Deep Agents Memory
LangChainOfficialPublished by LangChain
- Skill
- Tool integration
- Agent tooling
- MIT
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
Deep Agents memory provides a flexible system for managing agent state and file access through pluggable backends. It supports ephemeral storage for single-thread tasks, persistent storage for cross-session memory, and direct filesystem access for local development. By using a CompositeBackend, developers can route specific file paths to different storage types, enabling hybrid memory architectures within a single agent.
What it does
- Provides StateBackend for thread-scoped ephemeral file storage.
- Enables StoreBackend for persistent, cross-session memory.
- Supports FilesystemBackend for direct disk access during local development.
- Allows routing of different file paths to specific backends via CompositeBackend.
- Includes standard file operation tools like read, write, edit, and grep.
- Supports secure local development with virtualized path restrictions and human-in-the-loop interrupts.
When to use it
- When an agent needs to maintain state across multiple conversation threads.
- When you need to separate temporary working files from long-term user preferences.
- When building local CLI tools that require reading or writing to the host filesystem.
- When you need to implement custom memory logic using a persistent store.
Advantages
- Highly configurable storage architecture.
- Prevents accidental data loss by choosing the appropriate persistence layer.
- Enhances security for local development through virtualized path modes.
- Seamless integration with existing agent workflows and toolsets.
Usage examples
- “Configure my agent to save files in /memories/ to a persistent store while keeping other files ephemeral.”
- The agent is initialized with a CompositeBackend that routes /memories/ paths to a StoreBackend, ensuring persistence across threads.
- “How do I safely allow my agent to edit local files during development?”
- The agent is configured with a FilesystemBackend in virtual_mode=True, with interrupts enabled for write and edit operations to ensure human oversight.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/langchain-ai/deep-agents-memory/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip deep-agents-memory.zip -d .agents/skills
Documentation by LangChain
<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 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 |
</backend-selection>
<ex-default-state-backend> <python> Default StateBackend stores files ephemerally within a thread.
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.
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.
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.
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.
# 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.
// 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.
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.
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.
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.
# 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.
// 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.
# 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.
// 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.
# 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.
// 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).
# WRONG # CORRECT
store = InMemoryStore() store = PostgresStore(connection_string="postgresql://...")</python> <typescript> Use PostgresStore for production (InMemoryStore lost on restart).
// 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).
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.
routes = {"/mem/": StoreBackend(rt), "/mem/temp/": StateBackend(rt)}
# /mem/file.txt -> StoreBackend, /mem/temp/file.txt -> StateBackend (longer match)</python> </fix-longest-prefix-match>
Files
- ATTRIBUTION.mdAdded by AutoGineer898 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md9.7 KiB
LICENSE
MIT License Copyright (c) LangChain, Inc. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Python
Security
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Attribution and licence
- Published by
- LangChain
- Publisher
- LangChain (Official)
- Source
- langchain-ai/langchain-skills · config/skills/deep-agents-memory · commit 126c384
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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