Source code for langchain_experimental.autonomous_agents.autogpt.memory
from typing import Any, Dict, List
from langchain.memory.chat_memory import BaseChatMemory
from langchain.memory.utils import get_prompt_input_key
from langchain_core.vectorstores import VectorStoreRetriever
from pydantic import Field
[docs]
class AutoGPTMemory(BaseChatMemory):
"""Memory for AutoGPT."""
retriever: VectorStoreRetriever = Field(exclude=True)
"""VectorStoreRetriever object to connect to."""
@property
def memory_variables(self) -> List[str]:
return ["chat_history", "relevant_context"]
def _get_prompt_input_key(self, inputs: Dict[str, Any]) -> str:
"""Get the input key for the prompt."""
if self.input_key is None:
return get_prompt_input_key(inputs, self.memory_variables)
return self.input_key
[docs]
def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
input_key = self._get_prompt_input_key(inputs)
query = inputs[input_key]
docs = self.retriever.invoke(query)
return {
"chat_history": self.chat_memory.messages[-10:],
"relevant_context": docs,
}