# Using the Messages API

Practical patterns and examples for using the Messages API effectively

---

Anthropic offers two ways to build with Claude, each suited to different use cases:

| | Messages API | Claude Managed Agents |
|---|---|---|
| **What it is** | Direct model prompting access | Pre-built, configurable agent harness that runs in managed infrastructure |
| **Best for** | Custom agent loops and fine-grained control | Long-running tasks and asynchronous work |
| **Learn more** | [Messages API docs](/docs/en/build-with-claude/working-with-messages) | [Claude Managed Agents docs](/docs/en/managed-agents/overview) |

This guide covers common patterns for working with the Messages API, including basic requests, multi-turn conversations, prefill techniques, and vision capabilities. For complete API specifications, see the [Messages API reference](/docs/en/api/messages/create).

<Note>
This feature is eligible for [Zero Data Retention (ZDR)](/docs/en/build-with-claude/api-and-data-retention). When your organization has a ZDR arrangement, data sent through this feature is not stored after the API response is returned.
</Note>

## Basic request and response

<CodeGroup>
  ```bash cURL
  #!/bin/sh
  curl https://api.anthropic.com/v1/messages \
       --header "x-api-key: $ANTHROPIC_API_KEY" \
       --header "anthropic-version: 2023-06-01" \
       --header "content-type: application/json" \
       --data \
  '{
      "model": "claude-opus-4-7",
      "max_tokens": 1024,
      "messages": [
          {"role": "user", "content": "Hello, Claude"}
      ]
  }'
  ```

  ```bash CLI
  ant messages create \
    --model claude-opus-4-7 \
    --max-tokens 1024 \
    --message '{role: user, content: "Hello, Claude"}'
  ```

  ```python Python hidelines={1..2}
  import anthropic

  message = anthropic.Anthropic().messages.create(
      model="claude-opus-4-7",
      max_tokens=1024,
      messages=[{"role": "user", "content": "Hello, Claude"}],
  )
  print(message)
  ```

  ```typescript TypeScript hidelines={1..2}
  import Anthropic from "@anthropic-ai/sdk";

  const anthropic = new Anthropic();

  const message = await anthropic.messages.create({
    model: "claude-opus-4-7",
    max_tokens: 1024,
    messages: [{ role: "user", content: "Hello, Claude" }]
  });
  console.log(message);
  ```

  ```csharp C#
  using System;
  using System.Threading.Tasks;
  using Anthropic;
  using Anthropic.Models.Messages;

  class Program
  {
      static async Task Main()
      {
          AnthropicClient client = new();

          var parameters = new MessageCreateParams
          {
              Model = Model.ClaudeOpus4_7,
              MaxTokens = 1024,
              Messages = [new() { Role = Role.User, Content = "Hello, Claude" }]
          };
          var message = await client.Messages.Create(parameters);
          Console.WriteLine(message);
      }
  }
  ```

  ```go Go hidelines={1..11,-1}
  package main

  import (
  	"context"
  	"fmt"
  	"log"

  	"github.com/anthropics/anthropic-sdk-go"
  )

  func main() {
  	client := anthropic.NewClient()

  	response, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
  		Model:     anthropic.ModelClaudeOpus4_7,
  		MaxTokens: 1024,
  		Messages: []anthropic.MessageParam{
  			anthropic.NewUserMessage(anthropic.NewTextBlock("Hello, Claude")),
  		},
  	})
  	if err != nil {
  		log.Fatal(err)
  	}
  	fmt.Println(response)
  }
  ```

  ```java Java hidelines={1..8,-2..}
  import com.anthropic.client.AnthropicClient;
  import com.anthropic.client.okhttp.AnthropicOkHttpClient;
  import com.anthropic.models.messages.MessageCreateParams;
  import com.anthropic.models.messages.Message;
  import com.anthropic.models.messages.Model;

  public class Main {
      public static void main(String[] args) {
          AnthropicClient client = AnthropicOkHttpClient.fromEnv();

          MessageCreateParams params = MessageCreateParams.builder()
              .model(Model.CLAUDE_OPUS_4_7)
              .maxTokens(1024L)
              .addUserMessage("Hello, Claude")
              .build();

          Message response = client.messages().create(params);
          System.out.println(response);
      }
  }
  ```

  ```php PHP hidelines={1..4}
  <?php

  use Anthropic\Client;

  $client = new Client(apiKey: getenv("ANTHROPIC_API_KEY"));

  $message = $client->messages->create(
      maxTokens: 1024,
      messages: [['role' => 'user', 'content' => 'Hello, Claude']],
      model: 'claude-opus-4-7',
  );
  echo $message->content[0]->text;
  ```

  ```ruby Ruby hidelines={1..2}
  require "anthropic"

  client = Anthropic::Client.new

  message = client.messages.create(
    model: "claude-opus-4-7",
    max_tokens: 1024,
    messages: [
      { role: "user", content: "Hello, Claude" }
    ]
  )
  puts message
  ```
</CodeGroup>

```json Output
{
  "id": "msg_01XFDUDYJgAACzvnptvVoYEL",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Hello!"
    }
  ],
  "model": "claude-opus-4-7",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 12,
    "output_tokens": 6
  }
}
```

