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agent-craft/m02_llm_fundamentals/s03_llm_temperature.py
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Python

from config import OPENAI_API_KEY
from openai import OpenAI
client = OpenAI(api_key=OPENAI_API_KEY, base_url="https://api.deepseek.com")
msg = [{"role": "user", "content": "请用一句话生动形象地描述量子力学的奇妙之处。"}]
response_low_temperature = client.chat.completions.create(
model="deepseek-chat",
messages=[
{"role": "system", "content": "你是一个科学解说员,请用生动形象的语言回答问题。"}, # 提示词角色
{"role": "user", "content": "请用一句话描述量子力学的奇妙之处。"}, # 用户输入的对话
],
temperature=0.1
)
response_high_temperature = client.chat.completions.create(
model="deepseek-chat",
messages=[
{"role": "system", "content": "你是一个科学解说员,请用生动形象的语言回答问题。"}, # 提示词角色
{"role": "user", "content": "请用一句话描述量子力学的奇妙之处。"}, # 用户输入的对话
],
temperature=1.3
)
# 测试1:低温度 (稳定)
print(f"温度 0.1: {response_low_temperature.choices[0].message.content}")
# 测试2:高温度 (随机)
print(f"温度 1.3: {response_high_temperature.choices[0].message.content}")