feat: async memory support

Adds async support for tools with tests, async execution in the agent executor, and async operations for memory (with aiosqlite). Improves tool decorator typing, ensures _run backward compatibility, updates docs and docstrings, adds tests, and regenerates lockfiles.

lib/crewai/pyproject.toml

@@ -38,6 +38,7 @@ dependencies = [
     "pydantic-settings~=2.10.1",
     "mcp~=1.16.0",
     "uv~=0.9.13",
+    "aiosqlite~=0.21.0",
 ]
 
 [project.urls]

lib/crewai/src/crewai/memory/contextual/contextual_memory.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import asyncio
 from typing import TYPE_CHECKING
 
 from crewai.memory import (
@@ -16,6 +17,8 @@ if TYPE_CHECKING:
 
 
 class ContextualMemory:
+    """Aggregates and retrieves context from multiple memory sources."""
+
     def __init__(
         self,
         stm: ShortTermMemory,
@@ -46,9 +49,14 @@ class ContextualMemory:
             self.exm.task = self.task
 
     def build_context_for_task(self, task: Task, context: str) -> str:
-        """
-        Automatically builds a minimal, highly relevant set of contextual information
-        for a given task.
+        """Build contextual information for a task synchronously.
+
+        Args:
+            task: The task to build context for.
+            context: Additional context string.
+
+        Returns:
+            Formatted context string from all memory sources.
         """
         query = f"{task.description} {context}".strip()
 
@@ -63,6 +71,31 @@ class ContextualMemory:
         ]
         return "\n".join(filter(None, context_parts))
 
+    async def abuild_context_for_task(self, task: Task, context: str) -> str:
+        """Build contextual information for a task asynchronously.
+
+        Args:
+            task: The task to build context for.
+            context: Additional context string.
+
+        Returns:
+            Formatted context string from all memory sources.
+        """
+        query = f"{task.description} {context}".strip()
+
+        if query == "":
+            return ""
+
+        # Fetch all contexts concurrently
+        results = await asyncio.gather(
+            self._afetch_ltm_context(task.description),
+            self._afetch_stm_context(query),
+            self._afetch_entity_context(query),
+            self._afetch_external_context(query),
+        )
+
+        return "\n".join(filter(None, results))
+
     def _fetch_stm_context(self, query: str) -> str:
         """
         Fetches recent relevant insights from STM related to the task's description and expected_output,
@@ -135,3 +168,87 @@ class ContextualMemory:
             f"- {result['content']}" for result in external_memories
         )
         return f"External memories:\n{formatted_memories}"
+
+    async def _afetch_stm_context(self, query: str) -> str:
+        """Fetch recent relevant insights from STM asynchronously.
+
+        Args:
+            query: The search query.
+
+        Returns:
+            Formatted insights as bullet points, or empty string if none found.
+        """
+        if self.stm is None:
+            return ""
+
+        stm_results = await self.stm.asearch(query)
+        formatted_results = "\n".join(
+            [f"- {result['content']}" for result in stm_results]
+        )
+        return f"Recent Insights:\n{formatted_results}" if stm_results else ""
+
+    async def _afetch_ltm_context(self, task: str) -> str | None:
+        """Fetch historical data from LTM asynchronously.
+
+        Args:
+            task: The task description to search for.
+
+        Returns:
+            Formatted historical data as bullet points, or None if none found.
+        """
+        if self.ltm is None:
+            return ""
+
+        ltm_results = await self.ltm.asearch(task, latest_n=2)
+        if not ltm_results:
+            return None
+
+        formatted_results = [
+            suggestion
+            for result in ltm_results
+            for suggestion in result["metadata"]["suggestions"]
+        ]
+        formatted_results = list(dict.fromkeys(formatted_results))
+        formatted_results = "\n".join([f"- {result}" for result in formatted_results])  # type: ignore # Incompatible types in assignment (expression has type "str", variable has type "list[str]")
+
+        return f"Historical Data:\n{formatted_results}" if ltm_results else ""
+
+    async def _afetch_entity_context(self, query: str) -> str:
+        """Fetch relevant entity information asynchronously.
+
+        Args:
+            query: The search query.
+
+        Returns:
+            Formatted entity information as bullet points, or empty string if none found.
+        """
+        if self.em is None:
+            return ""
+
+        em_results = await self.em.asearch(query)
+        formatted_results = "\n".join(
+            [f"- {result['content']}" for result in em_results]
+        )
+        return f"Entities:\n{formatted_results}" if em_results else ""
+
+    async def _afetch_external_context(self, query: str) -> str:
+        """Fetch relevant information from External Memory asynchronously.
+
+        Args:
+            query: The search query.
+
+        Returns:
+            Formatted information as bullet points, or empty string if none found.
+        """
+        if self.exm is None:
+            return ""
+
+        external_memories = await self.exm.asearch(query)
+
+        if not external_memories:
+            return ""
+
+        formatted_memories = "\n".join(
+            f"- {result['content']}" for result in external_memories
+        )
+        return f"External memories:\n{formatted_memories}"

lib/crewai/src/crewai/memory/entity/entity_memory.py

@@ -26,7 +26,13 @@ class EntityMemory(Memory):
 
     _memory_provider: str | None = PrivateAttr()
 
-    def __init__(self, crew=None, embedder_config=None, storage=None, path=None):
+    def __init__(
+        self,
+        crew: Any = None,
+        embedder_config: Any = None,
+        storage: Any = None,
+        path: str | None = None,
+    ) -> None:
         memory_provider = None
         if embedder_config and isinstance(embedder_config, dict):
             memory_provider = embedder_config.get("provider")
@@ -43,7 +49,7 @@ class EntityMemory(Memory):
                 if embedder_config and isinstance(embedder_config, dict)
                 else None
             )
-            storage = Mem0Storage(type="short_term", crew=crew, config=config)
+            storage = Mem0Storage(type="short_term", crew=crew, config=config)  # type: ignore[no-untyped-call]
         else:
             storage = (
                 storage
@@ -170,7 +176,17 @@ class EntityMemory(Memory):
         query: str,
         limit: int = 5,
         score_threshold: float = 0.6,
-    ):
+    ) -> list[Any]:
+        """Search entity memory for relevant entries.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching memory entries.
+        """
         crewai_event_bus.emit(
             self,
             event=MemoryQueryStartedEvent(
@@ -217,6 +233,168 @@ class EntityMemory(Memory):
             )
             raise
 
