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config_config替换成memory_config

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This commit is contained in:
lixinyue
2026-01-22 18:43:22 +08:00
parent f3f9211c9c
commit 8db4f914d8
21 changed files with 158 additions and 201 deletions
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6
api/app/services/emotion_config_service.py
View File

@@ -8,6 +8,8 @@ Classes:
"""
from typing import Dict, Any
from uuid import UUID
from sqlalchemy.orm import Session
from app.models.memory_config_model import MemoryConfig
@@ -37,7 +39,7 @@ class EmotionConfigService:
self.db = db
logger.info("情绪配置服务初始化完成")
def get_emotion_config(self, config_id: int) -> Dict[str, Any]:
def get_emotion_config(self, config_id: UUID) -> Dict[str, Any]:
"""获取情绪引擎配置
查询指定配置ID的情绪相关配置字段。
@@ -144,7 +146,7 @@ class EmotionConfigService:
def update_emotion_config(
self,
config_id: int,
config_id: UUID,
config_data: Dict[str, Any]
) -> Dict[str, Any]:
"""更新情绪引擎配置

130
api/app/services/memory_agent_service.py
View File

@@ -9,6 +9,7 @@ import os
import re
import time
import uuid
from uuid import UUID
from typing import Any, AsyncGenerator, Dict, List, Optional
import redis
@@ -266,7 +267,7 @@ class MemoryAgentService:
logger.info("Log streaming completed, cleaning up resources")
# LogStreamer uses context manager for file handling, so cleanup is automatic
async def write_memory(self, end_user_id: str, messages: str, config_id: Optional[str], db: Session, storage_type: str, user_rag_memory_id: str) -> str:
async def write_memory(self, end_user_id: str, messages: list[dict], config_id: Optional[uuid.UUID], db: Session, storage_type: str, user_rag_memory_id: str) -> str:
"""
Process write operation with config_id
@@ -319,85 +320,52 @@ class MemoryAgentService:
raise ValueError(error_msg)
async with make_write_graph() as graph:
config = {"configurable": {"thread_id": end_user_id}}
# Convert structured messages to LangChain messages
langchain_messages = []
for msg in messages:
if msg['role'] == 'user':
langchain_messages.append(HumanMessage(content=msg['content']))
elif msg['role'] == 'assistant':
langchain_messages.append(AIMessage(content=msg['content']))
try:
if storage_type == "rag":
# For RAG storage, convert messages to single string
message_text = "\n".join([f"{msg['role']}: {msg['content']}" for msg in messages])
result = await write_rag(end_user_id, message_text, user_rag_memory_id)
return result
else:
async with make_write_graph() as graph:
config = {"configurable": {"thread_id": end_user_id}}
# Convert structured messages to LangChain messages
langchain_messages = []
for msg in messages:
if msg['role'] == 'user':
langchain_messages.append(HumanMessage(content=msg['content']))
elif msg['role'] == 'assistant':
langchain_messages.append(AIMessage(content=msg['content']))
# 初始状态 - 包含所有必要字段
initial_state = {
"messages": langchain_messages,
"end_user_id": end_user_id,
"memory_config": memory_config
}
# 初始状态 - 包含所有必要字段
initial_state = {
"messages": langchain_messages,
"end_user_id": end_user_id,
"memory_config": memory_config
}
# 获取节点更新信息
async for update_event in graph.astream(
initial_state,
stream_mode="updates",
config=config
):
for node_name, node_data in update_event.items():
if 'save_neo4j' == node_name:
massages = node_data
print(massages)