## Multiple conversational turns

The Messages API is stateless, which means that you always send the full conversational history to the API. You can use this pattern to build up a conversation over time. Earlier conversational turns don't necessarily need to actually originate from Claude. You can use synthetic `assistant` messages.

<CodeGroup>
```bash cURL
#!/bin/sh
curl https://api.anthropic.com/v1/messages \
     --header "x-api-key: $ANTHROPIC_API_KEY" \
     --header "anthropic-version: 2023-06-01" \
     --header "content-type: application/json" \
     --data \
'{
    "model": "claude-opus-4-7",
    "max_tokens": 1024,
    "messages": [
        {"role": "user", "content": "Hello, Claude"},
        {"role": "assistant", "content": "Hello!"},
        {"role": "user", "content": "Can you describe LLMs to me?"}

    ]
}'
```

```bash CLI
ant messages create \
  --model claude-opus-4-7 \
  --max-tokens 1024 \
  --message '{role: user, content: "Hello, Claude"}' \
  --message '{role: assistant, content: "Hello!"}' \
  --message '{role: user, content: "Can you describe LLMs to me?"}'
```

```python Python hidelines={1..2}
import anthropic

message = anthropic.Anthropic().messages.create(
    model="claude-opus-4-7",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello, Claude"},
        {"role": "assistant", "content": "Hello!"},
        {"role": "user", "content": "Can you describe LLMs to me?"},
    ],
)
print(message)
```

```typescript TypeScript hidelines={1..2}
import Anthropic from "@anthropic-ai/sdk";

const anthropic = new Anthropic();

await anthropic.messages.create({
  model: "claude-opus-4-7",
  max_tokens: 1024,
  messages: [
    { role: "user", content: "Hello, Claude" },
    { role: "assistant", content: "Hello!" },
    { role: "user", content: "Can you describe LLMs to me?" }
  ]
});
```

```csharp C#
using System;
using System.Threading.Tasks;
using Anthropic;
using Anthropic.Models.Messages;

class Program
{
    static async Task Main(string[] args)
    {
        AnthropicClient client = new();

        var parameters = new MessageCreateParams
        {
            Model = Model.ClaudeOpus4_7,
            MaxTokens = 1024,
            Messages =
            [
                new() { Role = Role.User, Content = "Hello, Claude" },
                new() { Role = Role.Assistant, Content = "Hello!" },
                new() { Role = Role.User, Content = "Can you describe LLMs to me?" }
            ]
        };

        var message = await client.Messages.Create(parameters);
        Console.WriteLine(message);
    }
}
```

```go Go hidelines={1..11,-1}
package main

import (
	"context"
	"fmt"
	"log"

	"github.com/anthropics/anthropic-sdk-go"
)

