Create Message - Requesty Docs

curl https://router.requesty.ai/v1/messages \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_REQUESTY_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "anthropic/claude-sonnet-4-20250514",
    "max_tokens": 1024,
    "messages": [
      {
        "role": "user",
        "content": "Hello, Claude!"
      }
    ]
  }'

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai",
)

message = client.messages.create(
    model="anthropic/claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello, Claude!"}
    ],
)

print(message.content[0].text)

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

const client = new Anthropic({
  apiKey: process.env.REQUESTY_API_KEY,
  baseURL: "https://router.requesty.ai",
});

const message = await client.messages.create({
  model: "anthropic/claude-sonnet-4-20250514",
  max_tokens: 1024,
  messages: [
    { role: "user", content: "Hello, Claude!" },
  ],
});

console.log(message.content[0].text);

{
  "id": "msg_01ABC123",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Hello! I'm Claude, an AI assistant by Anthropic. How can I help you today?"
    }
  ],
  "model": "anthropic/claude-sonnet-4-20250514",
  "stop_reason": "end_turn",
  "usage": {
    "input_tokens": 12,
    "output_tokens": 20,
    "cost": 0.000198
  }
}

POST

messages

curl https://router.requesty.ai/v1/messages \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_REQUESTY_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "anthropic/claude-sonnet-4-20250514",
    "max_tokens": 1024,
    "messages": [
      {
        "role": "user",
        "content": "Hello, Claude!"
      }
    ]
  }'

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai",
)

message = client.messages.create(
    model="anthropic/claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello, Claude!"}
    ],
)

print(message.content[0].text)

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

const client = new Anthropic({
  apiKey: process.env.REQUESTY_API_KEY,
  baseURL: "https://router.requesty.ai",
});

const message = await client.messages.create({
  model: "anthropic/claude-sonnet-4-20250514",
  max_tokens: 1024,
  messages: [
    { role: "user", content: "Hello, Claude!" },
  ],
});

console.log(message.content[0].text);

{
  "id": "msg_01ABC123",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Hello! I'm Claude, an AI assistant by Anthropic. How can I help you today?"
    }
  ],
  "model": "anthropic/claude-sonnet-4-20250514",
  "stop_reason": "end_turn",
  "usage": {
    "input_tokens": 12,
    "output_tokens": 20,
    "cost": 0.000198
  }
}

curl https://router.requesty.ai/v1/messages \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_REQUESTY_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "anthropic/claude-sonnet-4-20250514",
    "max_tokens": 1024,
    "messages": [
      {
        "role": "user",
        "content": "Hello, Claude!"
      }
    ]
  }'

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai",
)

message = client.messages.create(
    model="anthropic/claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello, Claude!"}
    ],
)

print(message.content[0].text)

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

const client = new Anthropic({
  apiKey: process.env.REQUESTY_API_KEY,
  baseURL: "https://router.requesty.ai",
});

const message = await client.messages.create({
  model: "anthropic/claude-sonnet-4-20250514",
  max_tokens: 1024,
  messages: [
    { role: "user", content: "Hello, Claude!" },
  ],
});

console.log(message.content[0].text);

{
  "id": "msg_01ABC123",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Hello! I'm Claude, an AI assistant by Anthropic. How can I help you today?"
    }
  ],
  "model": "anthropic/claude-sonnet-4-20250514",
  "stop_reason": "end_turn",
  "usage": {
    "input_tokens": 12,
    "output_tokens": 20,
    "cost": 0.000198
  }
}

Send a message to an Anthropic-compatible model and receive a response. This endpoint follows the Anthropic Messages API format and supports all Anthropic models as well as compatible models from other providers through Requesty’s routing.

Base URL

https://router.requesty.ai/v1/messages

Authentication

Include your Requesty API key in the request headers using Anthropic’s standard format:

x-api-key: YOUR_REQUESTY_API_KEY

Headers

Header	Required	Description
`x-api-key`	✅	Your Requesty API key (Anthropic format)
`Content-Type`	✅	Must be `application/json`
`anthropic-version`	❌	API version (defaults to `2023-06-01`)

Example Request

curl https://router.requesty.ai/v1/messages \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_REQUESTY_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "anthropic/claude-sonnet-4-20250514",
    "max_tokens": 1024,
    "messages": [
      {
        "role": "user",
        "content": "Hello, Claude!"
      }
    ]
  }'

Model Selection

You can use any model available in the Model Library. Examples:

Anthropic Models: anthropic/claude-sonnet-4-20250514, anthropic/claude-3-7-sonnet
OpenAI Models: openai/gpt-4o, openai/gpt-4o-mini
Google Models: google/gemini-2.0-flash-exp
Other Providers: mistral/mistral-large-2411, meta/llama-3.3-70b-instruct

While this endpoint uses the Anthropic Messages format, Requesty automatically handles format conversion for non-Anthropic models, so you can use any supported model with this endpoint.

