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beaver_project/app-instance/backend/beaver/tools/builtins/memory.py

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"""Beaver 内置 memory tool。
这个文件的职责很单纯:把 `MemoryStore` 暴露成一个 agent runtime 可以调用的统一工具。
设计边界:
1. `store.py` 负责底层数据与并发安全
2. 本文件负责工具接口、参数校验分发、JSON 响应
3. 更高层的 engine / loader 之后再决定如何把这个工具注册进 runtime
换句话说本文件是“memory 能力的工具化外壳”,不是记忆实现本身。
"""
from __future__ import annotations
import json
from dataclasses import dataclass, field
from typing import Any
from beaver.memory.curated.store import MemoryStore
MEMORY_TOOL_DESCRIPTION = (
"Save durable information to persistent memory that survives across sessions. "
"Use this proactively for user corrections, preferences, environment facts, "
"project conventions, and stable tool quirks. Do not store temporary task "
"progress or raw session logs here; use session search for historical detail."
)
MEMORY_TOOL_PARAMETERS: dict[str, Any] = {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": ["add", "replace", "remove"],
"description": "The memory operation to perform.",
},
"target": {
"type": "string",
"enum": ["memory", "user"],
"description": "Which curated store to update.",
},
"content": {
"type": "string",
"description": "The new entry content. Required for add and replace.",
},
"old_text": {
"type": "string",
"description": "A short unique substring identifying the entry to replace or remove.",
},
},
"required": ["action", "target"],
}
def memory_tool(
*,
action: str,
target: str = "memory",
content: str | None = None,
old_text: str | None = None,
store: MemoryStore | None = None,
) -> str:
"""分发 Hermes 风格的 CRUD memory API并返回 JSON 字符串。
这里统一采用 JSON 返回,是为了兼容常见 tool-calling 场景:
- LLM 更容易消费结构化结果
- Web/API/日志层也更容易透传和记录
"""
if store is None:
return json.dumps(
{
"success": False,
"error": "Memory store is not available for this runtime.",
},
ensure_ascii=False,
)
if target not in {"memory", "user"}:
return json.dumps(
{
"success": False,
"error": f"Invalid target '{target}'. Use 'memory' or 'user'.",
},
ensure_ascii=False,
)
if action == "add":
if not content:
result = {"success": False, "error": "content is required for add."}
else:
result = store.add(target, content)
elif action == "replace":
if not old_text:
result = {"success": False, "error": "old_text is required for replace."}
elif not content:
result = {"success": False, "error": "content is required for replace."}
else:
result = store.replace(target, old_text, content)
elif action == "remove":
if not old_text:
result = {"success": False, "error": "old_text is required for remove."}
else:
result = store.remove(target, old_text)
else:
result = {
"success": False,
"error": f"Unknown action '{action}'. Use add, replace, or remove.",
}
return json.dumps(result, ensure_ascii=False)
@dataclass(slots=True)
class MemoryTool:
"""面向 runtime 的轻量工具封装。
这里故意保持很薄:
1. 不重复实现业务逻辑
2. 不重复维护 schema
3. 只做 `execute()` 到 `memory_tool()` 的桥接
"""
store: MemoryStore
name: str = "memory"
description: str = MEMORY_TOOL_DESCRIPTION
parameters: dict[str, Any] = field(default_factory=lambda: dict(MEMORY_TOOL_PARAMETERS))
async def execute(self, **kwargs: Any) -> str:
return memory_tool(store=self.store, **kwargs)