从一个菜鸟到老司机：DeepSeek V4 API 接入最全实战指南

# ❌ 错误做法
api_key = "sk-1234567890abcdef"

# ✅ 正确做法
import os
api_key = os.getenv("DEEPSEEK_API_KEY")

# Python 环境
python3 -m venv deepseek-env
source deepseek-env/bin/activate
pip install deepseek-sdk

# 或直接使用 requests
pip install requests python-dotenv

npm install deepseek-node
# 或
npm install axios dotenv

import os
from dotenv import load_dotenv
from deepseek import DeepSeek

load_dotenv()

client = DeepSeek(
    api_key=os.getenv("DEEPSEEK_API_KEY"),
    base_url="https://api.deepseek.com/v1"
)

response = client.chat.completions.create(
    model="deepseek-chat",
    messages=[
        {"role": "system", "content": "你是一个专业的技术助手。"},
        {"role": "user", "content": "请介绍一下 DeepSeek V4 的主要特点。"}
    ],
    temperature=0.7,
    max_tokens=1000
)

print(response.choices[0].message.content)

DeepSeek V4 是深度求索公司开发的新一代开源大语言模型，具有以下主要特点：
1. 开源免费：采用 Apache 2.0 许可证，可自由商用
2. 中文优化：针对中文语境深度训练，中文理解能力出色
3. 长上下文支持：支持 128K Token，可处理超长文档
4. 高性价比：API 价格仅为 GPT-4 的 1/10
5. 多语言能力：支持 100+ 种语言，适合国际化应用

curl https://api.deepseek.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $DEEPSEEK_API_KEY" \
  -d '{
    "model": "deepseek-chat",
    "messages": [
      {"role": "system", "content": "你是一个专业的技术助手。"},
      {"role": "user", "content": "请介绍一下 DeepSeek V4 的主要特点。"}
    ],
    "temperature": 0.7,
    "max_tokens": 1000
  }'

{
  "id": "chatcmpl-123456",
  "object": "chat.completion",
  "created": 1714032000,
  "model": "deepseek-chat",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "DeepSeek V4 是..."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 50,
    "completion_tokens": 200,
    "total_tokens": 250
  }
}

messages = [
    {"role": "system", "content": "系统指令，设定 AI 角色和行为"},
    {"role": "user", "content": "用户输入的问题或指令"},
    {"role": "assistant", "content": "AI 的回复（用于多轮对话）"},
    {"role": "user", "content": "用户的追问"}
]

# 1. 检查 Key 是否加载成功
import os
print(os.getenv("DEEPSEEK_API_KEY"))

# 2. 检查 Key 格式（应以 sk- 开头）
assert api_key.startswith("sk-"), "API Key 格式错误"

# 3. 检查 Key 前后是否有空格或换行符
api_key = api_key.strip()

# 输入 500 tokens，输出 1000 tokens
input_cost = 500 / 1000 * 0.001    # ¥0.0005
output_cost = 1000 / 1000 * 0.002  # ¥0.002
total = input_cost + output_cost    # ¥0.0025

print(f"本次调用成本：¥{total}")

from deepseek import DeepSeek
import os

client = DeepSeek(api_key=os.getenv("DEEPSEEK_API_KEY"))

stream = client.chat.completions.create(
    model="deepseek-chat",
    messages=[{"role": "user", "content": "请写一首关于春天的诗。"}],
    stream=True  # 关键参数
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

import asyncio
from deepseek import AsyncDeepSeek
import time

async def test_concurrent():
    client = AsyncDeepSeek(api_key=os.getenv("DEEPSEEK_API_KEY"))
    start = time.time()

    tasks = [client.chat.completions.create(
        model="deepseek-chat",
        messages=[{"role": "user", "content": f"问题 {i+1}"}]
    ) for i in range(10)]

    responses = await asyncio.gather(*tasks)
    total = time.time() - start

    print(f"10 个并发请求总耗时：{total:.2f}秒")
    print(f"平均每个请求耗时：{total/10:.2f}秒")

asyncio.run(test_concurrent())

import os
from dotenv import load_dotenv
from deepseek import DeepSeek
import logging

load_dotenv()
logger = logging.getLogger(__name__)

# 封装客户端（设置超时和重试）
client = DeepSeek(
    api_key=os.getenv("DEEPSEEK_API_KEY"),
    timeout=30,
    max_retries=3
)

# 添加异常处理
try:
    response = client.chat.completions.create(
        model="deepseek-chat",
        messages=[{"role": "user", "content": "你好"}],
        temperature=0.7,
        max_tokens=500
    )
    print(response.choices[0].message.content)
except Exception as e:
    logger.error(f"API 调用失败: {e}")
    # 降级策略：返回默认回复或使用缓存

# 记录日志
logger.info(f"Token 使用: prompt={response.usage.prompt_tokens}, "
            f"completion={response.usage.completion_tokens}")