+    async def asave(
+        self,
+        value: EntityMemoryItem | list[EntityMemoryItem],
+        metadata: dict[str, Any] | None = None,
+    ) -> None:
+        """Save entity items asynchronously.
+
+        Args:
+            value: Single EntityMemoryItem or list of EntityMemoryItems to save.
+            metadata: Optional metadata dict (not used, for signature compatibility).
+        """
+        if not value:
+            return
+
+        items = value if isinstance(value, list) else [value]
+        is_batch = len(items) > 1
+
+        metadata = {"entity_count": len(items)} if is_batch else items[0].metadata
+        crewai_event_bus.emit(
+            self,
+            event=MemorySaveStartedEvent(
+                metadata=metadata,
+                source_type="entity_memory",
+                from_agent=self.agent,
+                from_task=self.task,
+            ),
+        )
+
+        start_time = time.time()
+        saved_count = 0
+        errors: list[str | None] = []
+
+        async def save_single_item(item: EntityMemoryItem) -> tuple[bool, str | None]:
+            """Save a single item asynchronously."""
+            try:
+                if self._memory_provider == "mem0":
+                    data = f"""
+                    Remember details about the following entity:
+                    Name: {item.name}
+                    Type: {item.type}
+                    Entity Description: {item.description}
+                    """
+                else:
+                    data = f"{item.name}({item.type}): {item.description}"
+
+                await super(EntityMemory, self).asave(data, item.metadata)
+                return True, None
+            except Exception as e:
+                return False, f"{item.name}: {e!s}"
+
+        try:
+            for item in items:
+                success, error = await save_single_item(item)
+                if success:
+                    saved_count += 1
+                else:
+                    errors.append(error)
+
+            if is_batch:
+                emit_value = f"Saved {saved_count} entities"
+                metadata = {"entity_count": saved_count, "errors": errors}
+            else:
+                emit_value = f"{items[0].name}({items[0].type}): {items[0].description}"
+                metadata = items[0].metadata
+
+            crewai_event_bus.emit(
+                self,
+                event=MemorySaveCompletedEvent(
+                    value=emit_value,
+                    metadata=metadata,
+                    save_time_ms=(time.time() - start_time) * 1000,
+                    source_type="entity_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+
+            if errors:
+                raise Exception(
+                    f"Partial save: {len(errors)} failed out of {len(items)}"
+                )
+
+        except Exception as e:
+            fail_metadata = (
+                {"entity_count": len(items), "saved": saved_count}
+                if is_batch
+                else items[0].metadata
+            )
+            crewai_event_bus.emit(
+                self,
+                event=MemorySaveFailedEvent(
+                    metadata=fail_metadata,
+                    error=str(e),
+                    source_type="entity_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+            raise
+
+    async def asearch(
+        self,
+        query: str,
+        limit: int = 5,
+        score_threshold: float = 0.6,
+    ) -> list[Any]:
+        """Search entity memory asynchronously.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching memory entries.
+        """
+        crewai_event_bus.emit(
+            self,
+            event=MemoryQueryStartedEvent(
+                query=query,
+                limit=limit,
+                score_threshold=score_threshold,
+                source_type="entity_memory",
+                from_agent=self.agent,
+                from_task=self.task,
+            ),
+        )
+
+        start_time = time.time()
+        try:
+            results = await super().asearch(
+                query=query, limit=limit, score_threshold=score_threshold
+            )
+
+            crewai_event_bus.emit(
+                self,
+                event=MemoryQueryCompletedEvent(
+                    query=query,
+                    results=results,
+                    limit=limit,
+                    score_threshold=score_threshold,
+                    query_time_ms=(time.time() - start_time) * 1000,
+                    source_type="entity_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+
+            return results
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                event=MemoryQueryFailedEvent(
+                    query=query,
+                    limit=limit,
+                    score_threshold=score_threshold,
+                    error=str(e),
+                    source_type="entity_memory",
+                ),
+            )
+            raise
+
     def reset(self) -> None:
         try:
             self.storage.reset()

lib/crewai/src/crewai/memory/external/external_memory.py

@@ -30,7 +30,7 @@ class ExternalMemory(Memory):
     def _configure_mem0(crew: Any, config: dict[str, Any]) -> Mem0Storage:
         from crewai.memory.storage.mem0_storage import Mem0Storage
 
-        return Mem0Storage(type="external", crew=crew, config=config)
+        return Mem0Storage(type="external", crew=crew, config=config)  # type: ignore[no-untyped-call]
 
     @staticmethod
     def external_supported_storages() -> dict[str, Any]:
@@ -53,7 +53,10 @@ class ExternalMemory(Memory):
         if provider not in supported_storages:
             raise ValueError(f"Provider {provider} not supported")
 
-        return supported_storages[provider](crew, embedder_config.get("config", {}))
+        storage: Storage = supported_storages[provider](
+            crew, embedder_config.get("config", {})
+        )
+        return storage
 
     def save(
         self,
@@ -111,7 +114,17 @@ class ExternalMemory(Memory):
         query: str,
         limit: int = 5,
         score_threshold: float = 0.6,
-    ):
+    ) -> list[Any]:
+        """Search external memory for relevant entries.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching memory entries.
+        """
         crewai_event_bus.emit(
             self,
             event=MemoryQueryStartedEvent(
@@ -158,6 +171,124 @@ class ExternalMemory(Memory):
             )
             raise
 