Streaming

Enable streaming responses by setting stream: true:

{
	"model": "anthropic/claude-sonnet-4-20250514",
	"max_tokens": 1024,
	"stream": true,
	"messages": [
		{
			"role": "user",
			"content": "Write a short story"
		}
	]
}

Vision Support

Send images using the content blocks format:

{
	"model": "anthropic/claude-sonnet-4-20250514",
	"max_tokens": 1024,
	"messages": [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "What do you see in this image?"
				},
				{
					"type": "image",
					"source": {
						"type": "base64",
						"media_type": "image/jpeg",
						"data": "/9j/4AAQSkZJRgABAQAAAQABAAD..."
					}
				}
			]
		}
	]
}

PDF Support

You can send PDFs, encoded in base 64 format:

{
	"model": "anthropic/claude-sonnet-4-20250514",
	"max_tokens": 1024,
	"messages": [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "What is in this PDF?"
				},
                {
                    "type": "document",
                    "source": {
                        "type": "base64",
                        "media_type": "application/pdf",
                        "data": "JVBERi0=..."
                    }
				}
			]
		}
	]
}

Web Search

Enable real-time web search using Anthropic’s native web_search_20250305 tool type:

{
  "model": "anthropic/claude-sonnet-4-20250514",
  "max_tokens": 4096,
  "messages": [
    { "role": "user", "content": "What are the latest developments in AI?" }
  ],
  "tools": [{
    "type": "web_search_20250305",
    "name": "web_search",
    "max_uses": 5
  }],
  "stream": true
}

The response includes server_tool_use, web_search_tool_result, and text blocks with citations. See the Web Search guide for full response format details.

Tool Use

Define tools that the model can call:

{
	"model": "anthropic/claude-sonnet-4-20250514",
	"max_tokens": 1024,
	"tools": [
		{
			"name": "get_weather",
			"description": "Get the current weather in a given location",
			"input_schema": {
				"type": "object",
				"properties": {
					"location": {
						"type": "string",
						"description": "The city and state, e.g. San Francisco, CA"
					}
				},
				"required": ["location"]
			}
		}
	],
	"messages": [
		{
			"role": "user",
			"content": "What's the weather like in New York?"
		}
	]
}

System Prompts

Include system instructions using the system parameter:

{
	"model": "anthropic/claude-sonnet-4-20250514",
	"max_tokens": 1024,
	"system": "You are a helpful assistant that always responds in a friendly, professional manner.",
	"messages": [
		{
			"role": "user",
			"content": "Hello!"
		}
	]
}

Error Handling

The API returns standard HTTP status codes:

200 - Success
400 - Bad Request (invalid parameters)
401 - Unauthorized (invalid API key)
403 - Forbidden (insufficient permissions)
413 - Payload Too Large (request body exceeds 50 MB)
429 - Rate Limited
500 - Internal Server Error

Example error response:

{
	"error": {
		"type": "invalid_request_error",
		"message": "max_tokens is required"
	}
}

Response Format

Successful responses follow the Anthropic Messages format:

{
	"id": "msg_01ABC123",
	"type": "message",
	"role": "assistant",
	"content": [
		{
			"type": "text",
			"text": "Hello! I'm Claude, an AI assistant. How can I help you today?"
		}
	],
	"model": "anthropic/claude-sonnet-4-20250514",
	"stop_reason": "end_turn",
	"usage": {
		"input_tokens": 12,
		"output_tokens": 18,
		"cost": 0.000234
	}
}

The cost field inside usage is a Requesty extension and reports the USD cost of the request. It is returned by default on non-streaming responses, no extra request parameter is needed. See Cost Tracking.

Key Differences from OpenAI Chat Completions

Authentication: Uses x-api-key header instead of Authorization: Bearer
Required max_tokens: Unlike OpenAI’s API, the max_tokens parameter is required
Content Blocks: Messages use content blocks for rich content (text, images, tool calls)
System Parameter: System prompts are specified as a separate system parameter, not as a message
Role Restrictions: Only user and assistant roles are supported in messages (no system role)

For the most seamless experience with Anthropic models, use this endpoint. For broader compatibility across all providers, consider using the Chat Completions endpoint instead.

Headers

x-api-key

string

required

Your Requesty API key

anthropic-version

string

default:2023-06-01

The version of the Anthropic API to use

Example:

"2023-06-01"

Body

application/json

model

string

default:anthropic/claude-sonnet-4-20250514

required

The model to use for the completion

Example:

"anthropic/claude-sonnet-4-20250514"

max_tokens

integer

required

The maximum number of tokens to generate before stopping

Required range: x >= 1

Example:

1024

messages

object[]

required

Input messages

Show child attributes

system

string

System prompt to be used for the completion

temperature

number

Amount of randomness injected into the response

Required range: 0 <= x <= 2

top_p

number

Use nucleus sampling

Required range: 0 <= x <= 1

top_k

integer

Only sample from the top K options for each subsequent token

Required range: x >= 0

stream

boolean

Whether to incrementally stream the response using server-sent events

stop_sequences

string[]

Custom text sequences that will cause the model to stop generating

tools

object[]

Definitions of tools that the model may use

Show child attributes

tool_choice

How the model should use the provided tools

Available options:

auto,

any

Response

Message response

string

required

Unique object identifier

type

enum<string>

required

Object type

Available options:

message

role

enum<string>

required

Conversational role of the generated message

Available options:

assistant

content

object[]

required

Content generated by the model

Option 1
Option 2
Option 3
Option 4

Show child attributes

model

string

required

The model that handled the request

stop_reason

enum<string>

required

The reason that we stopped

Available options:

end_turn,

max_tokens,

stop_sequence,

tool_use

usage

object

required

Show child attributes

stop_sequence

string

Which custom stop sequence was generated

Last modified on November 3, 2026

​Base URL

​Authentication

​Headers

​Example Request

​Model Selection

​Streaming

​Vision Support

​PDF Support

​Web Search

​Tool Use

​System Prompts

​Error Handling

​Response Format

​Key Differences from OpenAI Chat Completions

Headers

Body

Response

Base URL

Authentication

Headers

Example Request

Model Selection

Streaming

Vision Support

PDF Support

Web Search

Tool Use

System Prompts

Error Handling

Response Format

Key Differences from OpenAI Chat Completions