forked from agent-lab/smolagents
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4.6 KiB
Markdown
131 lines
No EOL
4.6 KiB
Markdown
# 📚 管理Agent的记忆
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[[open-in-colab]]
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归根结底，Agent可以定义为由几个简单组件构成：它拥有工具、提示词。最重要的是，它具备对过往步骤的记忆，能够追溯完整的规划、执行和错误历史。
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### 回放Agent的记忆
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我们提供了多项功能来审查Agent的过往运行记录。
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您可以通过插装（instrumentation）在可视化界面中查看Agent的运行过程，该界面支持对特定步骤进行缩放操作，具体方法参见[插装指南](./inspect_runs)。
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您也可以使用`agent.replay()`方法实现回放：
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当Agent完成运行后：
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```py
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from smolagents import InferenceClientModel, CodeAgent
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agent = CodeAgent(tools=[], model=InferenceClientModel(), verbosity_level=0)
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result = agent.run("What's the 20th Fibonacci number?")
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```
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若要回放最近一次运行，只需使用：
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```py
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agent.replay()
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```
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### 动态修改Agent的记忆
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许多高级应用场景需要对Agent的记忆进行动态修改。
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您可以通过以下方式访问Agent的记忆：
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```py
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from smolagents import ActionStep
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system_prompt_step = agent.memory.system_prompt
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print("The system prompt given to the agent was:")
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print(system_prompt_step.system_prompt)
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task_step = agent.memory.steps[0]
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print("\n\nThe first task step was:")
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print(task_step.task)
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for step in agent.memory.steps:
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if isinstance(step, ActionStep):
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if step.error is not None:
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print(f"\nStep {step.step_number} got this error:\n{step.error}\n")
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else:
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print(f"\nStep {step.step_number} got these observations:\n{step.observations}\n")
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```
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使用`agent.memory.get_full_steps()`可获取完整步骤字典数据。
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您还可以通过步骤回调（step callbacks）实现记忆的动态修改。
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步骤回调函数可通过参数直接访问`agent`对象，因此能够访问所有记忆步骤并根据需要进行修改。例如，假设您正在监控网页浏览Agent每个步骤的屏幕截图，希望保留最新截图同时删除旧步骤的图片以节省token消耗。
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可参考以下代码示例：
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_注：此代码片段不完整，部分导入语句和对象定义已精简，完整代码请访问[原始脚本](https://github.com/huggingface/smolagents/blob/main/src/smolagents/vision_web_browser.py)_
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```py
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import helium
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from PIL import Image
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from io import BytesIO
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from time import sleep
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def update_screenshot(memory_step: ActionStep, agent: CodeAgent) -> None:
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sleep(1.0) # Let JavaScript animations happen before taking the screenshot
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driver = helium.get_driver()
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latest_step = memory_step.step_number
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for previous_memory_step in agent.memory.steps: # Remove previous screenshots from logs for lean processing
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if isinstance(previous_memory_step, ActionStep) and previous_memory_step.step_number <= latest_step - 2:
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previous_memory_step.observations_images = None
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png_bytes = driver.get_screenshot_as_png()
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image = Image.open(BytesIO(png_bytes))
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memory_step.observations_images = [image.copy()]
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```
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最后在初始化Agent时，将此函数传入`step_callbacks`参数：
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```py
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CodeAgent(
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tools=[WebSearchTool(), go_back, close_popups, search_item_ctrl_f],
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model=model,
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additional_authorized_imports=["helium"],
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step_callbacks=[update_screenshot],
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max_steps=20,
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verbosity_level=2,
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)
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```
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请访问我们的 [vision web browser code](https://github.com/huggingface/smolagents/blob/main/src/smolagents/vision_web_browser.py) 查看完整可运行示例。
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### 分步运行 Agents
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当您需要处理耗时数天的工具调用时，这种方式特别有用：您可以逐步执行Agents。这还允许您在每一步更新记忆。
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```py
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from smolagents import InferenceClientModel, CodeAgent, ActionStep, TaskStep
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agent = CodeAgent(tools=[], model=InferenceClientModel(), verbosity_level=1)
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print(agent.memory.system_prompt)
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task = "What is the 20th Fibonacci number?"
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# You could modify the memory as needed here by inputting the memory of another agent.
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# agent.memory.steps = previous_agent.memory.steps
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# Let's start a new task!
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agent.memory.steps.append(TaskStep(task=task, task_images=[]))
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final_answer = None
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step_number = 1
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while final_answer is None and step_number <= 10:
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memory_step = ActionStep(
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step_number=step_number,
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observations_images=[],
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)
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# Run one step.
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final_answer = agent.step(memory_step)
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agent.memory.steps.append(memory_step)
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step_number += 1
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# Change the memory as you please!
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# For instance to update the latest step:
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# agent.memory.steps[-1] = ...
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print("The final answer is:", final_answer)
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``` |