Set the path where all memories are saved

src/crewai/__init__.py

@@ -1,3 +1,4 @@
+__all__ = ["Agent", "Crew", "Process", "Task"]
 from crewai.agent import Agent
 from crewai.crew import Crew
 from crewai.process import Process

src/crewai/agent.py

@@ -21,7 +21,6 @@
 from pydantic_core import PydanticCustomError
 
 from crewai.agents import CacheHandler, CrewAgentExecutor, CrewAgentParser, ToolsHandler
-from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.utilities import I18N, Logger, Prompts, RPMController
 from crewai.utilities.token_counter_callback import TokenCalcHandler, TokenProcess
 
@@ -213,13 +212,8 @@ def execute_task(
                 task=task_prompt, context=context
             )
 
-        if self.crew and self.crew.memory:
-            contextual_memory = ContextualMemory(
-                self.crew._short_term_memory,
-                self.crew._long_term_memory,
-                self.crew._entity_memory,
-            )
-            memory = contextual_memory.build_context_for_task(task, context)
+        if self.crew and self.crew.memory and self.crew.contextual_memory:
+            memory = self.crew.contextual_memory.build_context_for_task(task, context)
             if memory.strip() != "":
                 task_prompt += self.i18n.slice("memory").format(memory=memory)
 

src/crewai/agents/__init__.py

@@ -1,3 +1,4 @@
+__all__ = ["CacheHandler", "CrewAgentExecutor", "CrewAgentParser", "ToolsHandler"]
 from .cache.cache_handler import CacheHandler
 from .executor import CrewAgentExecutor
 from .parser import CrewAgentParser

src/crewai/agents/cache/__init__.py

@@ -1 +1,2 @@
+__all__ = ["CacheHandler"]
 from .cache_handler import CacheHandler

src/crewai/crew.py

@@ -18,6 +18,8 @@
 
 from crewai.agent import Agent
 from crewai.agents.cache import CacheHandler
+from crewai.memory.memory import get_memory_paths
+from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.memory.entity.entity_memory import EntityMemory
 from crewai.memory.long_term.long_term_memory import LongTermMemory
 from crewai.memory.short_term.short_term_memory import ShortTermMemory
@@ -59,10 +61,6 @@ class Crew(BaseModel):
     _logger: Logger = PrivateAttr()
     _file_handler: FileHandler = PrivateAttr()
     _cache_handler: InstanceOf[CacheHandler] = PrivateAttr(default=CacheHandler())
-    _short_term_memory: Optional[InstanceOf[ShortTermMemory]] = PrivateAttr()
-    _long_term_memory: Optional[InstanceOf[LongTermMemory]] = PrivateAttr()
-    _entity_memory: Optional[InstanceOf[EntityMemory]] = PrivateAttr()
-
     cache: bool = Field(default=True)
     model_config = ConfigDict(arbitrary_types_allowed=True)
     tasks: List[Task] = Field(default_factory=list)
@@ -73,6 +71,10 @@ class Crew(BaseModel):
         default=False,
         description="Whether the crew should use memory to store memories of it's execution",
     )
+    contextual_memory: Optional[InstanceOf[ContextualMemory]] = Field(
+        default=None,
+        description="The memory storage for the crew.",
+    )
     embedder: Optional[dict] = Field(
         default={"provider": "openai"},
         description="Configuration for the embedder to be used for the crew.",
@@ -162,12 +164,22 @@ def set_private_attrs(self) -> "Crew":
     @model_validator(mode="after")
     def create_crew_memory(self) -> "Crew":
         """Set private attributes."""
-        if self.memory:
-            self._long_term_memory = LongTermMemory()
-            self._short_term_memory = ShortTermMemory(
-                crew=self, embedder_config=self.embedder
+        if self.memory and not self.contextual_memory:
+            long_term_memory_path, short_term_memory_path, entity_memory_path = (
+                get_memory_paths()
+            )
+            long_term_memory = LongTermMemory(db_path=long_term_memory_path)
+            short_term_memory = ShortTermMemory(
+                crew=self, db_path=short_term_memory_path, embedder_config=self.embedder
+            )
+            entity_memory = EntityMemory(
+                crew=self, db_path=entity_memory_path, embedder_config=self.embedder
+            )
+            self.contextual_memory = ContextualMemory(
+                short_term_memory=short_term_memory,
+                long_term_memory=long_term_memory,
+                entity_memory=entity_memory,
             )
-            self._entity_memory = EntityMemory(crew=self, embedder_config=self.embedder)
         return self
 
