Anthropic SDK

import anthropic

client = anthropic.Anthropic()

message = client.messages.create(
    model="MiniMax-M3.1-Flash-Preview",
    output_config={"effort": "max"},
    max_tokens=4096,
    system="You are a helpful assistant.",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Hi, how are you?"
                }
            ]
        }
    ]
)

for block in message.content:
    if block.type == "thinking":
        print(f"Thinking:\n{block.thinking}\n")
    elif block.type == "text":
        print(f"Text:\n{block.text}\n")

curl https://api.minimax.cn/anthropic/v1/messages \
  -H "Authorization: Bearer <MINIMAX_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "MiniMax-M3.1-Flash-Preview",
    "max_tokens": 2048,
    "output_config": { "effort": "max" },
    "messages": [{ "role": "user", "content": "Hi, how are you?" }]
  }'

import anthropic

client = anthropic.Anthropic()

print("Starting stream response...\n")
print("=" * 60)
print("Thinking Process:")
print("=" * 60)

stream = client.messages.create(
    model="MiniMax-M3.1-Flash-Preview",
    output_config={"effort": "max"},
    max_tokens=4096,
    system="You are a helpful assistant.",
    messages=[
        {"role": "user", "content": [{"type": "text", "text": "Hi, how are you?"}]}
    ],
    stream=True,
)

reasoning_buffer = ""
text_buffer = ""

for chunk in stream:
    if chunk.type == "content_block_start":
        if hasattr(chunk, "content_block") and chunk.content_block:
            if chunk.content_block.type == "text":
                print("\n" + "=" * 60)
                print("Response Content:")
                print("=" * 60)

    elif chunk.type == "content_block_delta":
        if hasattr(chunk, "delta") and chunk.delta:
            if chunk.delta.type == "thinking_delta":
                # 流式输出 thinking 过程
                new_thinking = chunk.delta.thinking
                if new_thinking:
                    print(new_thinking, end="", flush=True)
                    reasoning_buffer += new_thinking
            elif chunk.delta.type == "text_delta":
                # 流式输出文本内容
                new_text = chunk.delta.text
                if new_text:
                    print(new_text, end="", flush=True)
                    text_buffer += new_text

print("\n")