func main() {
	client := anthropic.NewClient()

	response, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
		Model:     anthropic.ModelClaudeOpus4_7,
		MaxTokens: 1024,
		Messages: []anthropic.MessageParam{
			anthropic.NewUserMessage(anthropic.NewTextBlock("Hello, Claude")),
			anthropic.NewAssistantMessage(anthropic.NewTextBlock("Hello!")),
			anthropic.NewUserMessage(anthropic.NewTextBlock("Can you describe LLMs to me?")),
		},
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Println(response)
}
```

```java Java hidelines={1..8,-2..}
import com.anthropic.client.AnthropicClient;
import com.anthropic.client.okhttp.AnthropicOkHttpClient;
import com.anthropic.models.messages.MessageCreateParams;
import com.anthropic.models.messages.Message;
import com.anthropic.models.messages.Model;

public class MultiTurnConversation {
    public static void main(String[] args) {
        AnthropicClient client = AnthropicOkHttpClient.fromEnv();

        MessageCreateParams params = MessageCreateParams.builder()
            .model(Model.CLAUDE_OPUS_4_7)
            .maxTokens(1024L)
            .addUserMessage("Hello, Claude")
            .addAssistantMessage("Hello!")
            .addUserMessage("Can you describe LLMs to me?")
            .build();

        Message response = client.messages().create(params);
        System.out.println(response);
    }
}
```

```php PHP hidelines={1..4}
<?php

use Anthropic\Client;

$client = new Client(apiKey: getenv("ANTHROPIC_API_KEY"));

$message = $client->messages->create(
    maxTokens: 1024,
    messages: [
        ['role' => 'user', 'content' => 'Hello, Claude'],
        ['role' => 'assistant', 'content' => 'Hello!'],
        ['role' => 'user', 'content' => 'Can you describe LLMs to me?'],
    ],
    model: 'claude-opus-4-7',
);

echo $message->content[0]->text;
```

```ruby Ruby hidelines={1..2}
require "anthropic"

client = Anthropic::Client.new

message = client.messages.create(
  model: "claude-opus-4-7",
  max_tokens: 1024,
  messages: [
    { role: "user", content: "Hello, Claude" },
    { role: "assistant", content: "Hello!" },
    { role: "user", content: "Can you describe LLMs to me?" }
  ]
)
puts message
```
</CodeGroup>

```json Output
{
  "id": "msg_018gCsTGsXkYJVqYPxTgDHBU",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Sure, I'd be happy to provide..."
    }
  ],
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 30,
    "output_tokens": 309
  }
}
```

## Putting words in Claude's mouth

You can pre-fill part of Claude's response in the last position of the input messages list. This can be used to shape Claude's response. The example below uses `"max_tokens": 1` to get a single multiple choice answer from Claude.

