创建消息

POST

messages

import os
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.cometapi.com",
    api_key=os.environ["COMETAPI_KEY"],
)

message = client.messages.create(
    model="claude-sonnet-5",
    max_tokens=1024,
    system="You are a helpful assistant.",
    messages=[
        {"role": "user", "content": "Hello, world"}
    ],
)

print(message.content[0].text)

{
  "id": "<string>",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "text": "<string>",
      "thinking": "<string>",
      "signature": "<string>",
      "id": "<string>",
      "name": "<string>",
      "input": {}
    }
  ],
  "model": "<string>",
  "stop_sequence": "<string>",
  "usage": {
    "input_tokens": 123,
    "output_tokens": 123,
    "cache_creation_input_tokens": 123,
    "cache_read_input_tokens": 123,
    "cache_creation": {
      "ephemeral_5m_input_tokens": 123,
      "ephemeral_1h_input_tokens": 123
    },
    "output_tokens_details": {
      "thinking_tokens": 123
    }
  }
}

CometAPI 原生支持 Anthropic 消息 API，让你能够直接访问 Claude 模型及其 Anthropic 专属功能。对于自适应思考、Prompt 缓存和 effort 控制等 Claude 能力，请使用此端点。

请将官方的 Anthropic Messages API reference 作为完整参数列表、响应 schema 和 Claude 特定行为的权威来源。本 CometAPI 页面说明了如何通过 CometAPI 发送该请求结构。

随着 Claude 功能的演进，Anthropic 的请求参数和响应字段可能会发生变化。请查看 Anthropic Messages API 文档以获取最新的完整参数列表和特定提供商行为。

许多较新的 Claude 模型在 Messages API 上会拒绝非默认的 temperature、top_p 和 top_k 值。除非你已经确认所选模型支持这些采样字段，否则请省略它们。如果模型返回不支持或参数已弃用的错误，请从请求中移除相应字段。

x-api-key 和 Authorization: Bearer 两种请求头都支持用于身份验证。官方 Anthropic SDK 默认使用 x-api-key。

快速开始

要通过 CometAPI 使用官方 Anthropic SDK，请设置 base URL：

import os
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.cometapi.com",
    api_key=os.environ["COMETAPI_KEY"],
)

message = client.messages.create(
    model="claude-sonnet-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}],
)
print(message.content[0].text)

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic({
    apiKey: process.env.COMETAPI_KEY,
    baseURL: "https://api.cometapi.com",
});

const message = await client.messages.create({
    model: "claude-sonnet-5",
    max_tokens: 1024,
    messages: [{ role: "user", content: "Hello!" }],
});
console.log(message.content[0].text);

控制自适应思考

使用 output_config.effort 搭配自适应思考来控制 Claude 在响应中投入多少工作量。较新的 Claude 模型会拒绝旧版的手动 thinking 结构 thinking={"type": "enabled", "budget_tokens": ...}。

message = client.messages.create(
    model="claude-sonnet-5",
    max_tokens=4096,
    thinking={"type": "adaptive"},
    output_config={"effort": "xhigh"},
    messages=[
        {
            "role": "user",
            "content": "Analyze the trade-offs between a monolithic architecture and microservices for a small engineering team.",
        }
    ],
)

for block in message.content:
    if block.type == "text":
        print(block.text)

当你使用更高的 effort 级别时，思考 Token 会计入你的 max_tokens 限制。请将 max_tokens 设置得足够高，以同时容纳思考内容和最终答案。

缓存 Prompt

为减少后续请求的延迟和成本，可以缓存较大的 system Prompt 或对话前缀。为需要缓存的 content 块添加 cache_control：

message = client.messages.create(
    model="claude-sonnet-5",
    max_tokens=1024,
    system=[
        {
            "type": "text",
            "text": "You are an expert code reviewer. [Long detailed instructions...]",
            "cache_control": {"type": "ephemeral"},
        }
    ],
    messages=[{"role": "user", "content": "Review this code..."}],
)

缓存使用情况会在响应的 usage 字段中报告：

cache_creation_input_tokens — 写入缓存的 tokens（按更高费率计费）
cache_read_input_tokens — 从缓存读取的 tokens（按较低费率计费）