     @model_validator(mode="after")

src/crewai/memory/__init__.py

@@ -1,3 +1,4 @@
+__all__ = ["EntityMemory", "LongTermMemory", "ShortTermMemory"]
 from .entity.entity_memory import EntityMemory
 from .long_term.long_term_memory import LongTermMemory
 from .short_term.short_term_memory import ShortTermMemory

src/crewai/memory/entity/entity_memory.py

@@ -1,3 +1,5 @@
+from pathlib import Path
+
 from crewai.memory.entity.entity_memory_item import EntityMemoryItem
 from crewai.memory.memory import Memory
 from crewai.memory.storage.rag_storage import RAGStorage
@@ -10,9 +12,15 @@ class EntityMemory(Memory):
     Inherits from the Memory class.
     """
 
-    def __init__(self, crew=None, embedder_config=None):
+    def __init__(
+        self,
+        crew=None,
+        db_storage_path: Path | None = None,
+        embedder_config: dict | None = None,
+    ):
         storage = RAGStorage(
             type="entities",
+            db_storage_path=db_storage_path,
             allow_reset=False,
             embedder_config=embedder_config,
             crew=crew,

src/crewai/memory/long_term/long_term_memory.py

@@ -1,3 +1,4 @@
+from pathlib import Path
 from typing import Any, Dict
 
 from crewai.memory.long_term.long_term_memory_item import LongTermMemoryItem
@@ -14,8 +15,8 @@ class LongTermMemory(Memory):
     LongTermMemoryItem instances.
     """
 
-    def __init__(self):
-        storage = LTMSQLiteStorage()
+    def __init__(self, db_path: Path):
+        storage = LTMSQLiteStorage(db_path)
         super().__init__(storage)
 
     def save(self, item: LongTermMemoryItem) -> None:  # type: ignore # BUG?: Signature of "save" incompatible with supertype "Memory"

src/crewai/memory/memory.py

@@ -1,6 +1,18 @@
+from pathlib import Path
 from typing import Any, Dict, Optional
 
 from crewai.memory.storage.interface import Storage
+from crewai.utilities.paths import db_storage_path
+
+
+def get_memory_paths(memory_path: Path | None = None) -> tuple[Path, Path, Path]:
+    if not memory_path:
+        memory_path = db_storage_path()
+
+    long_term_memory_path = memory_path / "long_term_memory_storage.db"
+    short_term_memory_path = memory_path
+    entity_memory_path = memory_path
+    return long_term_memory_path, short_term_memory_path, entity_memory_path
 
 
 class Memory:

src/crewai/memory/short_term/short_term_memory.py

@@ -1,3 +1,5 @@
+from pathlib import Path
+
 from crewai.memory.memory import Memory
 from crewai.memory.short_term.short_term_memory_item import ShortTermMemoryItem
 from crewai.memory.storage.rag_storage import RAGStorage
@@ -12,9 +14,17 @@ class ShortTermMemory(Memory):
     MemoryItem instances.
     """
 
-    def __init__(self, crew=None, embedder_config=None):
+    def __init__(
+        self,
+        db_storage_path: Path | None = None,
+        crew=None,
+        embedder_config=None,
+    ):
         storage = RAGStorage(
-            type="short_term", embedder_config=embedder_config, crew=crew
+            type="short_term",
+            db_storage_path=db_storage_path,
+            embedder_config=embedder_config,
+            crew=crew,
         )
         super().__init__(storage)
 

src/crewai/memory/storage/ltm_sqlite_storage.py

@@ -3,17 +3,14 @@
 from typing import Any, Dict, List, Optional, Union
 
 from crewai.utilities import Printer
-from crewai.utilities.paths import db_storage_path
 
 
 class LTMSQLiteStorage:
     """
     An updated SQLite storage class for LTM data storage.
     """
 
-    def __init__(
-        self, db_path: str = f"{db_storage_path()}/long_term_memory_storage.db"
-    ) -> None:
+    def __init__(self, db_path: str) -> None:
         self.db_path = db_path
         self._printer: Printer = Printer()
         self._initialize_db()

src/crewai/memory/storage/rag_storage.py

@@ -2,14 +2,14 @@
 import io
 import logging
 import os
+from pathlib import Path
 from typing import Any, Dict, List, Optional
 
 from embedchain import App
 from embedchain.llm.base import BaseLlm
 from embedchain.vectordb.chroma import InvalidDimensionException
 
 from crewai.memory.storage.interface import Storage
-from crewai.utilities.paths import db_storage_path
 
 
 @contextlib.contextmanager
@@ -37,18 +37,29 @@ class RAGStorage(Storage):
     search efficiency.
     """
 
-    def __init__(self, type, allow_reset=True, embedder_config=None, crew=None):
+    def __init__(
+        self,
+        type: str,
+        db_storage_path: Path | None = None,
+        allow_reset=True,
+        embedder_config=None,
+        crew=None,
+    ):
         super().__init__()
         if (
             not os.getenv("OPENAI_API_KEY")
             and not os.getenv("OPENAI_BASE_URL") == "https://api.openai.com/v1"
         ):
             os.environ["OPENAI_API_KEY"] = "fake"
+        if db_storage_path is None:
+            db_storage_path = db_storage_path()
 
         agents = crew.agents if crew else []
         agents = [agent.role for agent in agents]
         agents = "_".join(agents)
 
