docs/build/snippets/python/code-samples/customization-memory-filesystem-py.mdx

<CodeGroup>
    ```python Google
    from deepagents import create_deep_agent
    from deepagents.backends import FilesystemBackend
    from langgraph.checkpoint.memory import MemorySaver
    
    # Checkpointer is REQUIRED for human-in-the-loop
    checkpointer = MemorySaver()
    
    agent = create_deep_agent(
        model="google_genai:gemini-3.6-flash",
        backend=FilesystemBackend(root_dir="/Users/user/{project}"),
        memory=[
            "./AGENTS.md"
        ],
        interrupt_on={
            "write_file": True,  # Default: approve, edit, reject
            "read_file": False,  # No interrupts needed
            "edit_file": True,   # Default: approve, edit, reject
        },
        checkpointer=checkpointer,  # Required!
    )
    
    result = agent.invoke(
        {
            "messages": [
                {
                    "role": "user",
                    "content": "Please tell me what's in your memory files.",
                }
            ],
        },
        config={"configurable": {"thread_id": "12345"}},
    )
    ```

    ```python OpenAI
    from deepagents import create_deep_agent
    from deepagents.backends import FilesystemBackend
    from langgraph.checkpoint.memory import MemorySaver
    
    # Checkpointer is REQUIRED for human-in-the-loop
    checkpointer = MemorySaver()
    
    agent = create_deep_agent(
        model="openai:gpt-5.5",
        backend=FilesystemBackend(root_dir="/Users/user/{project}"),
        memory=[
            "./AGENTS.md"
        ],
        interrupt_on={
            "write_file": True,  # Default: approve, edit, reject
            "read_file": False,  # No interrupts needed
            "edit_file": True,   # Default: approve, edit, reject
        },
        checkpointer=checkpointer,  # Required!
    )
    
    result = agent.invoke(
        {
            "messages": [
                {
                    "role": "user",
                    "content": "Please tell me what's in your memory files.",
                }
            ],
        },
        config={"configurable": {"thread_id": "12345"}},
    )
    ```

    ```python Anthropic
    from deepagents import create_deep_agent
    from deepagents.backends import FilesystemBackend
    from langgraph.checkpoint.memory import MemorySaver
    
    # Checkpointer is REQUIRED for human-in-the-loop
    checkpointer = MemorySaver()
    
    agent = create_deep_agent(
        model="anthropic:claude-sonnet-4-6",
        backend=FilesystemBackend(root_dir="/Users/user/{project}"),
        memory=[
            "./AGENTS.md"
        ],
        interrupt_on={
            "write_file": True,  # Default: approve, edit, reject
            "read_file": False,  # No interrupts needed
            "edit_file": True,   # Default: approve, edit, reject
        },
        checkpointer=checkpointer,  # Required!
    )
    
    result = agent.invoke(
        {
            "messages": [
                {
                    "role": "user",
                    "content": "Please tell me what's in your memory files.",
                }
            ],
        },
        config={"configurable": {"thread_id": "12345"}},
    )
    ```

    ```python OpenRouter
    from deepagents import create_deep_agent
    from deepagents.backends import FilesystemBackend
    from langgraph.checkpoint.memory import MemorySaver
    
    # Checkpointer is REQUIRED for human-in-the-loop
    checkpointer = MemorySaver()
    
    agent = create_deep_agent(
        model="openrouter:z-ai/glm-5.2",
        backend=FilesystemBackend(root_dir="/Users/user/{project}"),
        memory=[
            "./AGENTS.md"
        ],
        interrupt_on={
            "write_file": True,  # Default: approve, edit, reject
            "read_file": False,  # No interrupts needed
            "edit_file": True,   # Default: approve, edit, reject
        },
        checkpointer=checkpointer,  # Required!
    )
    
    result = agent.invoke(
        {
            "messages": [
                {
                    "role": "user",
                    "content": "Please tell me what's in your memory files.",
                }
            ],
        },
        config={"configurable": {"thread_id": "12345"}},
    )
    ```

    ```python Fireworks
    from deepagents import create_deep_agent
    from deepagents.backends import FilesystemBackend
    from langgraph.checkpoint.memory import MemorySaver
    
    # Checkpointer is REQUIRED for human-in-the-loop
    checkpointer = MemorySaver()
    
    agent = create_deep_agent(
        model="fireworks:accounts/fireworks/models/glm-5p2",
        backend=FilesystemBackend(root_dir="/Users/user/{project}"),
        memory=[
            "./AGENTS.md"
        ],
        interrupt_on={
            "write_file": True,  # Default: approve, edit, reject
            "read_file": False,  # No interrupts needed
            "edit_file": True,   # Default: approve, edit, reject
        },
        checkpointer=checkpointer,  # Required!
    )
    
    result = agent.invoke(
        {
            "messages": [
                {
                    "role": "user",
                    "content": "Please tell me what's in your memory files.",
                }
            ],
        },
        config={"configurable": {"thread_id": "12345"}},
    )
    ```

    ```python Baseten
    from deepagents import create_deep_agent
    from deepagents.backends import FilesystemBackend
    from langgraph.checkpoint.memory import MemorySaver
    
    # Checkpointer is REQUIRED for human-in-the-loop
    checkpointer = MemorySaver()
    
    agent = create_deep_agent(
        model="baseten:zai-org/GLM-5.2",
        backend=FilesystemBackend(root_dir="/Users/user/{project}"),
        memory=[
            "./AGENTS.md"
        ],
        interrupt_on={
            "write_file": True,  # Default: approve, edit, reject
            "read_file": False,  # No interrupts needed
            "edit_file": True,   # Default: approve, edit, reject
        },
        checkpointer=checkpointer,  # Required!
    )
    
    result = agent.invoke(
        {
            "messages": [
                {
                    "role": "user",
                    "content": "Please tell me what's in your memory files.",
                }
            ],
        },
        config={"configurable": {"thread_id": "12345"}},
    )
    ```

    ```python Ollama
    from deepagents import create_deep_agent
    from deepagents.backends import FilesystemBackend
    from langgraph.checkpoint.memory import MemorySaver
    
    # Checkpointer is REQUIRED for human-in-the-loop
    checkpointer = MemorySaver()
    
    agent = create_deep_agent(
        model="ollama:north-mini-code-1.0",
        backend=FilesystemBackend(root_dir="/Users/user/{project}"),
        memory=[
            "./AGENTS.md"
        ],
        interrupt_on={
            "write_file": True,  # Default: approve, edit, reject
            "read_file": False,  # No interrupts needed
            "edit_file": True,   # Default: approve, edit, reject
        },
        checkpointer=checkpointer,  # Required!
    )
    
    result = agent.invoke(
        {
            "messages": [
                {
                    "role": "user",
                    "content": "Please tell me what's in your memory files.",
                }
            ],
        },
        config={"configurable": {"thread_id": "12345"}},
    )
    ```
</CodeGroup>