Prompt 缓存要求被缓存的 content 块至少包含 1,024 tokens。短于此长度的内容将不会被缓存。

流式输出响应

要使用 Server-Sent Events (SSE) 进行流式输出（Streaming）响应，请设置 stream: true。事件会按以下顺序到达：

message_start — 包含消息元数据和初始 usage
content_block_start — 标记每个 content 块的开始
content_block_delta — 增量文本块（text_delta）
content_block_stop — 标记每个 content 块的结束
message_delta — 最终的 stop_reason 和完整的 usage
message_stop — 表示流结束

with client.messages.stream(
    model="claude-sonnet-5",
    max_tokens=256,
    messages=[{"role": "user", "content": "Hello"}],
) as stream:
    for text in stream.text_stream:
        print(text, end="")

控制 effort

要控制 Claude 在生成响应时投入多少 effort，请使用 output_config.effort：

message = client.messages.create(
    model="claude-sonnet-5",
    max_tokens=4096,
    messages=[
        {"role": "user", "content": "Summarize this briefly."}
    ],
    output_config={"effort": "low"},  # "low", "medium", "high", "xhigh", or "max"
)

使用服务器工具

Claude 支持在 Anthropic 基础设施上运行的服务器端工具：

Web Fetch
Web Search

从 URL 获取并分析内容：

message = client.messages.create(
    model="claude-sonnet-5",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Analyze the content at https://arxiv.org/abs/1512.03385"}
    ],
    tools=[
        {"type": "web_fetch_20250910", "name": "web_fetch", "max_uses": 5}
    ],
)

在网络上搜索实时信息：

message = client.messages.create(
    model="claude-sonnet-5",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "What are the latest developments in AI?"}
    ],
    tools=[
        {"type": "web_search_20250305", "name": "web_search", "max_uses": 5}
    ],
)

响应示例

来自 CometAPI Anthropic 端点的典型响应：

{
  "id": "msg_bdrk_01UjHdmSztrL7QYYm7CKBDFB",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Hello!"
    }
  ],
  "model": "claude-sonnet-5",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 19,
    "cache_creation_input_tokens": 0,
    "cache_read_input_tokens": 0,
    "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 0
    },
    "output_tokens": 4
  }
}

与 OpenAI 兼容端点对比

功能	Anthropic 消息 (`/v1/messages`)	OpenAI-Compatible (`/v1/chat/completions`)
自适应思考	`thinking` 配合 `type: "adaptive"` 和 `output_config.effort`	不可用
Prompt 缓存	内容块上的 `cache_control`	不可用
努力程度控制	`output_config.effort`	不可用
Web 抓取/搜索	服务器工具（`web_fetch`、`web_search`）	不可用
认证请求头	`x-api-key` 或 `Bearer`	仅 `Bearer`
响应格式	Anthropic 格式（`content` 块）	OpenAI 格式（`choices`、`message`）
模型	仅 Claude	多提供商（GPT、Claude、Gemini 等）

授权

x-api-key

string

header

必填

Your CometAPI key passed via the x-api-key header. Authorization: Bearer $COMETAPI_KEY is also supported.

请求头

anthropic-version

string

默认值:2023-06-01

The Anthropic API version to use. Defaults to 2023-06-01.

示例:

"2023-06-01"

anthropic-beta

string

Comma-separated list of beta features to enable. Examples: max-tokens-3-5-sonnet-2024-07-15, pdfs-2024-09-25, output-128k-2025-02-19.

请求体

application/json

model

string

必填

The Claude model to use. See the Models page for available Claude model IDs.

示例:

"claude-sonnet-5"

messages

object[]

必填

The conversation messages. Must alternate between user and assistant roles. Each message's content can be a string or an array of content blocks (text, image, document, tool_use, tool_result). There is a limit of 100,000 messages per request.

Show child attributes

max_tokens

integer

必填

The maximum number of tokens to generate. The model may stop before reaching this limit. When using thinking, the thinking tokens count towards this limit.

必填范围: x >= 1

示例:

1024

system

System prompt providing context and instructions to Claude. Can be a plain string or an array of content blocks (useful for prompt caching).

temperature

number

默认值:1

Model-dependent sampling control. Many newer Claude models reject non-default temperature values on the Messages API. Omit this field unless you have verified that the selected model accepts it; if the model returns an unsupported or deprecated-parameter error, remove the field instead of substituting another sampling value.