+    async def asave(
+        self,
+        value: Any,
+        metadata: dict[str, Any] | None = None,
+    ) -> None:
+        """Save a value to external memory asynchronously.
+
+        Args:
+            value: The value to save.
+            metadata: Optional metadata to associate with the value.
+        """
+        crewai_event_bus.emit(
+            self,
+            event=MemorySaveStartedEvent(
+                value=value,
+                metadata=metadata,
+                source_type="external_memory",
+                from_agent=self.agent,
+                from_task=self.task,
+            ),
+        )
+
+        start_time = time.time()
+        try:
+            item = ExternalMemoryItem(
+                value=value,
+                metadata=metadata,
+                agent=self.agent.role if self.agent else None,
+            )
+            await super().asave(value=item.value, metadata=item.metadata)
+
+            crewai_event_bus.emit(
+                self,
+                event=MemorySaveCompletedEvent(
+                    value=value,
+                    metadata=metadata,
+                    save_time_ms=(time.time() - start_time) * 1000,
+                    source_type="external_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                event=MemorySaveFailedEvent(
+                    value=value,
+                    metadata=metadata,
+                    error=str(e),
+                    source_type="external_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+            raise
+
+    async def asearch(
+        self,
+        query: str,
+        limit: int = 5,
+        score_threshold: float = 0.6,
+    ) -> list[Any]:
+        """Search external memory asynchronously.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching memory entries.
+        """
+        crewai_event_bus.emit(
+            self,
+            event=MemoryQueryStartedEvent(
+                query=query,
+                limit=limit,
+                score_threshold=score_threshold,
+                source_type="external_memory",
+                from_agent=self.agent,
+                from_task=self.task,
+            ),
+        )
+
+        start_time = time.time()
+        try:
+            results = await super().asearch(
+                query=query, limit=limit, score_threshold=score_threshold
+            )
+
+            crewai_event_bus.emit(
+                self,
+                event=MemoryQueryCompletedEvent(
+                    query=query,
+                    results=results,
+                    limit=limit,
+                    score_threshold=score_threshold,
+                    query_time_ms=(time.time() - start_time) * 1000,
+                    source_type="external_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+
+            return results
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                event=MemoryQueryFailedEvent(
+                    query=query,
+                    limit=limit,
+                    score_threshold=score_threshold,
+                    error=str(e),
+                    source_type="external_memory",
+                ),
+            )
+            raise
+
     def reset(self) -> None:
         self.storage.reset()
 

lib/crewai/src/crewai/memory/long_term/long_term_memory.py

@@ -24,7 +24,11 @@ class LongTermMemory(Memory):
     LongTermMemoryItem instances.
     """
 
-    def __init__(self, storage=None, path=None):
+    def __init__(
+        self,
+        storage: LTMSQLiteStorage | None = None,
+        path: str | None = None,
+    ) -> None:
         if not storage:
             storage = LTMSQLiteStorage(db_path=path) if path else LTMSQLiteStorage()
         super().__init__(storage=storage)
@@ -48,7 +52,7 @@ class LongTermMemory(Memory):
             metadata.update(
                 {"agent": item.agent, "expected_output": item.expected_output}
             )
-            self.storage.save(  # type: ignore # BUG?: Unexpected keyword argument "task_description","score","datetime" for "save" of "Storage"
+            self.storage.save(
                 task_description=item.task,
                 score=metadata["quality"],
                 metadata=metadata,
@@ -80,11 +84,20 @@ class LongTermMemory(Memory):
             )
             raise
 
-    def search(  # type: ignore # signature of "search" incompatible with supertype "Memory"
+    def search(  # type: ignore[override]
         self,
         task: str,
         latest_n: int = 3,
-    ) -> list[dict[str, Any]]:  # type: ignore # signature of "search" incompatible with supertype "Memory"
+    ) -> list[dict[str, Any]]:
+        """Search long-term memory for relevant entries.
+
+        Args:
+            task: The task description to search for.
+            latest_n: Maximum number of results to return.
+
+        Returns:
+            List of matching memory entries.
+        """
         crewai_event_bus.emit(
             self,
             event=MemoryQueryStartedEvent(
@@ -98,7 +111,7 @@ class LongTermMemory(Memory):
 
         start_time = time.time()
         try:
-            results = self.storage.load(task, latest_n)  # type: ignore # BUG?: "Storage" has no attribute "load"
+            results = self.storage.load(task, latest_n)
 
             crewai_event_bus.emit(
                 self,
@@ -113,7 +126,118 @@ class LongTermMemory(Memory):
                 ),
             )
 
-            return results
+            return results or []
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                event=MemoryQueryFailedEvent(
+                    query=task,
+                    limit=latest_n,
+                    error=str(e),
+                    source_type="long_term_memory",
+                ),
+            )
+            raise
+
+    async def asave(self, item: LongTermMemoryItem) -> None:  # type: ignore[override]
+        """Save an item to long-term memory asynchronously.
+
+        Args:
+            item: The LongTermMemoryItem to save.
+        """
+        crewai_event_bus.emit(
+            self,
+            event=MemorySaveStartedEvent(
+                value=item.task,
+                metadata=item.metadata,
+                agent_role=item.agent,
+                source_type="long_term_memory",
+                from_agent=self.agent,
+                from_task=self.task,
+            ),
+        )
+
+        start_time = time.time()
+        try:
+            metadata = item.metadata
+            metadata.update(
+                {"agent": item.agent, "expected_output": item.expected_output}
+            )
+            await self.storage.asave(
+                task_description=item.task,
+                score=metadata["quality"],
+                metadata=metadata,
+                datetime=item.datetime,
+            )
+
+            crewai_event_bus.emit(
+                self,
+                event=MemorySaveCompletedEvent(
+                    value=item.task,
+                    metadata=item.metadata,
+                    agent_role=item.agent,
+                    save_time_ms=(time.time() - start_time) * 1000,
+                    source_type="long_term_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                event=MemorySaveFailedEvent(
+                    value=item.task,
+                    metadata=item.metadata,
+                    agent_role=item.agent,
+                    error=str(e),
+                    source_type="long_term_memory",
+                ),
+            )
+            raise
+
+    async def asearch(  # type: ignore[override]
+        self,
+        task: str,
+        latest_n: int = 3,
+    ) -> list[dict[str, Any]]:
+        """Search long-term memory asynchronously.
+
+        Args:
+            task: The task description to search for.
+            latest_n: Maximum number of results to return.
+
+        Returns:
+            List of matching memory entries.
+        """
+        crewai_event_bus.emit(
+            self,
+            event=MemoryQueryStartedEvent(
+                query=task,
+                limit=latest_n,
+                source_type="long_term_memory",
+                from_agent=self.agent,
+                from_task=self.task,
+            ),
+        )
+
+        start_time = time.time()
+        try:
+            results = await self.storage.aload(task, latest_n)
+
+            crewai_event_bus.emit(
+                self,
+                event=MemoryQueryCompletedEvent(
+                    query=task,
+                    results=results,
+                    limit=latest_n,
+                    query_time_ms=(time.time() - start_time) * 1000,
+                    source_type="long_term_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+
+            return results or []
         except Exception as e:
             crewai_event_bus.emit(
                 self,
@@ -127,4 +251,5 @@ class LongTermMemory(Memory):
             raise
 
     def reset(self) -> None:
+        """Reset long-term memory."""
         self.storage.reset()

lib/crewai/src/crewai/memory/memory.py

@@ -13,9 +13,7 @@ if TYPE_CHECKING:
 
 
 class Memory(BaseModel):
-    """
-    Base class for memory, now supporting agent tags and generic metadata.
-    """
+    """Base class for memory, supporting agent tags and generic metadata."""
 
     embedder_config: EmbedderConfig | dict[str, Any] | None = None
     crew: Any | None = None
@@ -52,20 +50,72 @@ class Memory(BaseModel):
         value: Any,
         metadata: dict[str, Any] | None = None,
     ) -> None:
-        metadata = metadata or {}
+        """Save a value to memory.
 
