DeepSeek
本篇主要介绍如何快速集成DeepSeek API 接入到应用中示例，废话不多说，上图上代码。
最下面有GitHub代码仓库，由于篇幅限制，更多代码示例都放在仓库里面。
代码示例-图：
企业微信截图_17398478001146.png
安装Python依赖
确保你已经安装了Python 3.8或更高版本。你可以从Python官方网站下载并安装。
pip3 install openai
# or
pip install -r requirements.txt
DeepSeek API 示例
对话 API
简单示例-场景：多轮对话
from openai import OpenAI
# DeepSeek API 是一个“无状态” API，即服务端不记录用户请求的上下文，用户在每次请求时，需将之前所有对话历史拼接好后，传递给对话 API。
client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")
# Round 1
messages = [{"role": "user", "content": "What's the highest mountain in the world?"}]
# messages = [{"role": "user", "content": "世界上最高的山是什么?"}]
response = client.chat.completions.create(
model="deepseek-chat",
messages=messages
)
messages.append(response.choices[0].message)
print(f"Messages Round 1: {messages}")
# Round 2
messages.append({"role": "user", "content": "What is the second?"})
# messages.append({"role": "user", "content": "第二个是什么?"})
response = client.chat.completions.create(
model="deepseek-chat",
messages=messages
)
messages.append(response.choices[0].message)
print(f"Messages Round 2: {messages}")
简单示例-场景：个人助手
# Please install OpenAI SDK first: `pip3 install openai`
from openai import OpenAI
# client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")
client = OpenAI(api_key="sk-62aa54bcf5b2478e88c4bcd4c6d852d1", base_url="https://api.deepseek.com")
response = client.chat.completions.create(
model="deepseek-chat",
messages=[
# 系统角色：可以根据系统角色输入的语言，来判断回答的内容是 `英文or中文`
# {"role": "system", "content": "You are a helpful assistant"},
{"role": "system", "content": "你是个乐于助人的助手"},
# 用户角色
# {"role": "user", "content": "Hello"},
{"role": "user", "content": "你好"},
],
stream=False
)
print(response.choices[0].message.content)
推理 API
推理-非流式：
from openai import OpenAI
# client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")
client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")
# Round 1
messages = [{"role": "user", "content": "9.11 and 9.8, which is greater?"}]
response = client.chat.completions.create(
model="deepseek-reasoner",
messages=messages
)
reasoning_content = response.choices[0].message.reasoning_content
content = response.choices[0].message.content
# Round 2
messages.append({'role': 'assistant', 'content': content})
messages.append({'role': 'user', 'content': "How many Rs are there in the word 'strawberry'?"})
response = client.chat.completions.create(
model="deepseek-reasoner",
messages=messages
)
# ...
流式-推理：
from openai import OpenAI
# client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")
client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")
# Round 1
messages = [{"role": "user", "content": "9.11 and 9.8, which is greater?"}]
response = client.chat.completions.create(
model="deepseek-reasoner",
messages=messages,
stream=True
)
reasoning_content = ""
content = ""
for chunk in response:
if chunk.choices[0].delta.reasoning_content:
reasoning_content += chunk.choices[0].delta.reasoning_content
else:
content += chunk.choices[0].delta.content
# Round 2
messages.append({"role": "assistant", "content": content})
messages.append({'role': 'user', 'content': "How many Rs are there in the word 'strawberry'?"})
response = client.chat.completions.create(
model="deepseek-reasoner",
messages=messages,
stream=True
)
# ...
代码仓库-更多示例
示例：
企业微信截图_1739847856153.png
