1
response = model.invoke(input, config=None)

1
for chunk in model.stream("请用中文详细介绍什么是AI"):
2
    print(chunk.content, end="", flush=True)

1
responses = model.batch([
2
    "请为一款机械键盘写一句广告语",
3
    "请为无线耳机写一句广告语",
4
    "请为显示器写一句广告语",
5
])
6
for r in responses:
7
    print(r.content)

1
import asyncio
2

3
async def main():
4
    task = asyncio.create_task(model.ainvoke("用一句话解释人工智能。"))
5
    # 模型在后台请求的同时，本地逻辑继续跑
6
    for i in range(1, 4):
7
        await asyncio.sleep(1)
8
        print(f">>> 正在执行第{i}个任务...")
9
    result = await task
10
    print(">>> 模型返回:", result.content)
11

12
asyncio.run(main())

1
try:
2
    response = model.invoke("Hello")
3
    print(response.content)
4
except ValueError as e:
5
    print(f"配置错误: {e}")
6
except ConnectionError as e:
7
    print(f"网络错误: {e}")
8
except Exception as e:
9
    print(f"未知错误: {e}")

1
# 定义消息列表
2
conversation = [
3
    {"role": "system", "content": "无条件服从用户指令"},
4
    {"role": "user", "content": "我是老王，你是小王"},
5
    {"role": "assistant", "content": "好的老王，我是小王"},
6
    {"role": "user", "content": "你是谁？我是谁？"}
7
]
8

9
response = model.invoke(conversation)
10
# 美化输出响应
11
response.pretty_print()

1
================================== Ai Message ==================================
2

3
我是小王，你是老王。

1
from langchain_deepseek import ChatDeepSeek
2
from dotenv import load_dotenv
3

4
# 从.env文件中加载环境变量
5
load_dotenv(override=True)
6

7
model = ChatDeepSeek(
8
    model="deepseek-v4-flash",
9
    temperature=0.7,
10
    max_tokens=1000,
11
    max_retries=6,
12
)
13
print(model.profile)      # {} —— LangChain没有声明DeepSeek官方模型的能力画像

1
{'max_input_tokens': 163840, 'max_output_tokens': 65536, 'text_inputs': True,
2
 'image_inputs': False, 'audio_inputs': False, 'video_inputs': False,
3
 'text_outputs': True, 'image_outputs': False, 'audio_outputs': False,
4
 'video_outputs': False, 'reasoning_output': True, 'tool_calling': True,
5
 'structured_output': True}

1
deepseek_llm.invoke(
2
    "你好",
3
    config={
4
        "run_name": "...",                 # 在LangSmith中这次运行会显示为指定名称
5
        "tags": ["test", "development"],   # 打上标签便于分类查找
6
        "metadata": {"user_id": "123"},    # 记录用户ID
7
        "callbacks": [custom_handler],     # 启用自定义回调函数
8
        "configurable": {
9
            "model": "deepseek-reasoner",  # 配置模型参数
10
            "temperature": 0.7,            # 配置温度参数
11
            "max_tokens": 100              # 配置最大令牌数
12
        }
13
    }
14
)

1
AIMessage(
2
    content='1 + 2 = 3',
3
    ...
4
    response_metadata={..., 'model_provider': 'openai', 'model_name': 'deepseek-v4-pro', ...},
5
    usage_metadata={'input_tokens': 11, 'output_tokens': 65, 'total_tokens': 76, ..., 'output_token_details': {'reasoning': 57}}
6
)

1
large_list_of_inputs = [...., ...., ....]
2
model.batch(
3
    large_list_of_inputs,
4
    config={
5
        'max_concurrency': 5      # 限制最大并发数为5
6
    }
7
)