+        Args:
+            value: The value to save.
+            metadata: Optional metadata to associate with the value.
+        """
+        metadata = metadata or {}
         self.storage.save(value, metadata)
 
+    async def asave(
+        self,
+        value: Any,
+        metadata: dict[str, Any] | None = None,
+    ) -> None:
+        """Save a value to memory asynchronously.
+
+        Args:
+            value: The value to save.
+            metadata: Optional metadata to associate with the value.
+        """
+        metadata = metadata or {}
+        await self.storage.asave(value, metadata)
+
     def search(
         self,
         query: str,
         limit: int = 5,
         score_threshold: float = 0.6,
     ) -> list[Any]:
-        return self.storage.search(
+        """Search memory for relevant entries.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching memory entries.
+        """
+        results: list[Any] = self.storage.search(
             query=query, limit=limit, score_threshold=score_threshold
         )
+        return results
+
+    async def asearch(
+        self,
+        query: str,
+        limit: int = 5,
+        score_threshold: float = 0.6,
+    ) -> list[Any]:
+        """Search memory for relevant entries asynchronously.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching memory entries.
+        """
+        results: list[Any] = await self.storage.asearch(
+            query=query, limit=limit, score_threshold=score_threshold
+        )
+        return results
 
     def set_crew(self, crew: Any) -> Memory:
+        """Set the crew for this memory instance."""
         self.crew = crew
         return self

lib/crewai/src/crewai/memory/short_term/short_term_memory.py

@@ -30,7 +30,13 @@ class ShortTermMemory(Memory):
 
     _memory_provider: str | None = PrivateAttr()
 
-    def __init__(self, crew=None, embedder_config=None, storage=None, path=None):
+    def __init__(
+        self,
+        crew: Any = None,
+        embedder_config: Any = None,
+        storage: Any = None,
+        path: str | None = None,
+    ) -> None:
         memory_provider = None
         if embedder_config and isinstance(embedder_config, dict):
             memory_provider = embedder_config.get("provider")
@@ -47,7 +53,7 @@ class ShortTermMemory(Memory):
                 if embedder_config and isinstance(embedder_config, dict)
                 else None
             )
-            storage = Mem0Storage(type="short_term", crew=crew, config=config)
+            storage = Mem0Storage(type="short_term", crew=crew, config=config)  # type: ignore[no-untyped-call]
         else:
             storage = (
                 storage
@@ -123,7 +129,17 @@ class ShortTermMemory(Memory):
         query: str,
         limit: int = 5,
         score_threshold: float = 0.6,
-    ):
+    ) -> list[Any]:
+        """Search short-term memory for relevant entries.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching memory entries.
+        """
         crewai_event_bus.emit(
             self,
             event=MemoryQueryStartedEvent(
@@ -140,7 +156,7 @@ class ShortTermMemory(Memory):
         try:
             results = self.storage.search(
                 query=query, limit=limit, score_threshold=score_threshold
-            )  # type: ignore # BUG? The reference is to the parent class, but the parent class does not have this parameters
+            )
 
             crewai_event_bus.emit(
                 self,
@@ -156,7 +172,130 @@ class ShortTermMemory(Memory):
                 ),
             )
 
-            return results
+            return list(results)
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                event=MemoryQueryFailedEvent(
+                    query=query,
+                    limit=limit,
+                    score_threshold=score_threshold,
+                    error=str(e),
+                    source_type="short_term_memory",
+                ),
+            )
+            raise
+
+    async def asave(
+        self,
+        value: Any,
+        metadata: dict[str, Any] | None = None,
+    ) -> None:
+        """Save a value to short-term memory asynchronously.
+
+        Args:
+            value: The value to save.
+            metadata: Optional metadata to associate with the value.
+        """
+        crewai_event_bus.emit(
+            self,
+            event=MemorySaveStartedEvent(
+                value=value,
+                metadata=metadata,
+                source_type="short_term_memory",
+                from_agent=self.agent,
+                from_task=self.task,
+            ),
+        )
+
+        start_time = time.time()
+        try:
+            item = ShortTermMemoryItem(
+                data=value,
+                metadata=metadata,
+                agent=self.agent.role if self.agent else None,
+            )
+            if self._memory_provider == "mem0":
+                item.data = (
+                    f"Remember the following insights from Agent run: {item.data}"
+                )
+
+            await super().asave(value=item.data, metadata=item.metadata)
+
+            crewai_event_bus.emit(
+                self,
+                event=MemorySaveCompletedEvent(
+                    value=value,
+                    metadata=metadata,
+                    save_time_ms=(time.time() - start_time) * 1000,
+                    source_type="short_term_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                event=MemorySaveFailedEvent(
+                    value=value,
+                    metadata=metadata,
+                    error=str(e),
+                    source_type="short_term_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+            raise
+
+    async def asearch(
+        self,
+        query: str,
+        limit: int = 5,
+        score_threshold: float = 0.6,
+    ) -> list[Any]:
+        """Search short-term memory asynchronously.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching memory entries.
+        """
+        crewai_event_bus.emit(
+            self,
+            event=MemoryQueryStartedEvent(
+                query=query,
+                limit=limit,
+                score_threshold=score_threshold,
+                source_type="short_term_memory",
+                from_agent=self.agent,
+                from_task=self.task,
+            ),
+        )
+
+        start_time = time.time()
+        try:
+            results = await self.storage.asearch(
+                query=query, limit=limit, score_threshold=score_threshold
+            )
+
+            crewai_event_bus.emit(
+                self,
+                event=MemoryQueryCompletedEvent(
+                    query=query,
+                    results=results,
+                    limit=limit,
+                    score_threshold=score_threshold,
+                    query_time_ms=(time.time() - start_time) * 1000,
+                    source_type="short_term_memory",
+                    from_agent=self.agent,
+                    from_task=self.task,
+                ),
+            )
+
+            return list(results)
         except Exception as e:
             crewai_event_bus.emit(
                 self,

lib/crewai/src/crewai/memory/storage/ltm_sqlite_storage.py

@@ -3,29 +3,30 @@ from pathlib import Path
 import sqlite3
 from typing import Any
 
