mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-08 23:58:34 +00:00
e70bc94ab6
* Integrate Mem0 * Update src/crewai/memory/contextual/contextual_memory.py Co-authored-by: Deshraj Yadav <deshraj@gatech.edu> * pending commit for _fetch_user_memories * update poetry.lock * fixes mypy issues * fix mypy checks * New fixes for user_id * remove memory_provider * handle memory_provider * checks for memory_config * add mem0 to dependency * Update pyproject.toml Co-authored-by: Deshraj Yadav <deshraj@gatech.edu> * update docs * update doc * bump mem0 version * fix api error msg and mypy issue * mypy fix * resolve comments * fix memory usage without mem0 * mem0 version bump * lazy import mem0 --------- Co-authored-by: Deshraj Yadav <deshraj@gatech.edu> Co-authored-by: João Moura <joaomdmoura@gmail.com> Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
from typing import Any, Dict, Optional
|
|
|
|
from crewai.memory.memory import Memory
|
|
|
|
|
|
class UserMemory(Memory):
|
|
"""
|
|
UserMemory class for handling user memory storage and retrieval.
|
|
Inherits from the Memory class and utilizes an instance of a class that
|
|
adheres to the Storage for data storage, specifically working with
|
|
MemoryItem instances.
|
|
"""
|
|
|
|
def __init__(self, crew=None):
|
|
try:
|
|
from crewai.memory.storage.mem0_storage import Mem0Storage
|
|
except ImportError:
|
|
raise ImportError(
|
|
"Mem0 is not installed. Please install it with `pip install mem0ai`."
|
|
)
|
|
storage = Mem0Storage(type="user", crew=crew)
|
|
super().__init__(storage)
|
|
|
|
def save(
|
|
self,
|
|
value,
|
|
metadata: Optional[Dict[str, Any]] = None,
|
|
agent: Optional[str] = None,
|
|
) -> None:
|
|
# TODO: Change this function since we want to take care of the case where we save memories for the usr
|
|
data = f"Remember the details about the user: {value}"
|
|
super().save(data, metadata)
|
|
|
|
def search(
|
|
self,
|
|
query: str,
|
|
limit: int = 3,
|
|
score_threshold: float = 0.35,
|
|
):
|
|
results = super().search(
|
|
query=query,
|
|
limit=limit,
|
|
score_threshold=score_threshold,
|
|
)
|
|
return results
|