.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "build_tutorial/prompt.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_build_tutorial_prompt.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_build_tutorial_prompt.py:


.. _prompt-engineering:

提示工程
================================

提示工程是构建大语言模型应用的关键步骤，尤其是针对多智能体的应用。
然而，目前市面上大多数 API 服务只专注于 Chat 场景，即对话只有两个参与者：用户（user）和
助手（assistant），并且两者必须交替发送消息。

为了支持多智能体应用，AgentScope 构建了不同的提示策略，从而将一组 `Msg` 对象转换为模型
API 需要的格式。

.. note:: 目前还没有一种提示工程可以做到一劳永逸。AgentScope 内置提示构建策略的目标
 是让初学者可以顺利调用模型 API,而不是达到最佳性能。
 对于高级用户，我们建议开发人员根据需求和模型 API 要求来自定义提示构建策略。

提示构建策略
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

内置提示策略在模型类的 `format` 方法中实现。以 DashScope Chat API 为例:

.. GENERATED FROM PYTHON SOURCE LINES 25-47

.. code-block:: Python


    from agentscope.models import DashScopeChatWrapper
    from agentscope.message import Msg
    import json


    model = DashScopeChatWrapper(
        config_name="_",
        model_name="qwen-max",
    )

    # 可以将 `Msg` 对象或 `Msg` 对象列表传递给 `format` 方法
    prompt = model.format(
        Msg("system", "You're a helpful assistant.", "system"),
        [
            Msg("assistant", "Hi!", "assistant"),
            Msg("user", "Nice to meet you!", "user"),
        ],
    )

    print(json.dumps(prompt, indent=4, ensure_ascii=False))





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    [
        {
            "role": "system",
            "content": "You're a helpful assistant."
        },
        {
            "role": "user",
            "content": "## Conversation History\nassistant: Hi!\nuser: Nice to meet you!"
        }
    ]




.. GENERATED FROM PYTHON SOURCE LINES 48-50

格式化输入消息后，我们可以将其传给 `model` 对象，进行实际的 API 调用。


.. GENERATED FROM PYTHON SOURCE LINES 50-55

.. code-block:: Python


    response = model(prompt)

    print(response.text)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Nice to meet you too! How can I assist you today?




.. GENERATED FROM PYTHON SOURCE LINES 56-134

非视觉模型
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

在下表中，我们列出了内置的提示策略，以及支持的大语言模型的前缀。

以下面的消息为例:

.. code-block:: python

    Msg("system", "You're a helpful assistant named Alice.", "system"),
    Msg("Alice", "Hi!", "assistant"),
    Msg("Bob", "Nice to meet you!", "user")


.. list-table::
    :header-rows: 1

    * - LLMs
      - `model_name`
      - Constructed Prompt
    * - OpenAI LLMs
      - `gpt-`
      - .. code-block:: python

            [
                {
                    "role": "system",
                    "name": "system",
                    "content": "You're a helpful assistant named Alice."
                },
                {
                    "role": "user",
                    "name": "Alice",
                    "content": "Hi!"
                },
                {
                    "role": "user",
                    "name": "Bob",
                    "content": "Nice to meet you!"
                }
            ]
    * - Gemini LLMs
      - `gemini-`
      - .. code-block:: python

            [
                {
                    "role": "user",
                    "parts": [
                        "You're a helpful assistant named Alice.\\n## Conversation History\\nAlice: Hi!\\nBob: Nice to meet you!"
                    ]
                }
            ]
    * - All other LLMs

        (e.g. DashScope, ZhipuAI ...)
      -
      - .. code-block:: python

            [
                {
                    "role": "system",
                    "content": "You're a helpful assistant named Alice."
                },
                {
                    "role": "user",
                    "content": "## Conversation History\\nAlice: Hi!\\nBob: Nice to meet you!"
                }
            ]

.. tip:: 考虑到一些 API 兼容不同的大语言模型（例如 OpenAI Python 库），AgentScope 使用 `model_name` 字段来区分不同的模型并决定最终使用的策略。

视觉模型
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

对于视觉模型，AgentScope 目前支持 OpenAI 视觉模型和 Dashscope 多模态 API。
未来将假如更多的视觉模型的支持。



.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 1.985 seconds)


.. _sphx_glr_download_build_tutorial_prompt.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: prompt.ipynb <prompt.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: prompt.py <prompt.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: prompt.zip <prompt.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_