from typing import List
from agno.agent import Agent, RunResponse # noqa
from agno.models.deepseek import DeepSeek
from pydantic import BaseModel, Field
from rich.pretty import pprint # noqa
class MovieScript(BaseModel):
setting: str = Field(
..., description="为一部大片提供一个精彩的场景。"
)
ending: str = Field(
...,
description="电影的结局。如果没有,请提供一个美好结局。",
)
genre: str = Field(
...,
description="电影的类型。如果没有,请选择动作、惊悚或浪漫喜剧。",
)
name: str = Field(..., description="给这部电影起个名字")
characters: List[str] = Field(..., description="这部电影的角色名字。")
storyline: str = Field(
..., description="这部电影三句话的剧情。要写得激动人心!"
)
json_mode_agent = Agent(
model=DeepSeek(id="deepseek-chat"),
description="你帮助人们写电影剧本。",
response_model=MovieScript,
)
# Get the response in a variable
# json_mode_response: RunResponse = json_mode_agent.run("New York")
# pprint(json_mode_response.content)
json_mode_agent.print_response("New York")
创建虚拟环境
打开 Terminal
并创建一个 python 虚拟环境。
python3 -m venv .venv
source .venv/bin/activate
设置您的 API 密钥
export DEEPSEEK_API_KEY=xxx
安装库
pip install -U openai agno
运行 Agent
python cookbook/models/deepseek/structured_output.py