massagesstatus = massages.get('write_result')['status']
contents = massages.get('write_result')
# Convert messages back to string for logging
message_text = "\n".join([f"{msg['role']}: {msg['content']}" for msg in messages])
return self.writer_messages_deal(massagesstatus, start_time, end_user_id, config_id, message_text, contents)
# try:
# if storage_type == "rag":
# # For RAG storage, convert messages to single string
# message_text = "\n".join([f"{msg['role']}: {msg['content']}" for msg in messages])
# result = await write_rag(end_user_id, message_text, user_rag_memory_id)
# return result
# else:
# async with make_write_graph() as graph:
# config = {"configurable": {"thread_id": end_user_id}}
# # Convert structured messages to LangChain messages
# langchain_messages = []
# for msg in messages:
# if msg['role'] == 'user':
# langchain_messages.append(HumanMessage(content=msg['content']))
# elif msg['role'] == 'assistant':
# langchain_messages.append(AIMessage(content=msg['content']))
#
# # 初始状态 - 包含所有必要字段
# initial_state = {
# "messages": langchain_messages,
# "end_user_id": end_user_id,
# "memory_config": memory_config
# }
#
# # 获取节点更新信息
# async for update_event in graph.astream(
# initial_state,
# stream_mode="updates",
# config=config
# ):
# for node_name, node_data in update_event.items():
# if 'save_neo4j' == node_name:
# massages = node_data
# massagesstatus = massages.get('write_result')['status']
# contents = massages.get('write_result')
# # Convert messages back to string for logging
# message_text = "\n".join([f"{msg['role']}: {msg['content']}" for msg in messages])
# return self.writer_messages_deal(massagesstatus, start_time, end_user_id, config_id, message_text, contents)
# except Exception as e:
# # 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)
# raise ValueError(error_msg)
# 获取节点更新信息
async for update_event in graph.astream(
initial_state,
stream_mode="updates",
config=config
):
for node_name, node_data in update_event.items():
if 'save_neo4j' == node_name:
massages = node_data
massagesstatus = massages.get('write_result')['status']
contents = massages.get('write_result')
# Convert messages back to string for logging
message_text = "\n".join([f"{msg['role']}: {msg['content']}" for msg in messages])
return self.writer_messages_deal(massagesstatus, start_time, end_user_id, config_id, message_text, contents)
except Exception as e:
# 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)
raise ValueError(error_msg)
@@ -408,7 +376,7 @@ class MemoryAgentService:
message: str,
history: List[Dict],
search_switch: str,
config_id: Optional[str],
config_id: Optional[UUID],
db: Session,
storage_type: str,
user_rag_memory_id: str) -> Dict:
@@ -685,7 +653,7 @@ class MemoryAgentService:
logger.info(f"Validation successful: Structured message list, count: {len(user_input.messages)}")
return user_input.messages
async def classify_message_type(self, message: str, config_id: int, db: Session) -> Dict:
async def classify_message_type(self, message: str, config_id: UUID, db: Session) -> Dict:
"""
Determine the type of user message (read or write)
Updated to eliminate global variables in favor of explicit parameters.
@@ -716,7 +684,7 @@ class MemoryAgentService:
retrieve_info: str,
history: List[Dict],
query: str,
config_id: str,
config_id: UUID,
db: Session
) -> str:
"""

