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Merge pull request #749 from SuanmoSuanyangTechnology/fix/perceptual-write

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refactor(memory_agent_service, memory_perceptual_service): Simplify audit logger import and usage
This commit is contained in:
Ke Sun
2026-03-31 14:20:59 +08:00
committed by GitHub
parent 75e8caf441 2ad25c48d2
commit 87c2419186
2 changed files with 60 additions and 61 deletions
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108
api/app/services/memory_agent_service.py
View File

@@ -37,6 +37,7 @@ from app.core.memory.agent.utils.type_classifier import status_typle
from app.core.memory.agent.utils.write_tools import write as write_neo4j
from app.core.memory.analytics.hot_memory_tags import get_interest_distribution
from app.core.memory.utils.llm.llm_utils import MemoryClientFactory
from app.core.memory.utils.log.audit_logger import audit_logger
from app.db import get_db_context
from app.models.knowledge_model import Knowledge, KnowledgeType
from app.repositories.neo4j.neo4j_connector import Neo4jConnector
@@ -49,10 +50,6 @@ from app.services.memory_konwledges_server import (
)
from app.services.memory_perceptual_service import MemoryPerceptualService
try:
from app.core.memory.utils.log.audit_logger import audit_logger
except ImportError:
audit_logger = None
logger = get_logger(__name__)
config_logger = get_config_logger()
@@ -68,24 +65,22 @@ class MemoryAgentService:
if str(messages) == 'success':
logger.info(f"Write operation successful for group {end_user_id} with config_id {config_id}")
# 记录成功的操作
if audit_logger:
audit_logger.log_operation(operation="WRITE", config_id=config_id, end_user_id=end_user_id,
success=True,
duration=duration, details={"message_length": len(message)})
audit_logger.log_operation(operation="WRITE", config_id=config_id, end_user_id=end_user_id,
success=True,
duration=duration, details={"message_length": len(message)})
return context
else:
logger.warning(f"Write operation failed for group {end_user_id}")
# 记录失败的操作
if audit_logger:
audit_logger.log_operation(
operation="WRITE",
config_id=config_id,
end_user_id=end_user_id,
success=False,
duration=duration,
error=f"写入失败: {messages[:100]}"
)
audit_logger.log_operation(
operation="WRITE",
config_id=config_id,
end_user_id=end_user_id,
success=False,
duration=duration,
error=f"写入失败: {messages[:100]}"
)
raise ValueError(f"写入失败: {messages}")
@@ -338,10 +333,9 @@ class MemoryAgentService:
logger.error(error_msg)
# Log failed operation
if audit_logger:
duration = time.time() - start_time
audit_logger.log_operation(operation="WRITE", config_id=config_id, end_user_id=end_user_id,
success=False, duration=duration, error=error_msg)
duration = time.time() - start_time
audit_logger.log_operation(operation="WRITE", config_id=config_id, end_user_id=end_user_id,
success=False, duration=duration, error=error_msg)
raise ValueError(error_msg)
@@ -401,10 +395,10 @@ class MemoryAgentService:
# Ensure proper error handling and logging
error_msg = f"Write operation failed: {str(e)}"
logger.error(error_msg)
if audit_logger:
duration = time.time() - start_time
audit_logger.log_operation(operation="WRITE", config_id=config_id, end_user_id=end_user_id,
success=False, duration=duration, error=error_msg)
duration = time.time() - start_time
audit_logger.log_operation(operation="WRITE", config_id=config_id, end_user_id=end_user_id,
success=False, duration=duration, error=error_msg)
raise ValueError(error_msg)
async def read_memory(
@@ -469,10 +463,9 @@ class MemoryAgentService:
logger.info(f"Read operation for group {end_user_id} with config_id {config_id}")
# 导入审计日志记录器
try:
from app.core.memory.utils.log.audit_logger import audit_logger
except ImportError:
audit_logger = None
config_load_start = time.time()
try:
@@ -492,16 +485,15 @@ class MemoryAgentService:
logger.error(error_msg)
# Log failed operation
if audit_logger:
duration = time.time() - start_time
audit_logger.log_operation(
operation="READ",
config_id=config_id,
end_user_id=end_user_id,
success=False,
duration=duration,
error=error_msg
)
duration = time.time() - start_time
audit_logger.log_operation(
operation="READ",
config_id=config_id,
end_user_id=end_user_id,
success=False,
duration=duration,
error=error_msg
)
raise ValueError(error_msg)
@@ -633,15 +625,15 @@ class MemoryAgentService:
total_time = time.time() - start_time
logger.info(
f"[PERF] read_memory completed successfully in {total_time:.4f}s (config: {config_load_time:.4f}s, graph: {graph_exec_time:.4f}s)")
if audit_logger:
duration = time.time() - start_time
audit_logger.log_operation(
operation="READ",
config_id=config_id,
end_user_id=end_user_id,
success=True,
duration=duration
)
duration = time.time() - start_time
audit_logger.log_operation(
operation="READ",
config_id=config_id,
end_user_id=end_user_id,
success=True,
duration=duration
)
return {
"answer": summary,
@@ -651,16 +643,16 @@ class MemoryAgentService:
# Ensure proper error handling and logging
error_msg = f"Read operation failed: {str(e)}"
logger.error(error_msg)
if audit_logger:
duration = time.time() - start_time
audit_logger.log_operation(
operation="READ",
config_id=config_id,
end_user_id=end_user_id,
success=False,
duration=duration,
error=error_msg
)
duration = time.time() - start_time
audit_logger.log_operation(
operation="READ",
config_id=config_id,
end_user_id=end_user_id,
success=False,
duration=duration,
error=error_msg
)
raise ValueError(error_msg)
def get_messages_list(self, user_input: Write_UserInput) -> list[dict]:

13
api/app/services/memory_perceptual_service.py
View File

@@ -244,6 +244,8 @@ class MemoryPerceptualService:
file: FileInput
):
llm, model_config = self._get_mutlimodal_client(file.type, memory_config)
if model_config is None or llm is None:
return None
multimodel_service = MultimodalService(self.db, ModelInfo(
model_name=model_config.model_name,
provider=model_config.provider,
@@ -265,15 +267,20 @@ class MemoryPerceptualService:
with open(os.path.join(prompt_path, 'perceptual_summary_system.jinja2'), 'r', encoding='utf-8') as f:
opt_system_prompt = f.read()
rendered_system_message = Template(opt_system_prompt).render(file_type=file.type, language='zh')
except FileNotFoundError:
raise BusinessException(message="System prompt template not found", code=BizCode.NOT_FOUND)
except FileNotFoundError as e:
business_logger.error(f"Failed to generate perceptual memory: {str(e)}")
return None
messages = [
{"role": RoleType.SYSTEM.value, "content": [{"type": "text", "text": rendered_system_message}]},
{"role": RoleType.USER.value, "content": [
{"type": "text", "text": "Summarize the following file"}, file_message
]}
]
result = await llm.ainvoke(messages)
try:
result = await llm.ainvoke(messages)
except Exception as e:
business_logger.error(f"Failed to generate perceptual memory: {str(e)}")
return None
content = result.content
final_output = ""
if isinstance(content, list):