<CodeGroup>
  ```bash cURL
  #!/bin/sh
  curl https://api.anthropic.com/v1/messages \
       --header "x-api-key: $ANTHROPIC_API_KEY" \
       --header "anthropic-version: 2023-06-01" \
       --header "content-type: application/json" \
       --data \
  '{
      "model": "claude-sonnet-4-5",
      "max_tokens": 1,
      "messages": [
          {"role": "user", "content": "What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae"},
          {"role": "assistant", "content": "The answer is ("}
      ]
  }'
  ```

  ```bash CLI
  ant messages create <<'YAML'
  model: claude-sonnet-4-5
  max_tokens: 1
  messages:
    - role: user
      content: "What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae"
    - role: assistant
      content: "The answer is ("
  YAML
  ```

  ```python Python hidelines={1..2}
  import anthropic

  message = anthropic.Anthropic().messages.create(
      model="claude-sonnet-4-5",
      max_tokens=1,
      messages=[
          {
              "role": "user",
              "content": "What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae",
          },
          {"role": "assistant", "content": "The answer is ("},
      ],
  )
  print(message)
  ```

  ```typescript TypeScript hidelines={1..2}
  import Anthropic from "@anthropic-ai/sdk";

  const anthropic = new Anthropic();

  const message = await anthropic.messages.create({
    model: "claude-sonnet-4-5",
    max_tokens: 1,
    messages: [
      {
        role: "user",
        content: "What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae"
      },
      { role: "assistant", content: "The answer is (" }
    ]
  });
  console.log(message);
  ```

  ```csharp C#
  using System;
  using System.Threading.Tasks;
  using Anthropic;
  using Anthropic.Models.Messages;

  class Program
  {
      static async Task Main(string[] args)
      {
          AnthropicClient client = new();

          var parameters = new MessageCreateParams
          {
              Model = Model.ClaudeSonnet4_5,
              MaxTokens = 1,
              Messages = [
                  new() { Role = Role.User, Content = "What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae" },
                  new() { Role = Role.Assistant, Content = "The answer is (" }
              ]
          };

          var message = await client.Messages.Create(parameters);
          Console.WriteLine(message);
      }
  }
  ```

  ```go Go hidelines={1..11,-1}
  package main

  import (
  	"context"
  	"fmt"
  	"log"

  	"github.com/anthropics/anthropic-sdk-go"
  )

  func main() {
  	client := anthropic.NewClient()

  	response, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
  		Model:     anthropic.ModelClaudeSonnet4_5,
  		MaxTokens: 1,
  		Messages: []anthropic.MessageParam{
  			anthropic.NewUserMessage(anthropic.NewTextBlock("What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae")),
  			anthropic.NewAssistantMessage(anthropic.NewTextBlock("The answer is (")),
  		},
  	})
  	if err != nil {
  		log.Fatal(err)
  	}
  	fmt.Println(response)
  }
  ```

  ```java Java hidelines={1..8,-2..}
  import com.anthropic.client.AnthropicClient;
  import com.anthropic.client.okhttp.AnthropicOkHttpClient;
  import com.anthropic.models.messages.MessageCreateParams;
  import com.anthropic.models.messages.Message;
  import com.anthropic.models.messages.Model;

  public class PrefillExample {
      public static void main(String[] args) {
          AnthropicClient client = AnthropicOkHttpClient.fromEnv();

          MessageCreateParams params = MessageCreateParams.builder()
              .model(Model.CLAUDE_SONNET_4_5)
              .maxTokens(1L)
              .addUserMessage("What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae")
              .addAssistantMessage("The answer is (")
              .build();

          Message response = client.messages().create(params);
          System.out.println(response);
      }
  }
  ```

  ```php PHP hidelines={1..4}
  <?php

  use Anthropic\Client;

  $client = new Client(apiKey: getenv("ANTHROPIC_API_KEY"));

  $message = $client->messages->create(
      maxTokens: 1,
      messages: [
          ['role' => 'user', 'content' => 'What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae'],
          ['role' => 'assistant', 'content' => 'The answer is ('],
      ],
      model: 'claude-sonnet-4-5',
  );
  echo $message->content[0]->text;
  ```

  ```ruby Ruby hidelines={1..2}
  require "anthropic"

  client = Anthropic::Client.new

  message = client.messages.create(
    model: "claude-sonnet-4-5",
    max_tokens: 1,
    messages: [
      {
        role: "user",
        content: "What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae"
      },
      { role: "assistant", content: "The answer is (" }
    ]
  )
  puts message
  ```
</CodeGroup>

```json Output
{
  "id": "msg_01Q8Faay6S7QPTvEUUQARt7h",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "C"
    }
  ],
  "model": "claude-sonnet-4-5",
  "stop_reason": "max_tokens",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 42,
    "output_tokens": 1
  }
}
```

