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deep-agents-memory

deep-agents-memory

github.com/langchain-aiAgent workflows11955 installsUpdated 10w ago
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About deep-agents-memory

deep-agents-memory documents file-operation and memory backends for Deep Agents, for developers configuring temporary files, cross-session persistence, or local disk access. It supports combining backends and routing paths to different storage targets.

Key features

  1. 01Thread-scoped ephemeral file storage
  2. 02Cross-thread persistent storage
  3. 03Path-based backend composition
  4. 04File read, write, and search tools
  5. 05Local disk access with operation approval

Use cases

  1. 01Keep temporary work files within one thread
  2. 02Share persistent memory across threads
  3. 03Combine ephemeral and long-term file storage
  4. 04Restrict and approve file operations in local development

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/langchain-ai/skills-benchmarks --skill deep-agents-memory

After installing, type/deep-agents-memoryin Claude Code to confirm it loaded.

Details

From the project README
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 CaseBackendWhy
Temporary working filesStateBackendDefault, no setup
Local development CLIFilesystemBackendDirect disk access
Cross-session memoryStoreBackendPersists across threads
Hybrid storageCompositeBackendMix ephemeral + persistent
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
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)
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
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()
});

Security: Never use FilesystemBackend in web servers - use StateBackend or sandbox instead.

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())
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!
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! ``` 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) ``` 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) ``` Use PostgresStore for production (InMemoryStore lost on restart). ```python # WRONG # CORRECT store = InMemoryStore() store = PostgresStore(connection_string="postgresql://...") ``` Use PostgresStore for production (InMemoryStore lost on restart). ```typescript // WRONG // CORRECT const store = new InMemoryStore(); const store = new PostgresStore({ connectionString: "..." }); ``` Enable virtual_mode=True to restrict path access (prevents ../ and ~/ escapes). ```python backend = FilesystemBackend(root_dir="/project", virtual_mode=True) # Secure ``` 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) ```

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