refactor(memory): move memory tools to dedicated module and update imports

reme_ai/constants/common_constants.py

@@ -1,4 +1,4 @@
-"""Common constants module.
+"""Common constants' module.
 
 This module defines constants used as keys throughout the application to maintain
 a consistent reference for data structures related to workflow management, chat

reme_ai/core/op/base_ray_op.py

@@ -57,7 +57,7 @@ class BaseRayOp(BaseOp, metaclass=ABCMeta):
             for k, v in kwargs.items()
         }
 
-        # Submit sliced chunks to reduce inter-node data transfer
+        # Submit sliced chunks to reduce internode data transfer
         remote_task_loop = ray.remote(self._ray_task_loop)
         for i in range(max_workers):
             chunk = parallel_list[i::max_workers]

reme_ai/core/schema/message.py

@@ -2,7 +2,6 @@
 
 import datetime
 import json
-from typing import Any
 
 from pydantic import BaseModel, ConfigDict, Field, model_validator
 
@@ -44,14 +43,14 @@ class ContentBlock(BaseModel):
 
     @model_validator(mode="before")
     @classmethod
-    def init_block(cls, data: dict[str, Any]) -> dict[str, Any]:
+    def init_block(cls, data: dict) -> dict:
         """Dynamically maps the type-specific key to the content field."""
         content_type = data.get("type", "")
         if content_type and content_type in data:
             data["content"] = data[content_type]
         return data
 
-    def simple_dump(self) -> dict[str, Any]:
+    def simple_dump(self) -> dict:
         """Serializes the block into an API-compatible dictionary format."""
         return {
             "type": self.type,
@@ -69,28 +68,45 @@ class Message(BaseModel):
     reasoning_content: str = Field(default="")
     tool_calls: list[ToolCall] = Field(default_factory=list)
     tool_call_id: str = Field(default="")
-    time_created: str = Field(
-        default_factory=lambda: datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
-    )
-    metadata: dict[str, Any] = Field(default_factory=dict)
+    time_created: str = Field(default_factory=lambda: datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
+    metadata: dict = Field(default_factory=dict)
 
-    def dump_content(self) -> str | list[dict[str, Any]]:
+    def dump_content(self) -> str | list[dict]:
         """Returns content as a raw string or a list of serialized blocks."""
         if isinstance(self.content, str):
             return self.content
         return [block.simple_dump() for block in self.content]
 
-    def simple_dump(self, add_reasoning: bool = True) -> dict[str, Any]:
+    def simple_dump(
+        self,
+        add_name: bool = False,
+        add_reasoning: bool = True,
+        add_time_created: bool = False,
+        add_metadata: bool = False,
+    ) -> dict:
         """Transforms the message into a simplified dictionary for standard APIs."""
-        result = {"role": self.role.value, "content": self.dump_content()}
+        result = {}
+        if add_name and self.name:
+            result["name"] = self.name
+
+        result["role"] = self.role.value
+        result["content"] = self.dump_content()
 
         if add_reasoning and self.reasoning_content:
             result["reasoning_content"] = self.reasoning_content
+
         if self.tool_calls:
             result["tool_calls"] = [tc.simple_output_dump() for tc in self.tool_calls]
+
         if self.tool_call_id:
             result["tool_call_id"] = self.tool_call_id
 
+        if add_time_created:
+            result["time_created"] = self.time_created
+
+        if add_metadata:
+            result["metadata"] = self.metadata
+
         return result
 
     def format_message(
@@ -133,4 +149,4 @@ class Trajectory(BaseModel):
     task_id: str = Field(default="")
     messages: list[Message] = Field(default_factory=list)
     score: float = Field(default=0.0)
-    metadata: dict[str, Any] = Field(default_factory=dict)
+    metadata: dict = Field(default_factory=dict)

reme_ai/core/service/mcp_service.py

@@ -34,8 +34,8 @@ class MCPService(BaseService):
 
         self.mcp.add_tool(
             FunctionTool(
-                name=tool_call.name,
-                description=tool_call.description,
+                name=tool_call.name,  # noqa
+                description=tool_call.description,  # noqa
                 fn=execute_tool,
                 parameters=tool_call.parameters.simple_input_dump(),
             ),

reme_ai/core/utils/mcp_client.py

@@ -8,7 +8,7 @@ from typing import Any
 from mcp import ClientSession, StdioServerParameters, Tool
 from mcp.client.sse import sse_client
 from mcp.client.stdio import stdio_client
-from mcp.client.streamable_http import streamablehttp_client
+from mcp.client.streamable_http import streamable_http_client
 from mcp.types import CallToolResult, TextContent
 
 from ..schema import ToolCall
@@ -64,7 +64,7 @@ class MCPClient:
                 async with sse_client(**cfg) as transport:
                     yield transport
             elif t_type == "streamable-http":
-                async with streamablehttp_client(**cfg) as transport:
+                async with streamable_http_client(**cfg) as transport:
                     yield transport
             else:
                 raise NotImplementedError(f"Unsupported transport: {t_type}")

reme_ai/mem_agent/base_memory_agent.py

@@ -8,7 +8,7 @@ from loguru import logger
 from ..core.enumeration import Role, MemoryType
 from ..core.op import BaseOp
 from ..core.schema import Message, ToolCall
-from ..tool.memory import BaseMemoryTool, ThinkTool
+from ..mem_tool import BaseMemoryTool, ThinkTool
 
 
 class BaseMemoryAgent(BaseOp, metaclass=ABCMeta):
@@ -141,35 +141,26 @@ class BaseMemoryAgent(BaseOp, metaclass=ABCMeta):
 
     async def react(self, messages: list[Message]):
         """Performs reasoning and acting steps until completion or max steps reached."""
-        success: bool = False
         for step in range(self.max_steps):
             assistant_message, should_act = await self._reasoning_step(messages, step)
 
             if not should_act:
-                success = True
                 break
 
             tool_result_messages = await self._acting_step(assistant_message, step)
             messages.extend(tool_result_messages)
 
