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fix: add type annotations to contextual_memory.py

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This commit is contained in:
Greyson LaLonde
2025-09-05 09:57:02 -04:00
parent a414e7f2a7
commit e93d597721
1 changed files with 21 additions and 17 deletions
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38
src/crewai/memory/contextual/contextual_memory.py
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@@ -1,4 +1,6 @@
from typing import TYPE_CHECKING, Optional
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Optional
from crewai.memory import (
EntityMemory,
@@ -19,8 +21,8 @@ class ContextualMemory:
ltm: LongTermMemory,
em: EntityMemory,
exm: ExternalMemory,
agent: Optional["Agent"] = None,
task: Optional["Task"] = None,
agent: Optional[Agent] = None,
task: Optional[Task] = None,
):
self.stm = stm
self.ltm = ltm
@@ -42,7 +44,7 @@ class ContextualMemory:
self.exm.agent = self.agent
self.exm.task = self.task
def build_context_for_task(self, task, context) -> str:
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.
@@ -52,14 +54,14 @@ class ContextualMemory:
if query == "":
return ""
context = []
context.append(self._fetch_ltm_context(task.description))
context.append(self._fetch_stm_context(query))
context.append(self._fetch_entity_context(query))
context.append(self._fetch_external_context(query))
return "\n".join(filter(None, context))
context_parts = []
context_parts.append(self._fetch_ltm_context(task.description))
context_parts.append(self._fetch_stm_context(query))
context_parts.append(self._fetch_entity_context(query))
context_parts.append(self._fetch_external_context(query))
return "\n".join(filter(None, context_parts))
def _fetch_stm_context(self, query) -> str:
def _fetch_stm_context(self, query: str) -> str:
"""
Fetches recent relevant insights from STM related to the task's description and expected_output,
formatted as bullet points.
@@ -74,7 +76,7 @@ class ContextualMemory:
)
return f"Recent Insights:\n{formatted_results}" if stm_results else ""
def _fetch_ltm_context(self, task) -> Optional[str]:
def _fetch_ltm_context(self, task: str) -> Optional[str]:
"""
Fetches historical data or insights from LTM that are relevant to the task's description and expected_output,
formatted as bullet points.
@@ -90,14 +92,16 @@ class ContextualMemory:
formatted_results = [
suggestion
for result in ltm_results
for suggestion in result["metadata"]["suggestions"] # type: ignore # Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
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]")
formatted_results_str = "\n".join(
[f"- {result}" for result in formatted_results]
)
return f"Historical Data:\n{formatted_results}" if ltm_results else ""
return f"Historical Data:\n{formatted_results_str}" if ltm_results else ""
def _fetch_entity_context(self, query) -> str:
def _fetch_entity_context(self, query: str) -> str:
"""
Fetches relevant entity information from Entity Memory related to the task's description and expected_output,
formatted as bullet points.
@@ -107,7 +111,7 @@ class ContextualMemory:
em_results = self.em.search(query)
formatted_results = "\n".join(
[f"- {result['context']}" for result in em_results] # type: ignore # Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
[f"- {result['context']}" for result in em_results]
)
return f"Entities:\n{formatted_results}" if em_results else ""