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fix(workflow): fix memory write behavior in RAG workspace

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This commit is contained in:
Eternity
2026-03-20 18:31:17 +08:00
parent dce7206c44
commit 31085ed678
7 changed files with 128 additions and 17 deletions
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14
api/app/core/workflow/engine/runtime_schema.py
View File

@@ -12,14 +12,26 @@ class ExecutionContext(BaseModel):
execution_id: str
workspace_id: str
user_id: str
memory_storage_type: str
user_rag_memory_id: str
checkpoint_config: RunnableConfig
@classmethod
def create(cls, execution_id: str, workspace_id: str, user_id: str):
def create(
cls,
execution_id: str,
workspace_id: str,
user_id: str,
memory_storage_type: str,
user_rag_memory_id: str
):
return cls(
execution_id=execution_id,
workspace_id=workspace_id,
user_id=user_id,
memory_storage_type=memory_storage_type,
user_rag_memory_id=user_rag_memory_id,
checkpoint_config=RunnableConfig(
configurable={
"thread_id": uuid.uuid4(),

9
api/app/core/workflow/engine/state_manager.py
View File

@@ -33,6 +33,8 @@ class WorkflowState(dict):
"workspace_id",
"user_id",
"activate",
"memory_storage_type",
"user_rag_memory_id"
})
__optional_keys__ = frozenset({
"error",
@@ -62,6 +64,9 @@ class WorkflowState(dict):
# node activate status
activate: Annotated[dict[str, bool], merge_activate_state]
memory_storage_type: str
user_rag_memory_id: str
class WorkflowStateManager:
def create_initial_state(
@@ -85,7 +90,9 @@ class WorkflowStateManager:
looping=0,
activate={
start_node_id: True
}
},
memory_storage_type=execution_context.memory_storage_type,
user_rag_memory_id=execution_context.user_rag_memory_id
)
@staticmethod

10
api/app/core/workflow/engine/variable_pool.py
View File

@@ -13,7 +13,7 @@ from pydantic import BaseModel
from app.core.workflow.engine.runtime_schema import ExecutionContext
from app.core.workflow.variable.base_variable import VariableType, DEFAULT_VALUE
from app.core.workflow.variable.variable_objects import T, create_variable_instance
from app.core.workflow.variable.variable_objects import T, create_variable_instance, ArrayVariable, FileVariable
logger = logging.getLogger(__name__)
@@ -373,6 +373,14 @@ class VariablePool:
def copy(self, pool: 'VariablePool'):
self.variables = deepcopy(pool.variables)
def is_file_variable(self, selector):
variable_struct = self._get_variable_struct(selector)
if isinstance(variable_struct, FileVariable):
return True
elif isinstance(variable_struct, ArrayVariable) and variable_struct.child_type == FileVariable:
return True
return False
def to_dict(self) -> dict[str, Any]:
"""导出为字典

20
api/app/core/workflow/executor.py
View File

@@ -409,7 +409,9 @@ async def execute_workflow(
input_data: dict[str, Any],
execution_id: str,
workspace_id: str,
user_id: str
user_id: str,
memory_storage_type: str,
user_rag_memory_id: str
) -> dict[str, Any]:
"""
Execute a workflow (convenience function, non-streaming).
@@ -420,6 +422,8 @@ async def execute_workflow(
execution_id (str): Execution ID.
workspace_id (str): Workspace ID.
user_id (str): User ID.
user_rag_memory_id: rag knowledge db id
memory_storage_type: neo4j / rag
Returns:
dict: Workflow execution result.
@@ -427,7 +431,9 @@ async def execute_workflow(
execution_context = ExecutionContext.create(
execution_id=execution_id,
workspace_id=workspace_id,
user_id=user_id
user_id=user_id,
memory_storage_type=memory_storage_type,
user_rag_memory_id=user_rag_memory_id
)
executor = WorkflowExecutor(
workflow_config=workflow_config,
@@ -441,7 +447,9 @@ async def execute_workflow_stream(
input_data: dict[str, Any],
execution_id: str,
workspace_id: str,
user_id: str
user_id: str,
memory_storage_type: str,
user_rag_memory_id: str
):
"""
Execute a workflow in streaming mode (convenience function).
@@ -452,6 +460,8 @@ async def execute_workflow_stream(
execution_id (str): Execution ID.
workspace_id (str): Workspace ID.
user_id (str): User ID.
user_rag_memory_id: rag knowledge db id
memory_storage_type: neo4j / rag
Yields:
dict: Streaming workflow events, e.g. node start, node end, chunk messages, workflow end.
@@ -459,7 +469,9 @@ async def execute_workflow_stream(
execution_context = ExecutionContext.create(
execution_id=execution_id,
workspace_id=workspace_id,
user_id=user_id
user_id=user_id,
memory_storage_type=memory_storage_type,
user_rag_memory_id=user_rag_memory_id
)
executor = WorkflowExecutor(
workflow_config=workflow_config,