<Warning>
Prefilling is not supported on [Claude Mythos Preview](https://anthropic.com/glasswing), Claude Opus 4.7, Claude Opus 4.6, and Claude Sonnet 4.6. Requests using prefill with these models return a 400 error. Use [structured outputs](/docs/en/build-with-claude/structured-outputs) or system prompt instructions instead. See the [migration guide](/docs/en/about-claude/models/migration-guide) for migration patterns.
</Warning>

## Vision

Claude can read both text and images in requests. Images can be supplied using the `base64`, `url`, or `file` source types. The `file` source type references an image uploaded through the [Files API](/docs/en/build-with-claude/files). Supported media types are `image/jpeg`, `image/png`, `image/gif`, and `image/webp`. See the [vision guide](/docs/en/build-with-claude/vision) for more details.

<CodeGroup>
  ```bash cURL
  #!/bin/sh

  # Option 1: Base64-encoded image
  IMAGE_URL="https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"
  IMAGE_MEDIA_TYPE="image/jpeg"
  IMAGE_BASE64=$(curl "$IMAGE_URL" | base64 | tr -d '\n')

  curl https://api.anthropic.com/v1/messages \
       --header "x-api-key: $ANTHROPIC_API_KEY" \
       --header "anthropic-version: 2023-06-01" \
       --header "content-type: application/json" \
       --data \
  '{
      "model": "claude-opus-4-7",
      "max_tokens": 1024,
      "messages": [
          {"role": "user", "content": [
              {"type": "image", "source": {
                  "type": "base64",
                  "media_type": "'$IMAGE_MEDIA_TYPE'",
                  "data": "'$IMAGE_BASE64'"
              }},
              {"type": "text", "text": "What is in the above image?"}
          ]}
      ]
  }'

  # Option 2: URL-referenced image
  curl https://api.anthropic.com/v1/messages \
       --header "x-api-key: $ANTHROPIC_API_KEY" \
       --header "anthropic-version: 2023-06-01" \
       --header "content-type: application/json" \
       --data \
  '{
      "model": "claude-opus-4-7",
      "max_tokens": 1024,
      "messages": [
          {"role": "user", "content": [
              {"type": "image", "source": {
                  "type": "url",
                  "url": "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"
              }},
              {"type": "text", "text": "What is in the above image?"}
          ]}
      ]
  }'
  ```

  
  ```bash CLI nocheck
  IMAGE_URL="https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"

  # Option 1: Base64-encoded image (CLI auto-encodes binary @file refs)
  curl -s "$IMAGE_URL" -o ./ant.jpg

  ant messages create <<'YAML'
  model: claude-opus-4-7
  max_tokens: 1024
  messages:
    - role: user
      content:
        - type: image
          source:
            type: base64
            media_type: image/jpeg
            data: "@./ant.jpg"
        - type: text
          text: What is in the above image?
  YAML

  # Option 2: URL-referenced image
  ant messages create <<YAML
  model: claude-opus-4-7
  max_tokens: 1024
  messages:
    - role: user
      content:
        - type: image
          source:
            type: url
            url: $IMAGE_URL
        - type: text
          text: What is in the above image?
  YAML
  ```

  
  ```python Python nocheck hidelines={1}
  import anthropic
  import base64
  import httpx

  # Option 1: Base64-encoded image
  image_url = "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"
  image_media_type = "image/jpeg"
  image_data = base64.standard_b64encode(httpx.get(image_url).content).decode("utf-8")

  message = anthropic.Anthropic().messages.create(
      model="claude-opus-4-7",
      max_tokens=1024,
      messages=[
          {
              "role": "user",
              "content": [
                  {
                      "type": "image",
                      "source": {
                          "type": "base64",
                          "media_type": image_media_type,
                          "data": image_data,
                      },
                  },
                  {"type": "text", "text": "What is in the above image?"},
              ],
          }
      ],
  )
  print(message)

  # Option 2: URL-referenced image
  message_from_url = anthropic.Anthropic().messages.create(
      model="claude-opus-4-7",
      max_tokens=1024,
      messages=[
          {
              "role": "user",
              "content": [
                  {
                      "type": "image",
                      "source": {
                          "type": "url",
                          "url": "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg",
                      },
                  },
                  {"type": "text", "text": "What is in the above image?"},
              ],
          }
      ],
  )
  print(message_from_url)
  ```

