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fix:收敛A_Memorix最小回归修复

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最小修复聊天摘要写回游标恢复、摘要元数据透传、webui反馈参数解析、embedding批次缓存索引、图存储清理与配置默认值回归，并补齐针对性回归测试，确保问题解决且不影响现有逻辑。
This commit is contained in:
A-Dawn
2026-04-16 20:28:54 +08:00
parent 322309bef9
commit 6bfccf90a3
17 changed files with 361 additions and 60 deletions
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10
src/A_memorix/core/embedding/api_adapter.py
View File

@@ -385,19 +385,19 @@ class EmbeddingAPIAdapter:
semaphore = asyncio.Semaphore(self.max_concurrent)
async def encode_with_semaphore(text: str, index: int):
async def encode_with_semaphore(text: str, batch_index: int, absolute_index: int):
async with semaphore:
embedding = await self._get_embedding_direct(text, dimensions=dimensions)
if embedding is None:
raise RuntimeError(f"文本 {index} 编码失败：embedding 返回为空")
raise RuntimeError(f"文本 {absolute_index} 编码失败：embedding 返回为空")
vector = self._validate_embedding_vector(
embedding,
source=f"文本 {index}",
source=f"文本 {absolute_index}",
)
return index, vector
return batch_index, vector
tasks = [
encode_with_semaphore(text, offset + index)
encode_with_semaphore(text, index, offset + index)
for index, text in uncached_items
]
results = await asyncio.gather(*tasks)

8
src/A_memorix/core/runtime/sdk_memory_kernel.py
View File

@@ -803,6 +803,7 @@ class SDKMemoryKernel:
context_length: Optional[int] = None,
include_personality: Optional[bool] = None,
time_end: Optional[float] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> Dict[str, Any]:
await self.initialize()
assert self.summary_importer
@@ -811,6 +812,7 @@ class SDKMemoryKernel:
context_length=context_length,
include_personality=include_personality,
time_end=time_end,
metadata=metadata,
)
if success:
await self.rebuild_episodes_for_sources([self._build_source("chat_summary", chat_id, [])])
@@ -854,6 +856,12 @@ class SDKMemoryKernel:
context_length=self._optional_int(summary_meta.get("context_length")),
include_personality=summary_meta.get("include_personality"),
time_end=time_end,
metadata={
**summary_meta,
"external_id": external_token,
"chat_id": str(chat_id or "").strip(),
"source_type": "chat_summary",
},
)
result.setdefault("external_id", external_id)
result.setdefault("chat_id", chat_id)

9
src/A_memorix/core/storage/graph_store.py
View File

@@ -1294,6 +1294,7 @@ class GraphStore:
if current_n == 0:
logger.warning("检测到空图元数据但邻接矩阵仍然存在，已重置为空图。")
self._adjacency = None
self._edge_hash_map = defaultdict(set)
elif current_n > adj_n:
logger.warning(f"检测到图存储维度不匹配: 节点数={current_n}, 矩阵大小={adj_n}. 正在自动修复...")
self._expand_adjacency_matrix(current_n - adj_n)
@@ -1305,6 +1306,14 @@ class GraphStore:
self._adjacency = csc_matrix((current_n, current_n), dtype=np.float32)
else:
self._adjacency = csr_matrix((current_n, current_n), dtype=np.float32)
self._edge_hash_map = defaultdict(
set,
{
(src_idx, dst_idx): set(hashes)
for (src_idx, dst_idx), hashes in self._edge_hash_map.items()
if src_idx < current_n and dst_idx < current_n
},
)
self._adjacency_dirty = True
logger.info(