+import aiosqlite
+
 from crewai.utilities import Printer
 from crewai.utilities.paths import db_storage_path
 
 
 class LTMSQLiteStorage:
-    """
-    An updated SQLite storage class for LTM data storage.
-    """
+    """SQLite storage class for long-term memory data."""
 
     def __init__(self, db_path: str | None = None) -> None:
+        """Initialize the SQLite storage.
+
+        Args:
+            db_path: Optional path to the database file.
+        """
         if db_path is None:
-            # Get the parent directory of the default db path and create our db file there
             db_path = str(Path(db_storage_path()) / "long_term_memory_storage.db")
         self.db_path = db_path
         self._printer: Printer = Printer()
-        # Ensure parent directory exists
         Path(self.db_path).parent.mkdir(parents=True, exist_ok=True)
         self._initialize_db()
 
-    def _initialize_db(self):
-        """
-        Initializes the SQLite database and creates LTM table
-        """
+    def _initialize_db(self) -> None:
+        """Initialize the SQLite database and create LTM table."""
         try:
             with sqlite3.connect(self.db_path) as conn:
                 cursor = conn.cursor()
@@ -106,9 +107,7 @@ class LTMSQLiteStorage:
             )
         return None
 
-    def reset(
-        self,
-    ) -> None:
+    def reset(self) -> None:
         """Resets the LTM table with error handling."""
         try:
             with sqlite3.connect(self.db_path) as conn:
@@ -121,4 +120,87 @@ class LTMSQLiteStorage:
                 content=f"MEMORY ERROR: An error occurred while deleting all rows in LTM: {e}",
                 color="red",
             )
-        return
+
+    async def asave(
+        self,
+        task_description: str,
+        metadata: dict[str, Any],
+        datetime: str,
+        score: int | float,
+    ) -> None:
+        """Save data to the LTM table asynchronously.
+
+        Args:
+            task_description: Description of the task.
+            metadata: Metadata associated with the memory.
+            datetime: Timestamp of the memory.
+            score: Quality score of the memory.
+        """
+        try:
+            async with aiosqlite.connect(self.db_path) as conn:
+                await conn.execute(
+                    """
+                    INSERT INTO long_term_memories (task_description, metadata, datetime, score)
+                    VALUES (?, ?, ?, ?)
+                    """,
+                    (task_description, json.dumps(metadata), datetime, score),
+                )
+                await conn.commit()
+        except aiosqlite.Error as e:
+            self._printer.print(
+                content=f"MEMORY ERROR: An error occurred while saving to LTM: {e}",
+                color="red",
+            )
+
+    async def aload(
+        self, task_description: str, latest_n: int
+    ) -> list[dict[str, Any]] | None:
+        """Query the LTM table by task description asynchronously.
+
+        Args:
+            task_description: Description of the task to search for.
+            latest_n: Maximum number of results to return.
+
+        Returns:
+            List of matching memory entries or None if error occurs.
+        """
+        try:
+            async with aiosqlite.connect(self.db_path) as conn:
+                cursor = await conn.execute(
+                    f"""
+                    SELECT metadata, datetime, score
+                    FROM long_term_memories
+                    WHERE task_description = ?
+                    ORDER BY datetime DESC, score ASC
+                    LIMIT {latest_n}
+                    """,  # nosec # noqa: S608
+                    (task_description,),
+                )
+                rows = await cursor.fetchall()
+                if rows:
+                    return [
+                        {
+                            "metadata": json.loads(row[0]),
+                            "datetime": row[1],
+                            "score": row[2],
+                        }
+                        for row in rows
+                    ]
+        except aiosqlite.Error as e:
+            self._printer.print(
+                content=f"MEMORY ERROR: An error occurred while querying LTM: {e}",
+                color="red",
+            )
+        return None
+
+    async def areset(self) -> None:
+        """Reset the LTM table asynchronously."""
+        try:
+            async with aiosqlite.connect(self.db_path) as conn:
+                await conn.execute("DELETE FROM long_term_memories")
+                await conn.commit()
+        except aiosqlite.Error as e:
+            self._printer.print(
+                content=f"MEMORY ERROR: An error occurred while deleting all rows in LTM: {e}",
+                color="red",
+            )

lib/crewai/src/crewai/memory/storage/rag_storage.py

@@ -129,6 +129,12 @@ class RAGStorage(BaseRAGStorage):
         return f"{base_path}/{file_name}"
 
     def save(self, value: Any, metadata: dict[str, Any]) -> None:
+        """Save a value to storage.
+
+        Args:
+            value: The value to save.
+            metadata: Metadata to associate with the value.
+        """
         try:
             client = self._get_client()
             collection_name = (
@@ -167,6 +173,51 @@ class RAGStorage(BaseRAGStorage):
                 f"Error during {self.type} save: {e!s}\n{traceback.format_exc()}"
             )
 
+    async def asave(self, value: Any, metadata: dict[str, Any]) -> None:
+        """Save a value to storage asynchronously.
+
+        Args:
+            value: The value to save.
+            metadata: Metadata to associate with the value.
+        """
+        try:
+            client = self._get_client()
+            collection_name = (
+                f"memory_{self.type}_{self.agents}"
+                if self.agents
+                else f"memory_{self.type}"
+            )
+            await client.aget_or_create_collection(collection_name=collection_name)
+
+            document: BaseRecord = {"content": value}
+            if metadata:
+                document["metadata"] = metadata
+
+            batch_size = None
+            if (
+                self.embedder_config
+                and isinstance(self.embedder_config, dict)
+                and "config" in self.embedder_config
+            ):
+                nested_config = self.embedder_config["config"]
+                if isinstance(nested_config, dict):
+                    batch_size = nested_config.get("batch_size")
+
+            if batch_size is not None:
+                await client.aadd_documents(
+                    collection_name=collection_name,
+                    documents=[document],
+                    batch_size=cast(int, batch_size),
+                )
+            else:
+                await client.aadd_documents(
+                    collection_name=collection_name, documents=[document]
+                )
+        except Exception as e:
+            logging.error(
+                f"Error during {self.type} async save: {e!s}\n{traceback.format_exc()}"
+            )
+
     def search(
         self,
         query: str,
@@ -174,6 +225,17 @@ class RAGStorage(BaseRAGStorage):
         filter: dict[str, Any] | None = None,
         score_threshold: float = 0.6,
     ) -> list[Any]:
+        """Search for matching entries in storage.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            filter: Optional metadata filter.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching entries.
+        """
         try:
             client = self._get_client()
             collection_name = (
@@ -194,6 +256,44 @@ class RAGStorage(BaseRAGStorage):
             )
             return []
 
