocess.run(cmd, check=True)
         subprocess.run(cmd, check=True)
 
 
     index_dir.mkdir(parents=True, exist_ok=True)
     index_dir.mkdir(parents=True, exist_ok=True)
@@ -152,8 +152,8 @@ def cmd_full_demo(args):
     for split in ['train.json', 'val.json', 'test.json']:
     for split in ['train.json', 'val.json', 'test.json']:
         engine.load_metadata(str(data_dir / split))
         engine.load_metadata(str(data_dir / split))
     result = engine.recognize(str(query_path), top_n=5)
     result = engine.recognize(str(query_path), top_n=5)
-    print('[demo-query]', query_item['song_id'], query_item['audio_path'])
-    print(json.dumps(result, ensure_ascii=False, indent=2))
+    print('[demo-query]', query_item['song_id'], query_item['audio_path'], flush=True)
+    print(json.dumps(result, ensure_ascii=False, indent=2), flush=True)
 
 
 
 
 if __name__ == '__main__':
 if __name__ == '__main__':

@@ -139,7 +139,7 @@ class ChromaprintMatcher:
                     f"[chromaprint-index] progress: refs={ref_idx}/{total_refs} "
                     f"[chromaprint-index] progress: refs={ref_idx}/{total_refs} "
                     f"hashes={self.num_hashes} postings={self.index_size} "
                     f"hashes={self.num_hashes} postings={self.index_size} "
                     f"elapsed_sec={elapsed:.1f} eta_sec={eta_sec:.1f}"
                     f"elapsed_sec={elapsed:.1f} eta_sec={eta_sec:.1f}"
-                )
+                , flush=True)
             if checkpoint_every_refs > 0 and ref_idx % checkpoint_every_refs == 0:
             if checkpoint_every_refs > 0 and ref_idx % checkpoint_every_refs == 0:
                 if cache_file is not None:
                 if cache_file is not None:
                     self.save(str(cache_file))
                     self.save(str(cache_file))

@@ -48,7 +48,7 @@ class ECAPAEmbedder:
         )
         )
         missing = self.model.load_state_dict(state["model_state_dict"], strict=False)
         missing = self.model.load_state_dict(state["model_state_dict"], strict=False)
         if missing.unexpected_keys:
         if missing.unexpected_keys:
-            print(f"[warn] unexpected keys while loading model: {missing.unexpected_keys}")
+            print(f"[warn] unexpected keys while loading model: {missing.unexpected_keys}", flush=True)
         self.model.to(self.device)
         self.model.to(self.device)
         self.model.eval()
         self.model.eval()
 
 
@@ -133,7 +133,7 @@ class ECAPAEmbedder:
         refs_done = 0
         refs_done = 0
 
 
         if resume and final_embs_path.exists() and final_ids_path.exists():
         if resume and final_embs_path.exists() and final_ids_path.exists():
-            print(f"[build-reference-index] resume hit complete index: {final_embs_path} / {final_ids_path}")
+            print(f"[build-reference-index] resume hit complete index: {final_embs_path} / {final_ids_path}", flush=True)
             final_embs = np.load(final_embs_path)
             final_embs = np.load(final_embs_path)
             final_ids = np.load(final_ids_path, allow_pickle=True).tolist()
             final_ids = np.load(final_ids_path, allow_pickle=True).tolist()
             return final_embs, final_ids
             return final_embs, final_ids
@@ -154,9 +154,9 @@ class ECAPAEmbedder:
                 print(
                 print(
                     f"[build-reference-index] resuming from checkpoint: refs_done={refs_done}/{total_refs} "
                     f"[build-reference-index] resuming from checkpoint: refs_done={refs_done}/{total_refs} "
                     f"windows_done={len(all_ids)}"
                     f"windows_done={len(all_ids)}"
-                )
+                , flush=True)
             except Exception as exc:
             except Exception as exc:
-                print(f"[build-reference-index] resume checkpoint ignored due to load failure: {exc}")
+                print(f"[build-reference-index] resume checkpoint ignored due to load failure: {exc}", flush=True)
                 refs_done = 0
                 refs_done = 0
                 all_embs = []
                 all_embs = []
                 all_ids = []
                 all_ids = []
@@ -170,7 +170,7 @@ class ECAPAEmbedder:
         print(
         print(
             f"[build-reference-index] start: refs={total_refs} device={self.device.type} "
             f"[build-reference-index] start: refs={total_refs} device={self.device.type} "
             f"window_sec={window_sec} stride_sec={stride_sec} resume={resume} refs_done={refs_done}"
             f"window_sec={window_sec} stride_sec={stride_sec} resume={resume} refs_done={refs_done}"
-        )
+        , flush=True)
 