  
  ```typescript TypeScript nocheck hidelines={1..2}
  import Anthropic from "@anthropic-ai/sdk";

  const anthropic = new Anthropic();

  // Option 1: Base64-encoded image
  const image_url =
    "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg";
  const image_media_type = "image/jpeg";
  const image_array_buffer = await (await fetch(image_url)).arrayBuffer();
  const image_data = Buffer.from(image_array_buffer).toString("base64");

  const message = await anthropic.messages.create({
    model: "claude-opus-4-7",
    max_tokens: 1024,
    messages: [
      {
        role: "user",
        content: [
          {
            type: "image",
            source: {
              type: "base64",
              media_type: image_media_type,
              data: image_data
            }
          },
          {
            type: "text",
            text: "What is in the above image?"
          }
        ]
      }
    ]
  });
  console.log(message);

  // Option 2: URL-referenced image
  const messageFromUrl = await anthropic.messages.create({
    model: "claude-opus-4-7",
    max_tokens: 1024,
    messages: [
      {
        role: "user",
        content: [
          {
            type: "image",
            source: {
              type: "url",
              url: "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"
            }
          },
          {
            type: "text",
            text: "What is in the above image?"
          }
        ]
      }
    ]
  });
  console.log(messageFromUrl);
  ```

  
  ```csharp C# nocheck
  using System;
  using System.Collections.Generic;
  using System.Net.Http;
  using System.Threading.Tasks;
  using Anthropic;
  using Anthropic.Models.Messages;

  public class Program
  {
      public static async Task Main(string[] args)
      {
          AnthropicClient client = new();

          // Option 1: Base64-encoded image
          string imageUrl = "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg";

          using HttpClient httpClient = new();
          byte[] imageBytes = await httpClient.GetByteArrayAsync(imageUrl);
          string imageData = Convert.ToBase64String(imageBytes);

          var parameters = new MessageCreateParams
          {
              Model = Model.ClaudeOpus4_7,
              MaxTokens = 1024,
              Messages =
              [
                  new()
                  {
                      Role = Role.User,
                      Content = new MessageParamContent(new List<ContentBlockParam>
                      {
                          new ContentBlockParam(new ImageBlockParam(
                              new ImageBlockParamSource(new Base64ImageSource()
                              {
                                  Data = imageData,
                                  MediaType = MediaType.ImageJpeg,
                              })
                          )),
                          new ContentBlockParam(new TextBlockParam("What is in the above image?")),
                      }),
                  }
              ]
          };

          var message = await client.Messages.Create(parameters);
          Console.WriteLine(message);

          // Option 2: URL-referenced image
          var parametersFromUrl = new MessageCreateParams
          {
              Model = Model.ClaudeOpus4_7,
              MaxTokens = 1024,
              Messages =
              [
                  new()
                  {
                      Role = Role.User,
                      Content = new MessageParamContent(new List<ContentBlockParam>
                      {
                          new ContentBlockParam(new ImageBlockParam(
                              new ImageBlockParamSource(new UrlImageSource()
                              {
                                  Url = new Uri("https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"),
                              })
                          )),
                          new ContentBlockParam(new TextBlockParam("What is in the above image?")),
                      }),
                  }
              ]
          };

          var messageFromUrl = await client.Messages.Create(parametersFromUrl);
          Console.WriteLine(messageFromUrl);
      }
  }
  ```

