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deep-agents-memory

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npx machina-cli add skill langchain-ai/langchain-skills/deep-agents-memory --openclaw
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<overview> 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 </overview>

<backend-selection>
Use CaseBackendWhy
Temporary working filesStateBackendDefault, no setup
Local development CLIFilesystemBackendDirect disk access
Cross-session memoryStoreBackendPersists across threads
Hybrid storageCompositeBackendMix ephemeral + persistent
</backend-selection> <ex-default-state-backend> <python> Default StateBackend stores files ephemerally within a thread. ```python from deepagents import create_deep_agent

agent = create_deep_agent() # Default: StateBackend result = agent.invoke({ "messages": [{"role": "user", "content": "Write notes to /draft.txt"}] }, config={"configurable": {"thread_id": "thread-1"}})

/draft.txt is lost when thread ends

</python>
<typescript>
Default StateBackend stores files ephemerally within a thread.
```typescript
import { createDeepAgent } from "deepagents";

const agent = await createDeepAgent();  // Default: StateBackend
const result = await agent.invoke({
  messages: [{ role: "user", content: "Write notes to /draft.txt" }]
}, { configurable: { thread_id: "thread-1" } });
// /draft.txt is lost when thread ends
</typescript> </ex-default-state-backend> <ex-composite-backend-for-hybrid> <python> Configure CompositeBackend to route paths to different storage backends. ```python 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)

/draft.txt -> ephemeral (StateBackend)

/memories/user-prefs.txt -> persistent (StoreBackend)

</python>
<typescript>
Configure CompositeBackend to route paths to different storage backends.
```typescript
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
});

// /draft.txt -> ephemeral (StateBackend)
// /memories/user-prefs.txt -> persistent (StoreBackend)
</typescript> </ex-composite-backend-for-hybrid> <ex-cross-session-memory> <python> Files in /memories/ persist across threads via StoreBackend routing. ```python # Using CompositeBackend from previous example 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)

Thread 2 can read file saved by Thread 1

</python>
<typescript>
Files in /memories/ persist across threads via StoreBackend routing.
```typescript
// Using CompositeBackend from previous example
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);
// Thread 2 can read file saved by Thread 1
</typescript> </ex-cross-session-memory> <ex-filesystem-backend-local-dev> <python> Use FilesystemBackend for local development with real disk access and human-in-the-loop. ```python 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), # Restrict access interrupt_on={"write_file": True, "edit_file": True}, checkpointer=MemorySaver() )

Agent can read/write actual files on disk

</python>
<typescript>
Use FilesystemBackend for local development with real disk access and human-in-the-loop.
```typescript
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()
});
</typescript>

Security: Never use FilesystemBackend in web servers - use StateBackend or sandbox instead. </ex-filesystem-backend-local-dev>

<ex-store-in-custom-tools> <python> Access the store directly in custom tools for long-term memory operations. ```python 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 )

</python>
</ex-store-in-custom-tools>

<boundaries>
### 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
</boundaries>