+        dir = db_storage_path / {type} / {agents}
+
         config = {
             "app": {
                 "config": {"name": type, "collect_metrics": False, "log_level": "ERROR"}
@@ -63,7 +74,7 @@ def __init__(self, type, allow_reset=True, embedder_config=None, crew=None):
                 "provider": "chroma",
                 "config": {
                     "collection_name": type,
-                    "dir": f"{db_storage_path()}/{type}/{agents}",
+                    "dir": str(dir.absolute()),
                     "allow_reset": allow_reset,
                 },
             },

src/crewai/project/__init__.py

@@ -1,2 +1,3 @@
+__all__ = ["agent", "crew", "task", "CrewBase"]
 from .annotations import agent, crew, task
 from .crew_base import CrewBase

src/crewai/telemetry/__init__.py

@@ -1 +1,2 @@
+__all__ = ["Telemetry"]
 from .telemetry import Telemetry

src/crewai/utilities/__init__.py

@@ -1,3 +1,15 @@
+__all__ = [
+    "Converter",
+    "ConverterError",
+    "I18N",
+    "Instructor",
+    "Logger",
+    "Printer",
+    "Prompts",
+    "RPMController",
+    "FileHandler",
+    "YamlParser",
+]
 from .converter import Converter, ConverterError
 from .i18n import I18N
 from .instructor import Instructor

src/crewai/utilities/fileHandler.py

@@ -16,5 +16,5 @@ def __init__(self, file_path):
     def log(self, **kwargs):
         now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
         message = f"{now}: ".join([f"{key}={value}" for key, value in kwargs.items()])
-        with open(self._path, "a", encoding = 'utf-8') as file:
+        with open(self._path, "a", encoding="utf-8") as file:
             file.write(message + "\n")

src/crewai/utilities/logger.py

@@ -1,3 +1,4 @@
+import datetime
 from crewai.utilities.printer import Printer
 
 
@@ -13,6 +14,7 @@ def __init__(self, verbose_level=0):
     def log(self, level, message, color="bold_green"):
         level_map = {"debug": 1, "info": 2}
         if self.verbose_level and level_map.get(level, 0) <= self.verbose_level:
-            timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-            self._printer.print(f"[{timestamp}][{level.upper()}]: {message}", color=color)
-
+            timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            self._printer.print(
+                f"[{timestamp}][{level.upper()}]: {message}", color=color
+            )

src/crewai/utilities/paths.py

@@ -4,7 +4,7 @@
 import appdirs
 
 
-def db_storage_path():
+def db_storage_path() -> Path:
     app_name = get_project_directory_name()
     app_author = "CrewAI"
 

tests/agent_tools/agent_tools_test.py

@@ -55,6 +55,7 @@ def test_ask_question():
         == "As an AI researcher, I don't have personal feelings or emotions like love or hate. However, I recognize the importance of AI Agents in today's technological landscape. They have the potential to greatly enhance our lives and make tasks more efficient. At the same time, it is crucial to consider the ethical implications and societal impacts that come with their use. My role is to provide objective research and analysis on these topics."
     )
 
+
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_ask_question_with_wrong_co_worker_variable():
     result = tools.ask_question(
@@ -68,6 +69,7 @@ def test_ask_question_with_wrong_co_worker_variable():
         == "No, I don't hate AI agents. In fact, I find them quite fascinating. They are powerful tools that can greatly assist in various tasks, including my research. As a technology researcher, AI and AI agents are subjects of interest to me due to their potential in advancing our understanding and capabilities in various fields. My supposed love for them stems from this professional interest and the potential they hold."
     )
 
+
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_delegate_work_withwith_coworker_as_array():
     result = tools.delegate_work(

tests/memory/long_term_memory_test.py

@@ -1,13 +1,15 @@
 import pytest
 
+
 from crewai.memory.long_term.long_term_memory import LongTermMemory
 from crewai.memory.long_term.long_term_memory_item import LongTermMemoryItem
 
 
-@pytest.fixture
+@pytest.fixture(scope="session")
 def long_term_memory():
     """Fixture to create a LongTermMemory instance"""
-    return LongTermMemory()
+    data_dir = pytest.tmp_path_factory.mktemp("long_term_memory")
+    return LongTermMemory(data_dir)
 
 
 def test_save_and_search(long_term_memory):

tests/memory/short_term_memory_test.py

@@ -23,10 +23,7 @@ def short_term_memory():
         expected_output="A list of relevant URLs based on the search query.",
         agent=agent,
     )
-    return ShortTermMemory(crew=Crew(
-        agents=[agent],
-        tasks=[task]
-    ))
+    return ShortTermMemory(crew=Crew(agents=[agent], tasks=[task]))
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])