-        return messages, success
+        return messages
 
     async def execute(self):
         messages = await self.build_messages()
         for i, message in enumerate(messages):
             logger.info(f"step0.{i} {message.role} {message.name or ''} {message.simple_dump()}")
 
-        messages, success = await self.react(messages)
-        if messages:
-            if success:
-                self.output = messages[-1].content
-            else:
-                self.output = f"react is not complete with content:\n{messages[-1].content}"
-        else:
-            self.output = "empty messages"
-
-        self.context.response.metadata["messages"] = messages
-        self.context.response.metadata["success"] = success
+        messages = await self.react(messages)
+        self.output = [
+            m.simple_dump(add_name=True, add_reasoning=True, add_time_created=True, add_metadata=True) for m in messages
+        ]
 
     @property
     def memory_target(self) -> str:

reme_ai/mem_tool/base_memory_tool.py

@@ -3,10 +3,10 @@
 from abc import ABCMeta
 from pathlib import Path
 
-from ...core.enumeration import MemoryType
-from ...core.op import BaseOp
-from ...core.schema import ToolCall, MemoryNode
-from ...core.utils import CacheHandler
+from ..core.enumeration import MemoryType
+from ..core.op import BaseOp
+from ..core.schema import ToolCall, MemoryNode
+from ..core.utils import CacheHandler
 
 
 class BaseMemoryTool(BaseOp, metaclass=ABCMeta):

reme_ai/mem_tool/history/add_history_memory.py

@@ -3,10 +3,10 @@
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
-from ....core.enumeration import MemoryType
-from ....core.schema import ToolCall, Message
-from ....core.utils import format_messages
+from ...core.context import C
+from ...core.enumeration import MemoryType
+from ...core.schema import ToolCall, Message
+from ...core.utils import format_messages
 
 
 @C.register_op()

reme_ai/mem_tool/history/read_history_memory.py

@@ -3,8 +3,8 @@
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
-from ....core.schema import MemoryNode
+from ...core.context import C
+from ...core.schema import MemoryNode
 
 
 @C.register_op()

reme_ai/mem_tool/identity/read_identity_memory.py

@@ -3,7 +3,7 @@
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
+from ...core.context import C
 
 
 @C.register_op()

reme_ai/mem_tool/identity/update_identity_memory.py

@@ -3,7 +3,7 @@
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
+from ...core.context import C
 
 
 @C.register_op()

reme_ai/mem_tool/meta/add_meta_memory.py

@@ -5,8 +5,8 @@ import json
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
-from ....core.enumeration import MemoryType
+from ...core.context import C
+from ...core.enumeration import MemoryType
 
 
 @C.register_op()

reme_ai/mem_tool/meta/read_meta_memory.py

@@ -3,8 +3,8 @@
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
-from ....core.enumeration import MemoryType
+from ...core.context import C
+from ...core.enumeration import MemoryType
 
 
 @C.register_op()

reme_ai/mem_tool/think_tool.py

@@ -5,8 +5,8 @@ before taking actions, helping agents reason about their next steps.
 """
 
 from .base_memory_tool import BaseMemoryTool
-from ...core.context import C
-from ...core.schema import ToolCall
+from ..core.context import C
+from ..core.schema import ToolCall
 
 
 @C.register_op()

reme_ai/mem_tool/vector/add_memory.py

@@ -3,8 +3,8 @@
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
-from ....core.schema import MemoryNode
+from ...core.context import C
+from ...core.schema import MemoryNode
 
 
 @C.register_op()

reme_ai/mem_tool/vector/add_summary_memory.py

@@ -3,7 +3,7 @@
 from loguru import logger
 
 from .add_memory import AddMemory
-from ....core.context import C
+from ...core.context import C
 
 
 @C.register_op()

reme_ai/mem_tool/vector/delete_memory.py

@@ -3,7 +3,7 @@
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
+from ...core.context import C
 
 
 @C.register_op()

reme_ai/mem_tool/vector/update_memory.py

@@ -3,8 +3,8 @@
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
-from ....core.schema import MemoryNode
+from ...core.context import C
+from ...core.schema import MemoryNode
 
 
 @C.register_op()

reme_ai/mem_tool/vector/vector_retrieve_memory.py

@@ -3,10 +3,10 @@
 from loguru import logger
 
 from ..base_memory_tool import BaseMemoryTool
-from ....core.context import C
-from ....core.enumeration import MemoryType
-from ....core.schema import MemoryNode, VectorNode
-from ....core.utils import deduplicate_memories
+from ...core.context import C
+from ...core.enumeration import MemoryType
+from ...core.schema import MemoryNode, VectorNode
+from ...core.utils import deduplicate_memories
 
 
 @C.register_op()

reme_ai/tool/__init__.py

@@ -1,11 +1,9 @@
 """tool"""
 
 from . import execute
-from . import memory
 from . import search
 
 __all__ = [
     "execute",
-    "memory",
     "search",
 ]