headroomlabs-ai/headroom · error · AttributeError

module {__name__!r} has no attribute {name!r}

Error message

module {__name__!r} has no attribute {name!r}

What it means

headroom.memory implements lazy submodule loading via a module-level __getattr__: names like DirectMem0Adapter and DirectMem0Config are imported from headroom.memory.backends.direct_mem0 only on first access. This AttributeError is the fallback branch meaning the requested name is neither eagerly exported nor one of the known lazily-imported optional symbols — i.e. a typo or a symbol that lives elsewhere.

Source

Thrown at headroom/memory/__init__.py:190

            _Mem0Config = Mem0Config
        return _Mem0Config

    if name == "DirectMem0Adapter":
        if _DirectMem0Adapter is None:
            from headroom.memory.backends.direct_mem0 import DirectMem0Adapter

            _DirectMem0Adapter = DirectMem0Adapter
        return _DirectMem0Adapter

    if name == "DirectMem0Config":
        if _DirectMem0Config is None:
            from headroom.memory.backends.direct_mem0 import Mem0Config as DirectMem0Config

            _DirectMem0Config = DirectMem0Config
        return _DirectMem0Config

    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")


__all__ = [
    # =========================================================================
    # Simple API (recommended for most users)
    # =========================================================================
    "Memory",  # Zero-config memory class
    "MemoryResult",  # Search result dataclass
    # =========================================================================
    # LLM Wrapper API
    # =========================================================================
    "with_memory",
    "MemoryWrapper",
    # Tool-based wrapper
    "with_memory_tools",
    "MemoryToolsWrapper",
    # =========================================================================
    # Core orchestrator

View on GitHub (pinned to 322425c43b)

Solutions

1. Check the module's __all__ (printed right below the raise) and use one of those names.
2. Import from the correct submodule: from headroom.memory.backends.direct_mem0 import Mem0Config, or from headroom.memory.adapters... for adapters.
3. Verify spelling and casing exactly against the headroom version you have installed.
4. If upgrading headroom changed the API, read the changelog for renamed lazy symbols.

Example fix

# before
from headroom.memory import Mem0Config
# AttributeError: module 'headroom.memory' has no attribute 'Mem0Config'

# after
from headroom.memory import DirectMem0Config  # the registered lazy alias

import headroom.memory as hm

wanted = "DirectMem0Config"
if not (hasattr(hm, wanted) or wanted in getattr(hm, "__all__", ())):
    raise SystemExit(f"{wanted} is not exported by headroom.memory; check __all__")

import headroom.memory as hm

def memory_exports(name: str) -> bool:
    """True if name is importable from headroom.memory (eager or lazy)."""
    return name in hm.__all__ or hasattr(hm, name)

try:
    from headroom.memory import DirectMem0Config
except AttributeError as e:
    raise SystemExit(
        f"{e}; import from the defining submodule instead: "
        "from headroom.memory.backends.direct_mem0 import Mem0Config"
    ) from None

When it happens

Trigger: from headroom.memory import Something with a misspelled name (e.g. Mem0Config instead of DirectMem0Config), or accessing an attribute that only exists on a submodule (headroom.memory.backends...) directly on the package, or referencing an optional adapter class whose lazy branch was renamed in a newer headroom version.

Common situations: IDE autocomplete suggesting submodule names; version upgrades that moved/renamed lazily-loaded backends; code written against headroom.memory.backends.* but importing from headroom.memory; `from headroom.memory import *` users hitting names not in __all__.

Related errors

• module {__name__!r} has no attribute {name!r}
• module {__name__!r} has no attribute {name!r}
• any-llm-sdk is required for AnyLLMBackend. Install with: pip
• litellm is required for LiteLLMBackend. Install with: pip in
• Magika is required for ML-based content detection. Install w

AI-assisted analysis of headroomlabs-ai/headroom@322425c43b (2026-08-15). Data as JSON: /api/errors/aca59e7f653f92ce. Report an issue: GitHub.