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Fix "ModuleNotFoundError: No module named 'agno.memory.v2'" (Agno v1 → v2+ memory migration)

After upgrading Agno, imports like agno.memory.v2.memory and agno.storage.sqlite stop resolving. Here's the exact mapping to the current API, verified on Agno 3.1.10, and how to keep user memories working.

Updated 4 min readMarkdown

Disclosure: I'm Mohammed, founder of MemorySync. I drafted this with AI assistance and checked it against Agno's official migration guide and a real install. Code status: on Oct 25, 2026 I installed agno 3.1.10 (Python 3.13) and reproduced the errors below. I then ran the "after" imports, the Agent construction and get_user_memories successfully. No model was called (no key), so memory creation itself was not run.

The error

You upgrade Agno and memory code that used to work fails on import:

ModuleNotFoundError: No module named 'agno.memory.v2'

or, in VS Code / Pylance:

Import "agno.memory.v2.memory" could not be resolved

often with a companion:

ModuleNotFoundError: No module named 'agno.storage'

This was reported in agno-agi/agno#5017 (Agno 2.1.4, Python 3.11). The maintainers' answer was to follow the memory section of the v2 migration guide. I reproduced all three errors on Agno 3.1.10:

$ python -c "from agno.memory.v2.memory import Memory"
ModuleNotFoundError: No module named 'agno.memory.v2'
$ python -c "from agno.storage.sqlite import SqliteStorage"
ModuleNotFoundError: No module named 'agno.storage'

Why it happens

Agno v2 removed the v1 memory and storage modules rather than aliasing them. Per the v2 migration guide:

  • Storage classes moved from agno/storage to agno/db and are now called Db classes. One instance serves agents, teams and workflows, and the mode and table_name parameters are gone.
  • The MemoryDb classes are deprecated in favour of the main Db classes.
  • The Memory class is deprecated. You set update_memory_on_run=True on an Agent that has a db.

The fix: before and after

v1 (breaks):

from agno.agent import Agent
from agno.memory.v2.db.sqlite import SqliteMemoryDb
from agno.memory.v2.memory import Memory
from agno.storage.sqlite import SqliteStorage

memory = Memory(db=SqliteMemoryDb(table_name="user_memories", db_file="agno.db"))
storage = SqliteStorage(table_name="agent_sessions", db_file="agno.db")
agent = Agent(memory=memory, storage=storage, enable_user_memories=True)

v2+ (ran on 3.1.10):

from agno.agent import Agent
from agno.db.sqlite import SqliteDb

db = SqliteDb(db_file="agno.db")          # sessions AND memories
agent = Agent(db=db, update_memory_on_run=True)

print(agent.get_user_memories(user_id="john@example.com"))  # [] until a run stores something

Things to check after the swap:

  1. Pass user_id on every run. Memories are stored per user, so a missing or changing user_id looks like "memory isn't stored".
  2. Table names. If you need your old table names, SqliteDb takes session_table= and memory_table= instead of table_name=.
  3. Custom memory model or instructions. Build a MemoryManager (from agno.memory import MemoryManager) and pass memory_manager= to the Agent. The parameter names I found on the current Agent are memory_manager, enable_agentic_memory, update_memory_on_run and add_memories_to_context.
  4. Existing v1 data. The migration guide links a v1-to-v2 migration script. It says to use the script from the v2 release matching your environment and not to run it under Agno v3, so migrate to v2 first, verify, then upgrade. Back up your database before running anything against it.
  5. TypeError: UserMemory.__init__() got an unexpected keyword argument 'summaries'. This is a different, older error from mixed v1 memory data (#2955, Agno 1.4.1). The reporter confirmed it was gone after the maintainers' follow-up, so upgrade first.

If you get ImportError: The SQLAlchemy asyncio module requires that the Python 'greenlet' library is installed when importing agno.db.sqlite, run pip install greenlet. I hit this on a clean Python 3.13 venv.

If you want memories outside the local database

update_memory_on_run writes to whatever Db you pass. If you want sessions to stay local but user memories to live in a hosted store shared across instances, MemorySync's agno-memorysync package backs Agno's MemoryManager (guide). The guide says it needs agno 2.8+, and this constructed fine on 3.1.10:

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.memory import MemoryManager
from agno_memorysync import MemorySyncDb   # pip install agno-memorysync; needs MEMORYSYNC_API_KEY

agent = Agent(
    db=SqliteDb(db_file="agent.db"),                  # sessions: local
    memory_manager=MemoryManager(db=MemorySyncDb()),  # memories: hosted
    update_memory_on_run=True,
    user_id="customer-42",
)

The guide notes that MemorySyncDb is memory-only on purpose. Pointing sessions at it raises MemorySyncMemoryOnlyError, so keep db= local.

Common questions

Is there a compatibility shim for agno.memory.v2? Not in 3.1.10. The import fails. Update the imports.

Do I still need a separate storage object? No. One Db instance handles sessions, memories, metrics, evals and knowledge in separate tables.

My memories are stored but never show up in replies. If you pass a verbatim system_message=, it replaces Agno's built system prompt, which is where memories are injected. Use instructions= instead. (This tip is from MemorySync's Agno guide and applies to any memory db.)

Which Agno version is current? PyPI served 3.1.10 on Oct 25, 2026. The v2 migration steps above still applied to it.

To see a stored fact survive a reload before wiring anything in: try MemorySync in your browser. No signup is needed.

Sources

About the author

  • Building MemorySync (memorysync.io) — persistent memory infrastructure for AI agents, Cursor, and Claude Code.

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