update experimental (#8402)

some changes were made to experimental, porting them over

libs/experimental/langchain_experimental/generative_agents/generative_agent.py

@@ -11,11 +11,10 @@ from langchain_experimental.generative_agents.memory import GenerativeAgentMemor
 
 
 class GenerativeAgent(BaseModel):
-    """A character with memory and innate characteristics."""
+    """An Agent as a character with memory and innate characteristics."""
 
     name: str
     """The character's name."""
-
     age: Optional[int] = None
     """The optional age of the character."""
     traits: str = "N/A"
@@ -29,13 +28,10 @@ class GenerativeAgent(BaseModel):
     verbose: bool = False
     summary: str = ""  #: :meta private:
     """Stateful self-summary generated via reflection on the character's memory."""
-
     summary_refresh_seconds: int = 3600  #: :meta private:
     """How frequently to re-generate the summary."""
-
     last_refreshed: datetime = Field(default_factory=datetime.now)  # : :meta private:
     """The last time the character's summary was regenerated."""
-
     daily_summaries: List[str] = Field(default_factory=list)  # : :meta private:
     """Summary of the events in the plan that the agent took."""
 

libs/experimental/langchain_experimental/generative_agents/memory.py

@@ -14,24 +14,21 @@ logger = logging.getLogger(__name__)
 
 
 class GenerativeAgentMemory(BaseMemory):
+    """Memory for the generative agent."""
+
     llm: BaseLanguageModel
     """The core language model."""
-
     memory_retriever: TimeWeightedVectorStoreRetriever
     """The retriever to fetch related memories."""
     verbose: bool = False
-
     reflection_threshold: Optional[float] = None
     """When aggregate_importance exceeds reflection_threshold, stop to reflect."""
-
     current_plan: List[str] = []
     """The current plan of the agent."""
-
     # A weight of 0.15 makes this less important than it
     # would be otherwise, relative to salience and time
     importance_weight: float = 0.15
     """How much weight to assign the memory importance."""
-
     aggregate_importance: float = 0.0  # : :meta private:
     """Track the sum of the 'importance' of recent memories.