  
  ```go Go nocheck hidelines={1..16,-1}
  package main

  import (
  	"context"
  	"encoding/base64"
  	"fmt"
  	"io"
  	"log"
  	"net/http"

  	"github.com/anthropics/anthropic-sdk-go"
  )

  func main() {
  	client := anthropic.NewClient()

  	// Option 1: Base64-encoded image
  	imageURL := "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"

  	req, err := http.NewRequest("GET", imageURL, nil)
  	if err != nil {
  		log.Fatal(err)
  	}
  	req.Header.Set("User-Agent", "AnthropicDocsBot/1.0")

  	resp, err := http.DefaultClient.Do(req)
  	if err != nil {
  		log.Fatal(err)
  	}
  	defer resp.Body.Close()

  	imageBytes, err := io.ReadAll(resp.Body)
  	if err != nil {
  		log.Fatal(err)
  	}
  	imageData := base64.StdEncoding.EncodeToString(imageBytes)

  	message, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
  		Model:     anthropic.ModelClaudeOpus4_7,
  		MaxTokens: 1024,
  		Messages: []anthropic.MessageParam{
  			anthropic.NewUserMessage(
  				anthropic.NewImageBlockBase64("image/jpeg", imageData),
  				anthropic.NewTextBlock("What is in the above image?"),
  			),
  		},
  	})
  	if err != nil {
  		log.Fatal(err)
  	}
  	fmt.Println(message)

  	// Option 2: URL-referenced image
  	messageFromURL, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
  		Model:     anthropic.ModelClaudeOpus4_7,
  		MaxTokens: 1024,
  		Messages: []anthropic.MessageParam{
  			anthropic.NewUserMessage(
  				anthropic.NewImageBlock(anthropic.URLImageSourceParam{
  					URL: "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg",
  				}),
  				anthropic.NewTextBlock("What is in the above image?"),
  			),
  		},
  	})
  	if err != nil {
  		log.Fatal(err)
  	}
  	fmt.Println(messageFromURL)
  }
  ```

  
  ```java Java nocheck hidelines={1..12,-2..}
  import com.anthropic.client.AnthropicClient;
  import com.anthropic.client.okhttp.AnthropicOkHttpClient;
  import com.anthropic.models.messages.*;
  import java.net.URI;
  import java.net.http.HttpClient;
  import java.net.http.HttpRequest;
  import java.net.http.HttpResponse;
  import java.util.Base64;
  import java.util.List;

  public class VisionExample {
      public static void main(String[] args) throws Exception {
          AnthropicClient client = AnthropicOkHttpClient.fromEnv();

          // Option 1: Base64-encoded image
          String imageUrl = "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg";

          HttpClient httpClient = HttpClient.newHttpClient();
          HttpRequest request = HttpRequest.newBuilder().uri(URI.create(imageUrl)).build();
          HttpResponse<byte[]> response = httpClient.send(request, HttpResponse.BodyHandlers.ofByteArray());
          String imageData = Base64.getEncoder().encodeToString(response.body());

          List<ContentBlockParam> base64Content = List.of(
              ContentBlockParam.ofImage(
                  ImageBlockParam.builder()
                      .source(Base64ImageSource.builder()
                          .data(imageData)
                          .mediaType(Base64ImageSource.MediaType.IMAGE_JPEG)
                          .build())
                      .build()),
              ContentBlockParam.ofText(
                  TextBlockParam.builder()
                      .text("What is in the above image?")
                      .build())
          );

          Message message = client.messages().create(
              MessageCreateParams.builder()
                  .model(Model.CLAUDE_OPUS_4_7)
                  .maxTokens(1024L)
                  .addUserMessageOfBlockParams(base64Content)
                  .build());
          System.out.println(message);

          // Option 2: URL-referenced image
          List<ContentBlockParam> urlContent = List.of(
              ContentBlockParam.ofImage(
                  ImageBlockParam.builder()
                      .source(UrlImageSource.builder()
                          .url("https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg")
                          .build())
                      .build()),
              ContentBlockParam.ofText(
                  TextBlockParam.builder()
                      .text("What is in the above image?")
                      .build())
          );

          Message messageFromUrl = client.messages().create(
              MessageCreateParams.builder()
                  .model(Model.CLAUDE_OPUS_4_7)
                  .maxTokens(1024L)
                  .addUserMessageOfBlockParams(urlContent)
                  .build());
          System.out.println(messageFromUrl);
      }
  }
  ```

