原生 Claude 格式

curl -N -X POST "https://api.gravitex.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-sonnet-4-5-20250929",
    "max_tokens": 1024,
    "stream": true,
    "messages": [
      {"role": "user", "content": "请用中文简要介绍人工智能"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.gravitex.ai"
)

# 非流式
message = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "请用中文简要介绍人工智能"}
    ]
)
print(message.content[0].text)

# 流式
with client.messages.stream(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "请用中文简要介绍人工智能"}
    ]
) as stream:
    for text_block in stream.text_stream:
        print(text_block, end="")

curl -X POST "https://api.gravitex.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-sonnet-4-5-20250929",
    "max_tokens": 1024,
    "system": [
      {"type": "text", "text": "你是一个有用的助手，擅长用中文回答问题。"}
    ],
    "messages": [
      {"role": "user", "content": "什么是机器学习？"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.gravitex.ai"
)

with client.messages.stream(
    model="claude-sonnet-4-5-20250929",
    max_tokens=4096,
    thinking={
        "type": "enabled",
        "budget_tokens": 4096
    },
    temperature=1.0,
    top_p=0,
    messages=[
        {"role": "user", "content": "给出一道中等难度的几何题并分步解析"}
    ]
) as stream:
    for event in stream:
        if event.type == "content_block_delta":
            if hasattr(event.delta, "thinking"):
                # 思考过程
                print(f"[思考] {event.delta.thinking}", end="")
            elif hasattr(event.delta, "text"):
                # 最终答案
                print(event.delta.text, end="")

curl -X POST "https://api.gravitex.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-sonnet-4-5-20250929",
    "max_tokens": 1024,
    "tools": [
      {
        "type": "web_search_20250305",
        "name": "web_search"
      }
    ],
    "messages": [
      {"role": "user", "content": "最近关于人工智能的新闻有哪些？"}
    ]
  }'

curl -X POST "https://api.gravitex.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-sonnet-4-5-20250929",
    "max_tokens": 1024,
    "tools": [
      {
        "type": "web_search_20250305",
        "name": "web_search",
        "max_uses": 5
      }
    ],
    "messages": [
      {"role": "user", "content": "搜索一下今天北京的天气"}
    ]
  }'

curl -X POST "https://api.gravitex.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-sonnet-4-5-20250929",
    "max_tokens": 1024,
    "tools": [
      {
        "type": "web_search_20250305",
        "name": "web_search",
        "max_uses": 5,
        "user_location": {
          "type": "approximate",
          "timezone": "Asia/Shanghai",
          "country": "CN",
          "region": "Beijing",
          "city": "Beijing"
        }
      }
    ],
    "messages": [
      {"role": "user", "content": "上海今天的天气怎么样？"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.gravitex.ai"
)

message = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    tools=[
        {
            "type": "web_search_20250305",
            "name": "web_search",
            "max_uses": 5
        }
    ],
    messages=[
        {"role": "user", "content": "最近关于人工智能的新闻有哪些？"}
    ]
)
print(message.content[0].text)

{
  "id": "msg_xxx",
  "content": [
    {
      "type": "tool_use",
      "id": "toolu_xxx",
      "name": "get_weather",
      "input": {"city": "上海"}
    }
  ],
  "stop_reason": "tool_use"
}

curl -X POST "https://api.gravitex.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-sonnet-4-5-20250929",
    "max_tokens": 1024,
    "tools": [...],
    "messages": [
      {"role": "user", "content": "上海的天气怎么样？"},
      {
        "role": "assistant",
        "content": [
          {
            "type": "tool_use",
            "id": "toolu_xxx",
            "name": "get_weather",
            "input": {"city": "上海"}
          }
        ]
      },
      {
        "role": "user",
        "content": [
          {
            "type": "tool_result",
            "tool_use_id": "toolu_xxx",
            "content": "{\"temp\":\"22°C\",\"condition\":\"多云\",\"aqi\":53}"
          }
        ]
      }
    ]
  }'

curl -X POST "https://api.gravitex.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-sonnet-4-5-20250929",
    "max_tokens": 1024,
    "system": "你是一个 Python 编程助手",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "分析这段代码：\n```python\n[大量代码，至少1024个tokens]\n```",
            "cache_control": {"type": "ephemeral", "ttl": "1h"}
          }
        ]
      },
      {
        "role": "assistant",
        "content": [
          {
            "type": "text",
            "text": "这段代码的主要功能是...[详细分析]",
            "cache_control": {"type": "ephemeral", "ttl": "1h"}
          }
        ]
      },
      {
        "role": "user",
        "content": "如何优化这段代码的性能？"
      }
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.gravitex.ai"
)

# 首次请求：创建缓存
message1 = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    system=[
        {
            "type": "text",
            "text": "你是专业的文档分析助手...[长文本内容]",
            "cache_control": {"type": "ephemeral"}
        }
    ],
    messages=[
        {"role": "user", "content": "第一个问题"}
    ]
)

print(f"缓存创建: {message1.usage.cache_creation_input_tokens} tokens")
print(f"缓存读取: {message1.usage.cache_read_input_tokens} tokens")

# 5分钟内再次请求：使用缓存
message2 = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    system=[
        {
            "type": "text",
            "text": "你是专业的文档分析助手...[相同的长文本]",
            "cache_control": {"type": "ephemeral"}
        }
    ],
    messages=[
        {"role": "user", "content": "第二个问题"}
    ]
)

print(f"缓存创建: {message2.usage.cache_creation_input_tokens} tokens")
print(f"缓存读取: {message2.usage.cache_read_input_tokens} tokens")

event: message_start
data: {"type":"message_start","message":{"id":"msg_xxx","type":"message","role":"assistant","content":[],"model":"claude-sonnet-4-5-20250929","stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":25,"output_tokens":0}}}

event: content_block_start
data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"回"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"复"}}

event: content_block_stop
data: {"type":"content_block_stop","index":0}

event: message_delta
data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":100}}

event: message_stop
data: {"type":"message_stop"}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":"让我思考一下这个问题..."}}