43
src/A_memorix/core/storage/metadata_store.py
View File

@@ -178,6 +178,27 @@ class MetadataStore:
int(knowledge_type_result.get("normalized", 0) or 0),
)
def _ensure_memory_feedback_task_columns(self, cursor: sqlite3.Cursor) -> None:
"""补齐 memory_feedback_tasks 历史库缺失的 rollback_* 列。"""
cursor.execute("PRAGMA table_info(memory_feedback_tasks)")
feedback_task_columns = {row[1] for row in cursor.fetchall()}
feedback_task_migrations = {
"rollback_status": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_status TEXT DEFAULT 'none'",
"rollback_plan_json": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_plan_json TEXT",
"rollback_result_json": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_result_json TEXT",
"rollback_error": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_error TEXT",
"rollback_requested_by": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_requested_by TEXT",
"rollback_reason": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_reason TEXT",
"rollback_requested_at": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_requested_at REAL",
"rolled_back_at": "ALTER TABLE memory_feedback_tasks ADD COLUMN rolled_back_at REAL",
}
for col, sql in feedback_task_migrations.items():
if col not in feedback_task_columns:
try:
cursor.execute(sql)
except sqlite3.OperationalError as e:
logger.warning(f"Schema迁移失败 (memory_feedback_tasks.{col}): {e}")
def close(self) -> None:
"""关闭数据库连接"""
if self._conn:
@@ -641,24 +662,7 @@ class MetadataStore:
CREATE INDEX IF NOT EXISTS idx_person_profile_refresh_queue_requested
ON person_profile_refresh_queue(requested_at DESC)
""")
cursor.execute("PRAGMA table_info(memory_feedback_tasks)")
feedback_task_columns = {row[1] for row in cursor.fetchall()}
feedback_task_migrations = {
"rollback_status": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_status TEXT DEFAULT 'none'",
"rollback_plan_json": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_plan_json TEXT",
"rollback_result_json": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_result_json TEXT",
"rollback_error": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_error TEXT",
"rollback_requested_by": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_requested_by TEXT",
"rollback_reason": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_reason TEXT",
"rollback_requested_at": "ALTER TABLE memory_feedback_tasks ADD COLUMN rollback_requested_at REAL",
"rolled_back_at": "ALTER TABLE memory_feedback_tasks ADD COLUMN rolled_back_at REAL",
}
for col, sql in feedback_task_migrations.items():
if col not in feedback_task_columns:
try:
cursor.execute(sql)
except sqlite3.OperationalError as e:
logger.warning(f"Schema迁移失败 (memory_feedback_tasks.{col}): {e}")
self._ensure_memory_feedback_task_columns(cursor)
cursor.execute("""
CREATE TABLE IF NOT EXISTS external_memory_refs (
external_id TEXT PRIMARY KEY,
@@ -953,6 +957,7 @@ class MetadataStore:
CREATE INDEX IF NOT EXISTS idx_person_profile_refresh_queue_requested
ON person_profile_refresh_queue(requested_at DESC)
""")
self._ensure_memory_feedback_task_columns(cursor)
cursor.execute("""
CREATE TABLE IF NOT EXISTS external_memory_refs (
external_id TEXT PRIMARY KEY,
@@ -3945,6 +3950,8 @@ class MetadataStore:
"episodes", "episode_paragraphs",
"episode_rebuild_sources", "episode_pending_paragraphs",
"paragraph_vector_backfill",
"memory_feedback_tasks", "memory_feedback_action_logs",
"paragraph_stale_relation_marks", "person_profile_refresh_queue",
]
for table in tables:
cursor.execute(f"DELETE FROM {table}")

12
src/A_memorix/core/utils/summary_importer.py
View File

@@ -225,6 +225,7 @@ class SummaryImporter:
context_length: Optional[int] = None,
include_personality: Optional[bool] = None,
time_end: Optional[float] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> Tuple[bool, str]:
"""
从指定的聊天流中提取记录并执行总结导入
@@ -327,7 +328,14 @@ class SummaryImporter:
}
# 6. 执行导入
await self._execute_import(summary_text, entities, relations, stream_id, time_meta=time_meta)
await self._execute_import(
summary_text,
entities,
relations,
stream_id,
time_meta=time_meta,
metadata=metadata,
)
# 7. 持久化
self.vector_store.save()
@@ -393,6 +401,7 @@ class SummaryImporter:
relations: List[Dict[str, str]],
stream_id: str,
time_meta: Optional[Dict[str, Any]] = None,
metadata: Optional[Dict[str, Any]] = None,
):
"""将数据写入存储"""
# 获取默认知识类型
@@ -407,6 +416,7 @@ class SummaryImporter:
hash_value = self.metadata_store.add_paragraph(
content=summary,
source=f"chat_summary:{stream_id}",
metadata=metadata,
knowledge_type=knowledge_type.value,
time_meta=time_meta,
)

24
src/A_memorix/scripts/release_vnext_migrate.py
View File

@@ -375,30 +375,6 @@ def _preflight_impl(config_path: Path, data_dir: Path) -> Dict[str, Any]:
"memory_feedback_tasks rollback columns missing under current schema version",
)
)
elif not has_stale_marks:
checks.append(
CheckItem(
"CP-15",
"error",
"paragraph_stale_relation_marks table missing under current schema version",
)
)
elif not has_profile_refresh_queue:
checks.append(
CheckItem(
"CP-16",
"error",
"person_profile_refresh_queue table missing under current schema version",
)
)
elif not has_feedback_rollback_status or not has_feedback_rollback_plan:
checks.append(
CheckItem(
"CP-17",
"error",
"memory_feedback_tasks rollback columns missing under current schema version",
)
)
if _sqlite_table_exists(conn, "relations"):
row = conn.execute("SELECT COUNT(*) FROM relations").fetchone()