  
  ```php PHP hidelines={1..4} nocheck
  <?php

  use Anthropic\Client;

  $client = new Client(apiKey: getenv("ANTHROPIC_API_KEY"));

  // Option 1: Base64-encoded image
  $image_url = "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg";
  $image_media_type = "image/jpeg";
  $image_data = base64_encode(file_get_contents($image_url));

  $message = $client->messages->create(
      maxTokens: 1024,
      messages: [
          [
              'role' => 'user',
              'content' => [
                  [
                      'type' => 'image',
                      'source' => [
                          'type' => 'base64',
                          'media_type' => $image_media_type,
                          'data' => $image_data,
                      ],
                  ],
                  [
                      'type' => 'text',
                      'text' => 'What is in the above image?',
                  ],
              ],
          ],
      ],
      model: 'claude-opus-4-7',
  );
  echo $message;

  // Option 2: URL-referenced image
  $message_from_url = $client->messages->create(
      maxTokens: 1024,
      messages: [
          [
              'role' => 'user',
              'content' => [
                  [
                      'type' => 'image',
                      'source' => [
                          'type' => 'url',
                          'url' => 'https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg',
                      ],
                  ],
                  [
                      'type' => 'text',
                      'text' => 'What is in the above image?',
                  ],
              ],
          ],
      ],
      model: 'claude-opus-4-7',
  );
  echo $message_from_url;
  ```

  
  ```ruby Ruby nocheck hidelines={1}
  require "anthropic"
  require "base64"
  require "net/http"

  client = Anthropic::Client.new

  # Option 1: Base64-encoded image
  image_url = "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"
  image_media_type = "image/jpeg"
  image_data = Base64.strict_encode64(Net::HTTP.get(URI(image_url)))

  message = client.messages.create(
    model: "claude-opus-4-7",
    max_tokens: 1024,
    messages: [
      {
        role: "user",
        content: [
          {
            type: "image",
            source: {
              type: "base64",
              media_type: image_media_type,
              data: image_data
            }
          },
          {
            type: "text",
            text: "What is in the above image?"
          }
        ]
      }
    ]
  )
  puts message

  # Option 2: URL-referenced image
  message_from_url = client.messages.create(
    model: "claude-opus-4-7",
    max_tokens: 1024,
    messages: [
      {
        role: "user",
        content: [
          {
            type: "image",
            source: {
              type: "url",
              url: "https://upload.wikimedia.org/wikipedia/commons/a/a7/Camponotus_flavomarginatus_ant.jpg"
            }
          },
          {
            type: "text",
            text: "What is in the above image?"
          }
        ]
      }
    ]
  )
  puts message_from_url
  ```
</CodeGroup>

```json Output
{
  "id": "msg_01EcyWo6m4hyW8KHs2y2pei5",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "This image shows an ant, specifically a close-up view of an ant. The ant is shown in detail, with its distinct head, antennae, and legs clearly visible. The image is focused on capturing the intricate details and features of the ant, likely taken with a macro lens to get an extreme close-up perspective."
    }
  ],
  "model": "claude-opus-4-7",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 1551,
    "output_tokens": 71
  }
}
```

## Tool use and computer use

See the [tool use guide](/docs/en/agents-and-tools/tool-use/overview) for examples of how to use tools with the Messages API.
See the [computer use guide](/docs/en/agents-and-tools/tool-use/computer-use-tool) for examples of how to control desktop computer environments with the Messages API.
For guaranteed JSON output, see [Structured Outputs](/docs/en/build-with-claude/structured-outputs).