+    async def asearch(
+        self,
+        query: str,
+        limit: int = 5,
+        filter: dict[str, Any] | None = None,
+        score_threshold: float = 0.6,
+    ) -> list[Any]:
+        """Search for matching entries in storage asynchronously.
+
+        Args:
+            query: The search query.
+            limit: Maximum number of results to return.
+            filter: Optional metadata filter.
+            score_threshold: Minimum similarity score for results.
+
+        Returns:
+            List of matching entries.
+        """
+        try:
+            client = self._get_client()
+            collection_name = (
+                f"memory_{self.type}_{self.agents}"
+                if self.agents
+                else f"memory_{self.type}"
+            )
+            return await client.asearch(
+                collection_name=collection_name,
+                query=query,
+                limit=limit,
+                metadata_filter=filter,
+                score_threshold=score_threshold,
+            )
+        except Exception as e:
+            logging.error(
+                f"Error during {self.type} async search: {e!s}\n{traceback.format_exc()}"
+            )
+            return []
+
     def reset(self) -> None:
         try:
             client = self._get_client()

lib/crewai/tests/memory/test_async_memory.py

@@ -0,0 +1,496 @@
+"""Tests for async memory operations."""
+
+import threading
+from collections import defaultdict
+from unittest.mock import ANY, AsyncMock, MagicMock, patch
+
+import pytest
+
+from crewai.agent import Agent
+from crewai.crew import Crew
+from crewai.events.event_bus import crewai_event_bus
+from crewai.events.types.memory_events import (
+    MemoryQueryCompletedEvent,
+    MemoryQueryStartedEvent,
+    MemorySaveCompletedEvent,
+    MemorySaveStartedEvent,
+)
+from crewai.memory.contextual.contextual_memory import ContextualMemory
+from crewai.memory.entity.entity_memory import EntityMemory
+from crewai.memory.entity.entity_memory_item import EntityMemoryItem
+from crewai.memory.external.external_memory import ExternalMemory
+from crewai.memory.long_term.long_term_memory import LongTermMemory
+from crewai.memory.long_term.long_term_memory_item import LongTermMemoryItem
+from crewai.memory.short_term.short_term_memory import ShortTermMemory
+from crewai.task import Task
+
+
+@pytest.fixture
+def mock_agent():
+    """Fixture to create a mock agent."""
+    return Agent(
+        role="Researcher",
+        goal="Search relevant data and provide results",
+        backstory="You are a researcher at a leading tech think tank.",
+        tools=[],
+        verbose=True,
+    )
+
+
+@pytest.fixture
+def mock_task(mock_agent):
+    """Fixture to create a mock task."""
+    return Task(
+        description="Perform a search on specific topics.",
+        expected_output="A list of relevant URLs based on the search query.",
+        agent=mock_agent,
+    )
+
+
+@pytest.fixture
+def short_term_memory(mock_agent, mock_task):
+    """Fixture to create a ShortTermMemory instance."""
+    return ShortTermMemory(crew=Crew(agents=[mock_agent], tasks=[mock_task]))
+
+
+@pytest.fixture
+def long_term_memory(tmp_path):
+    """Fixture to create a LongTermMemory instance."""
+    db_path = str(tmp_path / "test_ltm.db")
+    return LongTermMemory(path=db_path)
+
+
+@pytest.fixture
+def entity_memory(tmp_path, mock_agent, mock_task):
+    """Fixture to create an EntityMemory instance."""
+    return EntityMemory(
+        crew=Crew(agents=[mock_agent], tasks=[mock_task]),
+        path=str(tmp_path / "test_entities"),
+    )
+
+
+class TestAsyncShortTermMemory:
+    """Tests for async ShortTermMemory operations."""
+
+    @pytest.mark.asyncio
+    async def test_asave_emits_events(self, short_term_memory):
+        """Test that asave emits the correct events."""
+        events: dict[str, list] = defaultdict(list)
+        condition = threading.Condition()
+
+        @crewai_event_bus.on(MemorySaveStartedEvent)
+        def on_save_started(source, event):
+            with condition:
+                events["MemorySaveStartedEvent"].append(event)
+                condition.notify()
+
+        @crewai_event_bus.on(MemorySaveCompletedEvent)
+        def on_save_completed(source, event):
+            with condition:
+                events["MemorySaveCompletedEvent"].append(event)
+                condition.notify()
+
+        await short_term_memory.asave(
+            value="async test value",
+            metadata={"task": "async_test_task"},
+        )
+
+        with condition:
+            success = condition.wait_for(
+                lambda: len(events["MemorySaveStartedEvent"]) >= 1
+                and len(events["MemorySaveCompletedEvent"]) >= 1,
+                timeout=5,
+            )
+        assert success, "Timeout waiting for async save events"
+
+        assert len(events["MemorySaveStartedEvent"]) >= 1
+        assert len(events["MemorySaveCompletedEvent"]) >= 1
+        assert events["MemorySaveStartedEvent"][-1].value == "async test value"
+        assert events["MemorySaveStartedEvent"][-1].source_type == "short_term_memory"
+
+    @pytest.mark.asyncio
+    async def test_asearch_emits_events(self, short_term_memory):
+        """Test that asearch emits the correct events."""
+        events: dict[str, list] = defaultdict(list)
+        search_started = threading.Event()
+        search_completed = threading.Event()
+
+        with patch.object(short_term_memory.storage, "asearch", new_callable=AsyncMock, return_value=[]):
+
+            @crewai_event_bus.on(MemoryQueryStartedEvent)
+            def on_search_started(source, event):
+                events["MemoryQueryStartedEvent"].append(event)
+                search_started.set()
+
+            @crewai_event_bus.on(MemoryQueryCompletedEvent)
+            def on_search_completed(source, event):
+                events["MemoryQueryCompletedEvent"].append(event)
+                search_completed.set()
+
+            await short_term_memory.asearch(
+                query="async test query",
+                limit=3,
+                score_threshold=0.35,
+            )
+
+            assert search_started.wait(timeout=2), "Timeout waiting for search started event"
+            assert search_completed.wait(timeout=2), "Timeout waiting for search completed event"
+
+        assert len(events["MemoryQueryStartedEvent"]) >= 1
+        assert len(events["MemoryQueryCompletedEvent"]) >= 1
+        assert events["MemoryQueryStartedEvent"][-1].query == "async test query"
+        assert events["MemoryQueryStartedEvent"][-1].source_type == "short_term_memory"
