| name | deep-agents-memory |
| description | INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing. |
Deep Agents use pluggable backends for file operations and memory:
Short-term (StateBackend): Persists within a single thread, lost when thread ends
Long-term (StoreBackend): Persists across threads and sessions
Hybrid (CompositeBackend): Route different paths to different backends
FilesystemMiddleware provides tools: ls, read_file, write_file, edit_file, glob, grep
| Use Case | Backend | Why |
|---|
| Temporary working files | StateBackend | Default, no setup |
| Local development CLI | FilesystemBackend | Direct disk access |
| Cross-session memory | StoreBackend | Persists across threads |
| Hybrid storage | CompositeBackend | Mix ephemeral + persistent |
Default StateBackend stores files ephemerally within a thread.
from deepagents import create_deep_agent
agent = create_deep_agent()
result = agent.invoke({
"messages": [{"role": "user", "content": "Write notes to /draft.txt"}]
}, config={"configurable": {"thread_id": "thread-1"}})
Default StateBackend stores files ephemerally within a thread.
import { createDeepAgent } from "deepagents";
const agent = await createDeepAgent();
const result = await agent.invoke({
messages: [{ role: "user", content: "Write notes to /draft.txt" }]
}, { configurable: { thread_id: "thread-1" } });
Configure CompositeBackend to route paths to different storage backends.
from deepagents import create_deep_agent
from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
from langgraph.store.memory import InMemoryStore
store = InMemoryStore()
composite_backend = lambda rt: CompositeBackend(
default=StateBackend(rt),
routes={"/memories/": StoreBackend(rt)}
)
agent = create_deep_agent(backend=composite_backend, store=store)
Configure CompositeBackend to route paths to different storage backends.
import { createDeepAgent, CompositeBackend, StateBackend, StoreBackend } from "deepagents";
import { InMemoryStore } from "@langchain/langgraph";
const store = new InMemoryStore();
const agent = await createDeepAgent({
backend: (config) => new CompositeBackend(
new StateBackend(config),
{ "/memories/": new StoreBackend(config) }
),
store
});
Files in /memories/ persist across threads via StoreBackend routing.
config1 = {"configurable": {"thread_id": "thread-1"}}
agent.invoke({"messages": [{"role": "user", "content": "Save to /memories/style.txt"}]}, config=config1)
config2 = {"configurable": {"thread_id": "thread-2"}}
agent.invoke({"messages": [{"role": "user", "content": "Read /memories/style.txt"}]}, config=config2)
Files in /memories/ persist across threads via StoreBackend routing.
const config1 = { configurable: { thread_id: "thread-1" } };
await agent.invoke({ messages: [{ role: "user", content: "Save to /memories/style.txt" }] }, config1);
const config2 = { configurable: { thread_id: "thread-2" } };
await agent.invoke({ messages: [{ role: "user", content: "Read /memories/style.txt" }] }, config2);
Use FilesystemBackend for local development with real disk access and human-in-the-loop.
from deepagents import create_deep_agent
from deepagents.backends import FilesystemBackend
from langgraph.checkpoint.memory import MemorySaver
agent = create_deep_agent(
backend=FilesystemBackend(root_dir=".", virtual_mode=True),
interrupt_on={"write_file": True, "edit_file": True},
checkpointer=MemorySaver()
)
Use FilesystemBackend for local development with real disk access and human-in-the-loop.
import { createDeepAgent, FilesystemBackend } from "deepagents";
import { MemorySaver } from "@langchain/langgraph";
const agent = await createDeepAgent({
backend: new FilesystemBackend({ rootDir: ".", virtualMode: true }),
interruptOn: { write_file: true, edit_file: true },
checkpointer: new MemorySaver()
});
Security: Never use FilesystemBackend in web servers - use StateBackend or sandbox instead.
Access the store directly in custom tools for long-term memory operations.
from langchain.tools import tool, ToolRuntime
from langchain.agents import create_agent
from langgraph.store.memory import InMemoryStore
@tool
def get_user_preference(key: str, runtime: ToolRuntime) -> str:
"""Get a user preference from long-term storage."""
store = runtime.store
result = store.get(("user_prefs",), key)
return str(result.value) if result else "Not found"
@tool
def save_user_preference(key: str, value: str, runtime: ToolRuntime) -> str:
"""Save a user preference to long-term storage."""
store = runtime.store
store.put(("user_prefs",), key, {"value": value})
return f"Saved {key}={value}"
store = InMemoryStore()
agent = create_agent(
model="gpt-4.1",
tools=[get_user_preference, save_user_preference],
store=store
)
### What Agents CAN Configure
- Backend type and configuration
- Routing rules for CompositeBackend
- Root directory for FilesystemBackend
- Human-in-the-loop for file operations
What Agents CANNOT Configure
- Tool names (ls, read_file, write_file, edit_file, glob, grep)
- Access files outside virtual_mode restrictions
- Cross-thread file access without proper backend setup
StoreBackend requires a store instance.
agent = create_deep_agent(backend=lambda rt: StoreBackend(rt))
agent = create_deep_agent(backend=lambda rt: StoreBackend(rt), store=InMemoryStore())
StoreBackend requires a store instance.
const agent = await createDeepAgent({ backend: (c) => new StoreBackend(c) });
const agent = await createDeepAgent({ backend: (c) => new StoreBackend(c), store: new InMemoryStore() });
StateBackend files are thread-scoped - use same thread_id or StoreBackend for cross-thread access.
agent.invoke({"messages": [...]}, config={"configurable": {"thread_id": "thread-1"}})
agent.invoke({"messages": [...]}, config={"configurable": {"thread_id": "thread-2"}})
StateBackend files are thread-scoped - use same thread_id or StoreBackend for cross-thread access.
await agent.invoke({ messages: [...] }, { configurable: { thread_id: "thread-1" } });
await agent.invoke({ messages: [...] }, { configurable: { thread_id: "thread-2" } });
Path must match CompositeBackend route prefix for persistence.
agent.invoke(...)
agent.invoke(...)
Path must match CompositeBackend route prefix for persistence.
await agent.invoke(...);
await agent.invoke(...);
Use PostgresStore for production (InMemoryStore lost on restart).
store = InMemoryStore() store = PostgresStore(connection_string="postgresql://...")
Use PostgresStore for production (InMemoryStore lost on restart).
const store = new InMemoryStore(); const store = new PostgresStore({ connectionString: "..." });
Enable virtual_mode=True to restrict path access (prevents ../ and ~/ escapes).
backend = FilesystemBackend(root_dir="/project", virtual_mode=True)
CompositeBackend matches longest prefix first.
routes = {"/mem/": StoreBackend(rt), "/mem/temp/": StateBackend(rt)}