81
api/app/services/memory_config_service.py
View File

@@ -23,53 +23,12 @@ from app.schemas.memory_config_schema import (
ModelNotFoundError,
)
from sqlalchemy.orm import Session
from uuid import UUID
logger = get_logger(__name__)
config_logger = get_config_logger()
def _validate_config_id(config_id):
"""Validate configuration ID format."""
if config_id is None:
raise InvalidConfigError(
"Configuration ID cannot be None",
field_name="config_id",
invalid_value=config_id,
)
if isinstance(config_id, int):
if config_id <= 0:
raise InvalidConfigError(
f"Configuration ID must be positive: {config_id}",
field_name="config_id",
invalid_value=config_id,
)
return config_id
if isinstance(config_id, str):
try:
parsed_id = int(config_id.strip())
if parsed_id <= 0:
raise InvalidConfigError(
f"Configuration ID must be positive: {parsed_id}",
field_name="config_id",
invalid_value=config_id,
)
return parsed_id
except ValueError:
raise InvalidConfigError(
f"Invalid configuration ID format: '{config_id}'",
field_name="config_id",
invalid_value=config_id,
)
raise InvalidConfigError(
f"Invalid type for configuration ID: expected int or str, got {type(config_id).__name__}",
field_name="config_id",
invalid_value=config_id,
)
class MemoryConfigService:
"""
Centralized service for memory configuration loading and validation.
@@ -93,14 +52,14 @@ class MemoryConfigService:
def load_memory_config(
self,
config_id: int,
config_id: UUID,
service_name: str = "MemoryConfigService",
) -> MemoryConfig:
"""
Load memory configuration from database by config_id.
Args:
config_id: Configuration ID from database
config_id: Configuration ID (UUID) from database
service_name: Name of the calling service (for logging purposes)
Returns:
@@ -116,18 +75,34 @@ class MemoryConfigService:
extra={
"operation": "load_memory_config",
"service": service_name,
"config_id": config_id,
"config_id": str(config_id),
},
)
logger.info(f"Loading memory configuration from database: config_id={config_id}")
try:
validated_config_id = _validate_config_id(config_id)
# Validate config_id is UUID
if not isinstance(config_id, UUID):
if isinstance(config_id, str):
try:
config_id = UUID(config_id)
except ValueError:
raise InvalidConfigError(
f"Invalid UUID format for config_id: {config_id}",
field_name="config_id",
invalid_value=config_id,
)
else:
raise InvalidConfigError(
f"config_id must be UUID or valid UUID string, got {type(config_id).__name__}",
field_name="config_id",
invalid_value=config_id,
)
# Step 1: Get config and workspace
db_query_start = time.time()
result = MemoryConfigRepository.get_config_with_workspace(self.db, validated_config_id)
result = MemoryConfigRepository.get_config_with_workspace(self.db, config_id)
db_query_time = time.time() - db_query_start
logger.info(f"[PERF] Config+Workspace query: {db_query_time:.4f}s")
if not result:
@@ -136,14 +111,14 @@ class MemoryConfigService:
"Configuration not found in database",
extra={
"operation": "load_memory_config",
"config_id": validated_config_id,
"config_id": str(config_id),
"load_result": "not_found",
"elapsed_ms": elapsed_ms,
"service": service_name,
},
)
raise ConfigurationError(
f"Configuration {validated_config_id} not found in database"
f"Configuration {config_id} not found in database"
)
memory_config, workspace = result
@@ -151,7 +126,7 @@ class MemoryConfigService:
# Step 2: Validate embedding model (returns both UUID and name)
embed_start = time.time()
embedding_uuid, embedding_name = validate_embedding_model(
validated_config_id,
config_id,
memory_config.embedding_id,
self.db,
workspace.tenant_id,
@@ -168,7 +143,7 @@ class MemoryConfigService:
self.db,
workspace.tenant_id,
required=True,
config_id=validated_config_id,
config_id=config_id,
workspace_id=workspace.id,
)
llm_time = time.time() - llm_start
@@ -185,7 +160,7 @@ class MemoryConfigService:
self.db,
workspace.tenant_id,
required=False,
config_id=validated_config_id,
config_id=config_id,
workspace_id=workspace.id,
)
rerank_time = time.time() - rerank_start
@@ -243,7 +218,7 @@ class MemoryConfigService:
extra={
"operation": "load_memory_config",
"service": service_name,
"config_id": validated_config_id,
"config_id": str(config_id),
"config_name": config.config_name,
"workspace_id": str(config.workspace_id),
"load_result": "success",

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

@@ -12,6 +12,7 @@
from typing import Optional, Dict, Any, Tuple
from datetime import datetime, timezone
from uuid import UUID
from sqlalchemy.orm import Session
@@ -87,7 +88,7 @@ class MemoryForgetService:
async def _get_forgetting_components(
self,
db: Session,
config_id: Optional[int] = None
config_id: Optional[UUID] = None
) -> Tuple[ACTRCalculator, ForgettingStrategy, ForgettingScheduler, Dict[str, Any]]:
"""
获取遗忘引擎组件（计算器、策略、调度器）
@@ -294,7 +295,7 @@ class MemoryForgetService:
end_user_id: str,
max_merge_batch_size: Optional[int] = None,
min_days_since_access: Optional[int] = None,
config_id: Optional[int] = None
config_id: Optional[UUID] = None
) -> Dict[str, Any]:
"""
手动触发遗忘周期
@@ -389,7 +390,7 @@ class MemoryForgetService:
def read_forgetting_config(
self,
db: Session,
config_id: int
config_id: UUID
) -> Dict[str, Any]:
"""
获取遗忘引擎配置
@@ -416,7 +417,7 @@ class MemoryForgetService:
def update_forgetting_config(
self,
db: Session,
config_id: int,
config_id: UUID,
update_fields: Dict[str, Any]
) -> Dict[str, Any]:
"""
@@ -466,7 +467,7 @@ class MemoryForgetService:
self,
db: Session,
end_user_id: Optional[str] = None,
config_id: Optional[int] = None
config_id: Optional[UUID] = None
) -> Dict[str, Any]:
"""
获取遗忘引擎统计信息
@@ -677,7 +678,7 @@ class MemoryForgetService:
db: Session,
importance_score: float,
days: int,
config_id: Optional[int] = None
config_id: Optional[UUID] = None
) -> Dict[str, Any]:
"""
获取遗忘曲线数据