+
+
+class TestAsyncLongTermMemory:
+    """Tests for async LongTermMemory operations."""
+
+    @pytest.mark.asyncio
+    async def test_asave_emits_events(self, long_term_memory):
+        """Test that asave emits the correct events."""
+        events: dict[str, list] = defaultdict(list)
+        condition = threading.Condition()
+
+        @crewai_event_bus.on(MemorySaveStartedEvent)
+        def on_save_started(source, event):
+            with condition:
+                events["MemorySaveStartedEvent"].append(event)
+                condition.notify()
+
+        @crewai_event_bus.on(MemorySaveCompletedEvent)
+        def on_save_completed(source, event):
+            with condition:
+                events["MemorySaveCompletedEvent"].append(event)
+                condition.notify()
+
+        item = LongTermMemoryItem(
+            task="async test task",
+            agent="test_agent",
+            expected_output="test output",
+            datetime="2024-01-01T00:00:00",
+            quality=0.9,
+            metadata={"task": "async test task", "quality": 0.9},
+        )
+
+        await long_term_memory.asave(item)
+
+        with condition:
+            success = condition.wait_for(
+                lambda: len(events["MemorySaveStartedEvent"]) >= 1
+                and len(events["MemorySaveCompletedEvent"]) >= 1,
+                timeout=5,
+            )
+        assert success, "Timeout waiting for async save events"
+
+        assert len(events["MemorySaveStartedEvent"]) >= 1
+        assert len(events["MemorySaveCompletedEvent"]) >= 1
+        assert events["MemorySaveStartedEvent"][-1].source_type == "long_term_memory"
+
+    @pytest.mark.asyncio
+    async def test_asearch_emits_events(self, long_term_memory):
+        """Test that asearch emits the correct events."""
+        events: dict[str, list] = defaultdict(list)
+        search_started = threading.Event()
+        search_completed = threading.Event()
+
+        @crewai_event_bus.on(MemoryQueryStartedEvent)
+        def on_search_started(source, event):
+            events["MemoryQueryStartedEvent"].append(event)
+            search_started.set()
+
+        @crewai_event_bus.on(MemoryQueryCompletedEvent)
+        def on_search_completed(source, event):
+            events["MemoryQueryCompletedEvent"].append(event)
+            search_completed.set()
+
+        await long_term_memory.asearch(task="async test task", latest_n=3)
+
+        assert search_started.wait(timeout=2), "Timeout waiting for search started event"
+        assert search_completed.wait(timeout=2), "Timeout waiting for search completed event"
+
+        assert len(events["MemoryQueryStartedEvent"]) >= 1
+        assert len(events["MemoryQueryCompletedEvent"]) >= 1
+        assert events["MemoryQueryStartedEvent"][-1].source_type == "long_term_memory"
+
+    @pytest.mark.asyncio
+    async def test_asave_and_asearch_integration(self, long_term_memory):
+        """Test that asave followed by asearch works correctly."""
+        item = LongTermMemoryItem(
+            task="integration test task",
+            agent="test_agent",
+            expected_output="test output",
+            datetime="2024-01-01T00:00:00",
+            quality=0.9,
+            metadata={"task": "integration test task", "quality": 0.9},
+        )
+
+        await long_term_memory.asave(item)
+        results = await long_term_memory.asearch(task="integration test task", latest_n=1)
+
+        assert results is not None
+        assert len(results) == 1
+        assert results[0]["metadata"]["agent"] == "test_agent"
+
+
+class TestAsyncEntityMemory:
+    """Tests for async EntityMemory operations."""
+
+    @pytest.mark.asyncio
+    async def test_asave_single_item_emits_events(self, entity_memory):
+        """Test that asave with a single item emits the correct events."""
+        events: dict[str, list] = defaultdict(list)
+        condition = threading.Condition()
+
+        @crewai_event_bus.on(MemorySaveStartedEvent)
+        def on_save_started(source, event):
+            with condition:
+                events["MemorySaveStartedEvent"].append(event)
+                condition.notify()
+
+        @crewai_event_bus.on(MemorySaveCompletedEvent)
+        def on_save_completed(source, event):
+            with condition:
+                events["MemorySaveCompletedEvent"].append(event)
+                condition.notify()
+
+        item = EntityMemoryItem(
+            name="TestEntity",
+            type="Person",
+            description="A test entity for async operations",
+            relationships="Related to other test entities",
+        )
+
+        await entity_memory.asave(item)
+
+        with condition:
+            success = condition.wait_for(
+                lambda: len(events["MemorySaveStartedEvent"]) >= 1
+                and len(events["MemorySaveCompletedEvent"]) >= 1,
+                timeout=5,
+            )
+        assert success, "Timeout waiting for async save events"
+
+        assert len(events["MemorySaveStartedEvent"]) >= 1
+        assert len(events["MemorySaveCompletedEvent"]) >= 1
+        assert events["MemorySaveStartedEvent"][-1].source_type == "entity_memory"
+
+    @pytest.mark.asyncio
+    async def test_asearch_emits_events(self, entity_memory):
+        """Test that asearch emits the correct events."""
+        events: dict[str, list] = defaultdict(list)
+        search_started = threading.Event()
+        search_completed = threading.Event()
+
+        @crewai_event_bus.on(MemoryQueryStartedEvent)
+        def on_search_started(source, event):
+            events["MemoryQueryStartedEvent"].append(event)
+            search_started.set()
+
+        @crewai_event_bus.on(MemoryQueryCompletedEvent)
+        def on_search_completed(source, event):
+            events["MemoryQueryCompletedEvent"].append(event)
+            search_completed.set()
+
+        await entity_memory.asearch(query="TestEntity", limit=5, score_threshold=0.6)
+
+        assert search_started.wait(timeout=2), "Timeout waiting for search started event"
+        assert search_completed.wait(timeout=2), "Timeout waiting for search completed event"
+
+        assert len(events["MemoryQueryStartedEvent"]) >= 1
+        assert len(events["MemoryQueryCompletedEvent"]) >= 1
+        assert events["MemoryQueryStartedEvent"][-1].source_type == "entity_memory"
+
+
+class TestAsyncContextualMemory:
+    """Tests for async ContextualMemory operations."""
+
+    @pytest.mark.asyncio
+    async def test_abuild_context_for_task_with_empty_query(self, mock_task):
+        """Test that abuild_context_for_task returns empty string for empty query."""