61
api/app/core/workflow/nodes/memory/node.py
View File

@@ -1,3 +1,4 @@
import re
from typing import Any
from app.core.workflow.engine.state_manager import WorkflowState
@@ -5,7 +6,9 @@ from app.core.workflow.engine.variable_pool import VariablePool
from app.core.workflow.nodes.base_node import BaseNode
from app.core.workflow.nodes.memory.config import MemoryReadNodeConfig, MemoryWriteNodeConfig
from app.core.workflow.variable.base_variable import VariableType
from app.core.workflow.variable.variable_objects import FileVariable, ArrayVariable
from app.db import get_db_read
from app.schemas import FileInput
from app.services.memory_agent_service import MemoryAgentService
from app.tasks import write_message_task
@@ -36,8 +39,8 @@ class MemoryReadNode(BaseNode):
search_switch=self.typed_config.search_switch,
history=[],
db=db,
storage_type="neo4j",
user_rag_memory_id=""
storage_type=state["memory_storage_type"],
user_rag_memory_id=state["user_rag_memory_id"]
)
@@ -49,6 +52,19 @@ class MemoryWriteNode(BaseNode):
def _output_types(self) -> dict[str, VariableType]:
return {"output": VariableType.STRING}
@staticmethod
def _extract_multimodal_memory_variables(content: str, variable_pool: VariablePool) -> tuple[list[str], str]:
variable_pattern_string = r'\{\{\s*[a-zA-Z0-9_]+\.[a-zA-Z0-9_]+\s*\}\}'
variable_pattern = re.compile(variable_pattern_string)
variables = variable_pattern.findall(content)
file_variables = []
for variable in variables:
if variable_pool.is_file_variable(variable):
file_variables.append(variable)
for var in file_variables:
content = content.replace(var, "")
return file_variables, content
async def execute(self, state: WorkflowState, variable_pool: VariablePool) -> Any:
self.typed_config = MemoryWriteNodeConfig(**self.config)
end_user_id = self.get_variable("sys.user_id", variable_pool)
@@ -56,6 +72,7 @@ class MemoryWriteNode(BaseNode):
if not end_user_id:
raise RuntimeError("End user id is required")
messages = []
multimodal_memories = []
if self.typed_config.message:
messages.append({
"role": "user",
@@ -63,17 +80,45 @@ class MemoryWriteNode(BaseNode):
})
for message in self.typed_config.messages:
file_variables, content = self._extract_multimodal_memory_variables(
message.content,
variable_pool
)
file_info = []
for var in file_variables:
instence: FileVariable | ArrayVariable[FileVariable] = variable_pool.get_instance(var)
if isinstance(instence, FileVariable):
file_info.append(FileInput(
type=instence.value.type,
transfer_method=instence.value.transfer_method,
upload_file_id=instence.value.file_id,
url=instence.value.url,
file_type=instence.value.origin_file_type
).model_dump())
elif isinstance(instence, ArrayVariable) and instence.child_type == FileVariable:
for file_instence in instence.value:
file_info.append(FileInput(
type=file_instence.value.type,
transfer_method=file_instence.value.transfer_method,
upload_file_id=file_instence.value.file_id,
url=file_instence.value.url,
file_type=file_instence.value.origin_file_type
).model_dump())
multimodal_memories.append({
"role": message.role,
"files": file_info
})
messages.append({
"role": message.role,
"content": self._render_template(message.content, variable_pool)
"content": self._render_template(content, variable_pool)
})
write_message_task.delay(
end_user_id,
messages,
str(self.typed_config.config_id),
"neo4j",
""
end_user_id=end_user_id,
message=messages,
config_id=str(self.typed_config.config_id),
storage_type=state["memory_storage_type"],
user_rag_memory_id=state["user_rag_memory_id"]
)
return "success"