 
         def write_checkpoint(ref_idx: int):
         def write_checkpoint(ref_idx: int):
             if not all_embs:
             if not all_embs:
@@ -214,7 +214,7 @@ class ECAPAEmbedder:
             }, indent=2))
             }, indent=2))
 
 
         if refs_done > total_refs:
         if refs_done > total_refs:
-            print(f"[build-reference-index] resume refs_done={refs_done} exceeds refs_total={total_refs}; restarting")
+            print(f"[build-reference-index] resume refs_done={refs_done} exceeds refs_total={total_refs}; restarting", flush=True)
             refs_done = 0
             refs_done = 0
             all_embs = []
             all_embs = []
             all_ids = []
             all_ids = []
@@ -239,7 +239,7 @@ class ECAPAEmbedder:
                 print(
                 print(
                     f"[build-reference-index] progress: refs={ref_idx}/{total_refs} "
                     f"[build-reference-index] progress: refs={ref_idx}/{total_refs} "
                     f"windows={len(all_ids)} elapsed_sec={elapsed:.1f} eta_sec={eta_sec:.1f}"
                     f"windows={len(all_ids)} elapsed_sec={elapsed:.1f} eta_sec={eta_sec:.1f}"
-                )
+                , flush=True)
             if checkpoint_every_refs > 0 and (ref_idx % checkpoint_every_refs == 0 or ref_idx == total_refs):
             if checkpoint_every_refs > 0 and (ref_idx % checkpoint_every_refs == 0 or ref_idx == total_refs):
                 write_checkpoint(ref_idx)
                 write_checkpoint(ref_idx)
 
 
@@ -252,7 +252,7 @@ class ECAPAEmbedder:
         np.save(final_embs_path, all_embs)
         np.save(final_embs_path, all_embs)
         np.save(final_ids_path, np.array(all_ids))
         np.save(final_ids_path, np.array(all_ids))
         write_complete(len(all_ids), all_embs.shape)
         write_complete(len(all_ids), all_embs.shape)
-        print(f"Built reference index: {len(all_ids)} windows, embeddings shape {all_embs.shape}")
+        print(f"Built reference index: {len(all_ids)} windows, embeddings shape {all_embs.shape}", flush=True)
         return all_embs, all_ids
         return all_embs, all_ids
 
 
     def search(self, query_emb: np.ndarray, ref_embs: np.ndarray, ref_ids: List[str], top_k: int = 10):
     def search(self, query_emb: np.ndarray, ref_embs: np.ndarray, ref_ids: List[str], top_k: int = 10):

+## 2026-06-02 15:18 UTC / build-index log flush hardening
+
+- 为 `run_demo.py`、`chromaprint_matcher.py`、`ecapa_embedder.py` 的关键 `print()` 增加 `flush=True`
+- 目的：避免 `build-index` 长时间运行时日志文件保持 `0 bytes`，导致“无声运行/无声退出”难排查
+- fresh evidence：极小样本复现 `/tmp/chroma_repro_tiny12` 已验证日志实时落盘
+  - `RC=1`
+  - 日志中可见：`[build-index] starting chromaprint index`
+  - 日志中可见：`[build-reference-index] start: refs=12 ...`
+  - 日志中可见最终 traceback：`ValueError: No reference embeddings were produced ...`
+- 结论：当前至少已修复“失败时日志完全不可见”的可观测性问题，下一步可继续针对真实路径复现 root cause
+
 ## 2026-06-02 15:09 UTC / build-index unexpected exit checkpoint
 ## 2026-06-02 15:09 UTC / build-index unexpected exit checkpoint
 