+        mock_task.description = ""
+        contextual_memory = ContextualMemory(
+            stm=None,
+            ltm=None,
+            em=None,
+            exm=None,
+        )
+
+        result = await contextual_memory.abuild_context_for_task(mock_task, "")
+        assert result == ""
+
+    @pytest.mark.asyncio
+    async def test_abuild_context_for_task_with_none_memories(self, mock_task):
+        """Test that abuild_context_for_task handles None memory sources."""
+        contextual_memory = ContextualMemory(
+            stm=None,
+            ltm=None,
+            em=None,
+            exm=None,
+        )
+
+        result = await contextual_memory.abuild_context_for_task(mock_task, "some context")
+        assert result == ""
+
+    @pytest.mark.asyncio
+    async def test_abuild_context_for_task_aggregates_results(self, mock_agent, mock_task):
+        """Test that abuild_context_for_task aggregates results from all memory sources."""
+        mock_stm = MagicMock(spec=ShortTermMemory)
+        mock_stm.asearch = AsyncMock(return_value=[{"content": "STM insight"}])
+
+        mock_ltm = MagicMock(spec=LongTermMemory)
+        mock_ltm.asearch = AsyncMock(
+            return_value=[{"metadata": {"suggestions": ["LTM suggestion"]}}]
+        )
+
+        mock_em = MagicMock(spec=EntityMemory)
+        mock_em.asearch = AsyncMock(return_value=[{"content": "Entity info"}])
+
+        mock_exm = MagicMock(spec=ExternalMemory)
+        mock_exm.asearch = AsyncMock(return_value=[{"content": "External memory"}])
+
+        contextual_memory = ContextualMemory(
+            stm=mock_stm,
+            ltm=mock_ltm,
+            em=mock_em,
+            exm=mock_exm,
+            agent=mock_agent,
+            task=mock_task,
+        )
+
+        result = await contextual_memory.abuild_context_for_task(mock_task, "additional context")
+
+        assert "Recent Insights:" in result
+        assert "STM insight" in result
+        assert "Historical Data:" in result
+        assert "LTM suggestion" in result
+        assert "Entities:" in result
+        assert "Entity info" in result
+        assert "External memories:" in result
+        assert "External memory" in result
+
+    @pytest.mark.asyncio
+    async def test_afetch_stm_context_returns_formatted_results(self, mock_agent, mock_task):
+        """Test that _afetch_stm_context returns properly formatted results."""
+        mock_stm = MagicMock(spec=ShortTermMemory)
+        mock_stm.asearch = AsyncMock(
+            return_value=[
+                {"content": "First insight"},
+                {"content": "Second insight"},
+            ]
+        )
+
+        contextual_memory = ContextualMemory(
+            stm=mock_stm,
+            ltm=None,
+            em=None,
+            exm=None,
+        )
+
+        result = await contextual_memory._afetch_stm_context("test query")
+
+        assert "Recent Insights:" in result
+        assert "- First insight" in result
+        assert "- Second insight" in result
+
+    @pytest.mark.asyncio
+    async def test_afetch_ltm_context_returns_formatted_results(self, mock_agent, mock_task):
+        """Test that _afetch_ltm_context returns properly formatted results."""
+        mock_ltm = MagicMock(spec=LongTermMemory)
+        mock_ltm.asearch = AsyncMock(
+            return_value=[
+                {"metadata": {"suggestions": ["Suggestion 1", "Suggestion 2"]}},
+            ]
+        )
+
+        contextual_memory = ContextualMemory(
+            stm=None,
+            ltm=mock_ltm,
+            em=None,
+            exm=None,
+        )
+
+        result = await contextual_memory._afetch_ltm_context("test task")
+
+        assert "Historical Data:" in result
+        assert "- Suggestion 1" in result
+        assert "- Suggestion 2" in result
+
+    @pytest.mark.asyncio
+    async def test_afetch_entity_context_returns_formatted_results(self, mock_agent, mock_task):
+        """Test that _afetch_entity_context returns properly formatted results."""
+        mock_em = MagicMock(spec=EntityMemory)
+        mock_em.asearch = AsyncMock(
+            return_value=[
+                {"content": "Entity A details"},
+                {"content": "Entity B details"},
+            ]
+        )
+
+        contextual_memory = ContextualMemory(
+            stm=None,
+            ltm=None,
+            em=mock_em,
+            exm=None,
+        )
+
+        result = await contextual_memory._afetch_entity_context("test query")
+
+        assert "Entities:" in result
+        assert "- Entity A details" in result
+        assert "- Entity B details" in result
+
+    @pytest.mark.asyncio
+    async def test_afetch_external_context_returns_formatted_results(self):
+        """Test that _afetch_external_context returns properly formatted results."""
+        mock_exm = MagicMock(spec=ExternalMemory)
+        mock_exm.asearch = AsyncMock(
+            return_value=[
+                {"content": "External data 1"},
+                {"content": "External data 2"},
+            ]
+        )
+
+        contextual_memory = ContextualMemory(
+            stm=None,
+            ltm=None,
+            em=None,
+            exm=mock_exm,
+        )
+
+        result = await contextual_memory._afetch_external_context("test query")
+
+        assert "External memories:" in result
+        assert "- External data 1" in result
+        assert "- External data 2" in result
+
+    @pytest.mark.asyncio
+    async def test_afetch_methods_return_empty_for_empty_results(self):
+        """Test that async fetch methods return empty string for no results."""
+        mock_stm = MagicMock(spec=ShortTermMemory)
+        mock_stm.asearch = AsyncMock(return_value=[])
+
+        mock_ltm = MagicMock(spec=LongTermMemory)
+        mock_ltm.asearch = AsyncMock(return_value=[])
+
+        mock_em = MagicMock(spec=EntityMemory)
+        mock_em.asearch = AsyncMock(return_value=[])
+
+        mock_exm = MagicMock(spec=ExternalMemory)
+        mock_exm.asearch = AsyncMock(return_value=[])
+
+        contextual_memory = ContextualMemory(
+            stm=mock_stm,
+            ltm=mock_ltm,
+            em=mock_em,
+            exm=mock_exm,
+        )
+
+        stm_result = await contextual_memory._afetch_stm_context("query")
+        ltm_result = await contextual_memory._afetch_ltm_context("task")
+        em_result = await contextual_memory._afetch_entity_context("query")
+        exm_result = await contextual_memory._afetch_external_context("query")
+
+        assert stm_result == ""
+        assert ltm_result is None
+        assert em_result == ""
+        assert exm_result == ""