<fix-storebackend-requires-store>
<python>
StoreBackend requires a store instance.
```python
# WRONG
agent = create_deep_agent(backend=lambda rt: StoreBackend(rt))

# CORRECT
agent = create_deep_agent(backend=lambda rt: StoreBackend(rt), store=InMemoryStore())
</python> <typescript> StoreBackend requires a store instance. ```typescript // WRONG const agent = await createDeepAgent({ backend: (c) => new StoreBackend(c) });

// CORRECT const agent = await createDeepAgent({ backend: (c) => new StoreBackend(c), store: new InMemoryStore() });

</typescript>
</fix-storebackend-requires-store>

<fix-statebackend-files-dont-persist>
<python>
StateBackend files are thread-scoped - use same thread_id or StoreBackend for cross-thread access.
```python
# WRONG: thread-2 can't read file from thread-1
agent.invoke({"messages": [...]}, config={"configurable": {"thread_id": "thread-1"}})  # Write
agent.invoke({"messages": [...]}, config={"configurable": {"thread_id": "thread-2"}})  # File not found!
</python> <typescript> StateBackend files are thread-scoped - use same thread_id or StoreBackend for cross-thread access. ```typescript // WRONG: thread-2 can't read file from thread-1 await agent.invoke({ messages: [...] }, { configurable: { thread_id: "thread-1" } }); // Write await agent.invoke({ messages: [...] }, { configurable: { thread_id: "thread-2" } }); // File not found! ``` </typescript> </fix-statebackend-files-dont-persist> <fix-path-prefix-for-persistence> <python> Path must match CompositeBackend route prefix for persistence. ```python # With routes={"/memories/": StoreBackend(rt)}: agent.invoke(...) # /prefs.txt -> ephemeral (no match) agent.invoke(...) # /memories/prefs.txt -> persistent (matches route) ``` </python> <typescript> Path must match CompositeBackend route prefix for persistence. ```typescript // With routes: { "/memories/": StoreBackend }: await agent.invoke(...); // /prefs.txt -> ephemeral (no match) await agent.invoke(...); // /memories/prefs.txt -> persistent (matches route) ``` </typescript> </fix-path-prefix-for-persistence> <fix-production-store> <python> Use PostgresStore for production (InMemoryStore lost on restart). ```python # WRONG # CORRECT store = InMemoryStore() store = PostgresStore(connection_string="postgresql://...") ``` </python> <typescript> Use PostgresStore for production (InMemoryStore lost on restart). ```typescript // WRONG // CORRECT const store = new InMemoryStore(); const store = new PostgresStore({ connectionString: "..." }); ``` </typescript> </fix-production-store> <fix-filesystem-backend-needs-virtual-mode> <python> Enable virtual_mode=True to restrict path access (prevents ../ and ~/ escapes). ```python backend = FilesystemBackend(root_dir="/project", virtual_mode=True) # Secure ``` </python> </fix-filesystem-backend-needs-virtual-mode> <fix-longest-prefix-match> <python> CompositeBackend matches longest prefix first. ```python routes = {"/mem/": StoreBackend(rt), "/mem/temp/": StateBackend(rt)} # /mem/file.txt -> StoreBackend, /mem/temp/file.txt -> StateBackend (longer match) ``` </python> </fix-longest-prefix-match>

Source

git clone https://github.com/langchain-ai/langchain-skills/blob/main/config/skills/deep-agents-memory/SKILL.mdView on GitHub

Overview

Deep Agents support pluggable backends for memory and file I/O. StateBackend stores ephemeral data within a thread, StoreBackend provides persistence across threads and sessions, and CompositeBackend routes paths to the appropriate backend. The FilesystemMiddleware exposes utilities like ls, read_file, write_file, edit_file, glob, and grep to interact with these backends.

How This Skill Works

Backends implement storage for the agent's file operations. StateBackend keeps data ephemeral to a thread, while StoreBackend persists data across threads and sessions. A CompositeBackend can route specific path prefixes to different backends, enabling hybrid storage. FilesystemMiddleware provides practical file tools to operate on these backends.

When to Use It

  • Temporary working files during a single run (ephemeral StateBackend)
  • Local development CLI or disk-backed access via a filesystem-like backend
  • Cross-session memory needs where data persists across threads (StoreBackend)
  • Hybrid storage with selective persistence via CompositeBackend routing
  • Persisting user data, logs, or configurations across restarts

Quick Start

  1. Step 1: Create a Deep Agent with the default StateBackend (ephemeral)
  2. Step 2: If persistence is needed, configure CompositeBackend with StoreBackend for selective paths
  3. Step 3: Use agent.invoke and FilesystemMiddleware (ls, read_file, write_file) to interact with files

Best Practices

  • Choose StateBackend for short-lived data and avoid unnecessary persistence
  • Use StoreBackend for data you want to survive across threads/sessions
  • Leverage CompositeBackend to route /memories/ to persistent storage while keeping other paths ephemeral
  • Organize persistent paths under a dedicated folder (e.g., /memories/) for clarity
  • Test route mappings and thread isolation to prevent unintended persistence

Example Use Cases

  • Python: Write notes to /draft.txt using the default ephemeral StateBackend (lost when the thread ends)
  • Python: Save and read /memories/style.txt across threads with StoreBackend persistence
  • Python: Configure CompositeBackend so /draft.txt uses StateBackend while /memories/ uses StoreBackend
  • Using FilesystemMiddleware to ls and read_file on /draft.txt to inspect content
  • Cross-thread memory: thread-1 saves to /memories/style.txt; thread-2 reads it

Frequently Asked Questions

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