 
 - 新鲜证据：observable 与 legacy 两个 `build-index` 进程都已退出
 - 新鲜证据：observable 与 legacy 两个 `build-index` 进程都已退出

@@ -44,3 +44,27 @@
 1. 当前已不应继续把它描述成“仅仅线性慢”。
 1. 当前已不应继续把它描述成“仅仅线性慢”。
 2. 下一轮工作应转向 **build-index 异常退出排查**。
 2. 下一轮工作应转向 **build-index 异常退出排查**。
 3. 新提交已经有意义，因为状态从“运行中”变成了“已退出且无下游产物”。
 3. 新提交已经有意义，因为状态从“运行中”变成了“已退出且无下游产物”。
+
+## 本次追加交付（2026-06-02 15:18 UTC）
+
+### 新增代码修复
+
+| 文件 | 变更 |
+|---|---|
+| [../acr-engine/run_demo.py](../acr-engine/run_demo.py) | `build-index` / demo 关键日志统一 `flush=True` |
+| [../acr-engine/src/engines/chromaprint_matcher.py](../acr-engine/src/engines/chromaprint_matcher.py) | chromaprint 阶段 progress 日志 `flush=True` |
+| [../acr-engine/src/engines/ecapa_embedder.py](../acr-engine/src/engines/ecapa_embedder.py) | embedding/reference 阶段关键日志 `flush=True` |
+
+### 新增验证证据
+
+- 极小样本复现：`/tmp/chroma_repro_tiny12`
+- 结果：`RC=1`
+- 现在日志已实时落盘，不再是 `0 bytes`：
+  - `[build-index] starting chromaprint index ...`
+  - `[build-reference-index] start: refs=12 ...`
+  - `ValueError: No reference embeddings were produced ...`
+
+### 结论
+
+- 当前已修复“失败时日志完全不可见”的可观测性问题。
+- 下一轮 root cause 排查可以直接依赖实时日志，而不再需要盲等。

@@ -44,6 +44,11 @@
 - 这不再是“CPU-only 长时间构建但仍在推进”的状态。
 - 这不再是“CPU-only 长时间构建但仍在推进”的状态。
 - 现在更像是：**`build-index` 在 chromaprint 阶段中途退出，但没有留下显式下游产物**。
 - 现在更像是：**`build-index` 在 chromaprint 阶段中途退出，但没有留下显式下游产物**。
 
 
+#### 已完成的低风险修复
+- 已把 `run_demo.py`、`chromaprint_matcher.py`、`ecapa_embedder.py` 的关键日志改为 `flush=True`。
+- 极小样本 `/tmp/chroma_repro_tiny12` 已验证：失败时日志与 traceback 可实时落盘，不再保持 `0 bytes`。
+- 这意味着下一 session 继续排查时，日志可作为一手证据，而不是黑箱。
+
 ## 新 session 接管顺序
 ## 新 session 接管顺序
 
 
 1. 先看 [./session-handoff.md](./session-handoff.md)
 1. 先看 [./session-handoff.md](./session-handoff.md)

@@ -31,6 +31,16 @@
   2. 查 silent failure / OOM / shell termination 证据
   2. 查 silent failure / OOM / shell termination 证据
   3. 用小样本复现异常并补日志
   3. 用小样本复现异常并补日志
 
 
+### 最新可观测性修复（2026-06-02 15:18 UTC）
+
+- 已为 `run_demo.py`、`src/engines/chromaprint_matcher.py`、`src/engines/ecapa_embedder.py` 的关键 `print()` 增加 `flush=True`。
+- 极小样本复现 `/tmp/chroma_repro_tiny12` 已验证：
+  - 日志文件不再保持 `0 bytes`
+  - traceback 可实时落盘
+- 当前已确认：至少“失败时无日志”这个问题已被修复；下一步继续追真实路径 root cause。
+
+- 验证结果补充：`RC=1`，日志中可见 `ValueError: No reference embeddings were produced ...`。
+
 这是一个正在从原型向工业化推进的 **音乐 ACR / music retrieval** 项目。  
 这是一个正在从原型向工业化推进的 **音乐 ACR / music retrieval** 项目。  
 当前已经完成：
 当前已经完成：