Anthropic Messages API

POST

/apps/anthropic/v1/messages

import anthropic
import os

client = anthropic.Anthropic(
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope-intl.aliyuncs.com/apps/anthropic",
)

message = client.messages.create(
    model="qwen3.6-plus",
    max_tokens=1024,
    system="You are a helpful assistant",
    messages=[
        {
            "role": "user",
            "content": "你是谁？"
        }
    ],
    thinking={"type": "disabled"},
)

print(message.content[0].text)

{
  "id": "msg_e2898f19-fc0e-4cb3-bd9b-5b7dc4ea3bc9",
  "type": "message",
  "role": "assistant",
  "model": "qwen3.6-plus",
  "content": [
    {
      "type": "thinking",
      "thinking": "Let me analyze this question...",
      "signature": ""
    },
    {
      "type": "text",
      "text": "Hello! I am Qwen..."
    }
  ],
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 22,
    "output_tokens": 223,
    "cache_creation_input_tokens": 0,
    "cache_read_input_tokens": 0
  }
}

Authorizations

string

header

required

Qwen Cloud API key passed via x-api-key header. Authorization: Bearer header is also supported.

Body

application/json

string

required

Model name. Supported models:

Qwen Max: qwen3.6-max-preview, qwen3-max, qwen3-max-2026-01-23, qwen3-max-preview

Qwen Plus: qwen3.6-plus, qwen3.6-plus-2026-04-02, qwen3.5-plus, qwen3.5-plus-2026-04-20, qwen3.5-plus-2026-02-15, qwen-plus, qwen-plus-latest, qwen-plus-2025-09-11

Qwen Flash: qwen3.6-flash, qwen3.6-flash-2026-04-16, qwen3.5-flash, qwen3.5-flash-2026-02-23, qwen-flash, qwen-flash-2025-07-28

Qwen Turbo: qwen-turbo, qwen-turbo-latest

Qwen Coder: qwen3-coder-next, qwen3-coder-plus, qwen3-coder-plus-2025-09-23, qwen3-coder-flash

Qwen VL: qwen3-vl-plus, qwen3-vl-flash, qwen-vl-max, qwen-vl-plus

Qwen Open-source: qwen3.6-27b, qwen3.5-397b-a17b, qwen3.5-122b-a10b, qwen3.5-27b, qwen3.5-35b-a3b

Third-party models: deepseek-v4-pro, deepseek-v4-flash, deepseek-v3.2

integer

required

Maximum number of tokens to generate.

object[]

required

Message array, alternating between user and assistant turns.

Show child attributes

enum<string>

required

Message role.

Available options:user,assistant

string

required

Message content. Can be a plain text string or a structured content array.

string

System prompt to set the model's role or behavior. Passed as a top-level parameter; the messages array does not accept the system role. A string is equivalent to a single type="text" content block. To use context caching, pass an array of content blocks with cache_control.

boolean

defaultfalse

Enable streaming output. Default is false.

number

Controls diversity of generated text, range [0, 2). Higher values produce more random output. This range differs from Anthropic's native [0.0, 1.0] — verify this parameter when migrating from Anthropic.

number

Probability threshold for nucleus sampling. Both temperature and top_p control diversity — set only one at a time.

integer

Size of the sampling candidate set during generation.

string[]

Text sequences that stop generation. The model stops before outputting the sequence. When hit, stop_reason is still end_turn and the matched sequence is not included in the response.

object

Thinking configuration. When enabled, the model reasons before generating a reply to improve accuracy. The response will include thinking type content blocks.

Show child attributes

enum<string>

enabled (enable thinking) or disabled (disable thinking).

Available options:enabled,disabled

integer

Maximum tokens for the thinking process. A larger budget allows deeper analysis on complex problems. Takes effect when type is enabled.

enum<string>

Controls reasoning intensity. Default is max. Supported models: deepseek-v4-pro, deepseek-v4-flash. Values low or medium are mapped to high; xhigh is mapped to max.

Available options:high,max

object[]

Tool definition array for function calling.

Show child attributes

string

required

Tool name.

object

required

JSON Schema definition for the tool's input parameters.

string

Description of the tool's functionality.

object

Tool choice strategy. {"type": "auto"}: model decides whether to call tools (default). {"type": "any"}: force calling any tool. {"type": "none"}: disable tool calling. {"type": "tool", "name": "tool_name"}: force calling a specific tool.

Show child attributes

enum<string>

Strategy type.

Available options:auto,any,none,tool

string

When type is tool, specifies the name of the tool to call.

Response

200-application/json

string

Unique message identifier.

enum<string>

Always message.

Available options:message

enum<string>

Always assistant.

Available options:assistant

string

Model name used.

object[]

Content array. Element types can be text, thinking (returned when thinking is enabled), or tool_use (tool call).

Show child attributes

enum<string>

Content block type.

Available options:text,thinking,tool_use

string

Model-generated text reply when type is text.

string

Model's thinking process when type is thinking.

string

Signature when type is thinking. Currently always an empty string.

string

Unique identifier for the tool call when type is tool_use.

string

Name of the tool being called when type is tool_use.

object

Tool call input parameters when type is tool_use.

enum<string>

Stop reason: end_turn (normal completion), max_tokens (token limit reached), tool_use (tool call).

Available options:end_turn,max_tokens,tool_use

string | null

Always null.

object

Token usage statistics. In streaming, the usage in the message_start event only contains input_tokens and output_tokens; all 4 fields appear in the message_delta event.

Show child attributes

integer

Number of input tokens.

integer

Number of output tokens.

integer

Number of input tokens consumed for cache creation.

integer

Number of input tokens consumed by cache reads.