必填范围: 0 <= x <= 1

示例:

1

top_p

number

Model-dependent nucleus sampling control. Many newer Claude models reject non-default top_p values on the Messages API. Omit this field unless you have verified support for the selected model. Do not set temperature and top_p together.

必填范围: 0 <= x <= 1

示例:

1

top_k

integer

Model-dependent top-k sampling control. Many newer Claude models reject non-default top_k values on the Messages API. Omit this field unless you have verified support for the selected model.

必填范围: x >= 0

示例:

0

stream

boolean

默认值:false

If true, stream the response incrementally using Server-Sent Events (SSE). Events include message_start, content_block_start, content_block_delta, content_block_stop, message_delta, and message_stop.

stop_sequences

string[]

Custom strings that cause the model to stop generating when encountered. The stop sequence is not included in the response.

thinking

object

Controls Claude thinking when the selected model supports a configurable thinking mode. For newer adaptive-thinking models, use {"type":"adaptive"} with output_config.effort, or omit thinking when adaptive thinking is already the model default. Manual {"type":"enabled","budget_tokens":...} is supported only by older models and is rejected by newer Claude models.

Show child attributes

tools

object[]

Tools the model may use. Supports client-defined functions, web search (web_search_20250305), web fetch (web_fetch_20250910), code execution (code_execution_20250522), and more.

Show child attributes

tool_choice

object

Controls how the model uses tools.

Show child attributes

metadata

object

Request metadata for tracking and analytics.

Show child attributes

output_config

object

Configuration for response effort and output format. Field support depends on the selected Claude model.

Show child attributes

service_tier

enum<string>

The service tier to use. auto tries priority capacity first, standard_only uses only standard capacity.

可用选项:

auto,

standard_only

响应

200 - application/json

Successful response. When stream is true, the response is a stream of SSE events.

string

Unique identifier for this message (e.g., msg_01XFDUDYJgAACzvnptvVoYEL).

type

enum<string>

Always message.

可用选项:

message

role

enum<string>

Always assistant.

可用选项:

assistant

content

object[]

The response content blocks. May include text, thinking, tool_use, and other block types.

Show child attributes

model

string

The specific model version that generated this response, such as claude-sonnet-5.

stop_reason

enum<string>

Why the model stopped generating. refusal can be returned as a successful HTTP response when the model declines a request.

可用选项:

end_turn,

max_tokens,

stop_sequence,

tool_use,

pause_turn,

refusal

stop_sequence

string | null

The stop sequence that caused the model to stop, if applicable.

usage

object

Token usage statistics.

Show child attributes

创建模型响应

生成内容

import os
import anthropic

client = anthropic.Anthropic(
    base_url="https://api.cometapi.com",
    api_key=os.environ["COMETAPI_KEY"],
)

message = client.messages.create(
    model="claude-sonnet-5",
    max_tokens=1024,
    system="You are a helpful assistant.",
    messages=[
        {"role": "user", "content": "Hello, world"}
    ],
)

print(message.content[0].text)

{
  "id": "<string>",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "text": "<string>",
      "thinking": "<string>",
      "signature": "<string>",
      "id": "<string>",
      "name": "<string>",
      "input": {}
    }
  ],
  "model": "<string>",
  "stop_sequence": "<string>",
  "usage": {
    "input_tokens": 123,
    "output_tokens": 123,
    "cache_creation_input_tokens": 123,
    "cache_read_input_tokens": 123,
    "cache_creation": {
      "ephemeral_5m_input_tokens": 123,
      "ephemeral_1h_input_tokens": 123
    },
    "output_tokens_details": {
      "thinking_tokens": 123
    }
  }
}

内容审核

API 密钥

快速开始

控制自适应思考

缓存 Prompt

流式输出响应

控制 effort

使用服务器工具

响应示例

与 OpenAI 兼容端点对比

授权

请求头

请求体

响应

​快速开始

​控制自适应思考

​缓存 Prompt

​流式输出响应

​控制 effort

​使用服务器工具

​响应示例

​与 OpenAI 兼容端点对比

授权

请求头

请求体

响应

快速开始

控制自适应思考

缓存 Prompt

流式输出响应

控制 effort

使用服务器工具

响应示例

与 OpenAI 兼容端点对比