【AI大模型应用开发】MemGPT原理与快速上手：这可能是目前管理大模型记忆的最专业的框架和思路

# Check the memory pressure and potentially issue a memory pressure warning
current_total_tokens = response.usage.total_tokens
active_memory_warning = False
# We can't do summarize logic properly if context_window is undefined
if self.agent_state.llm_config.context_window is None:
    # Fallback if for some reason context_window is missing, just set to the default
    print(f"{CLI_WARNING_PREFIX}could not find context_window in config, setting to default {LLM_MAX_TOKENS['DEFAULT']}")
    print(f"{self.agent_state}")
    self.agent_state.llm_config.context_window = (
        LLM_MAX_TOKENS[self.model] if (self.model is not None and self.model in LLM_MAX_TOKENS) else LLM_MAX_TOKENS["DEFAULT"]
    )
if current_total_tokens > MESSAGE_SUMMARY_WARNING_FRAC * int(self.agent_state.llm_config.context_window):
    printd(
        f"{CLI_WARNING_PREFIX}last response total_tokens ({current_total_tokens}) > {MESSAGE_SUMMARY_WARNING_FRAC * int(self.agent_state.llm_config.context_window)}"
    )
    # Only deliver the alert if we haven't already (this period)
    if not self.agent_alerted_about_memory_pressure:
        active_memory_warning = True
        self.agent_alerted_about_memory_pressure = True  # it's up to the outer loop to handle this
else:
    printd(
        f"last response total_tokens ({current_total_tokens}) < {MESSAGE_SUMMARY_WARNING_FRAC * int(self.agent_state.llm_config.context_window)}"
    )

pip install -U pymemgpt

memgpt run

/exit: Exit the CLI
/attach: Attach a loaded data source to the agent
/save: Save a checkpoint of the current agent/conversation state
/dump: View the current message log (see the contents of main context)
/dump <count>: View the last messages (all if is omitted)
/memory: Print the current contents of agent memory
/pop: Undo the last message in the conversation
/pop <count>: Undo the last messages in the conversation. It defaults to 3, which usually is one turn around in the conversation
/retry: Pops the last answer and tries to get another one
/rethink <text>: Will replace the inner dialog of the last assistant message with the <text> to help shaping the conversation
/rewrite: Will replace the last assistant answer with the given text to correct or force the answer
/heartbeat: Send a heartbeat system message to the agent
/memorywarning: Send a memory warning system message to the agent

git clone https://github.com/cpacker/MemGPT.git
cd MemGPT
pip install -e .

# 加载 .env 到环境变量
from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv())
from memgpt import create_client
# Connect to the server as a user
client = create_client()
# Create an agent
agent_info = client.create_agent(
  name="my_agent", 
  persona="You are a friendly agent.", 
  human="Bob is a friendly human."
)
# Send a message to the agent
messages = client.user_message(agent_id=agent_info.id, message="Hello, agent!")