# Anthropic Claude Messages API
This section provides inference parameters and code examples for using the Anthropic Claude Messages API.
**Topics**
+ [Anthropic Claude Messages API overview](#model-parameters-anthropic-claude-messages-overview)
+ [Tool use](model-parameters-anthropic-claude-messages-tool-use.md)
+ [Extended thinking](claude-messages-extended-thinking.md)
+ [Adaptive thinking](claude-messages-adaptive-thinking.md)
+ [Thinking encryption](claude-messages-thinking-encryption.md)
+ [Differences in thinking across model versions](claude-messages-thinking-differences.md)
+ [Compaction](claude-messages-compaction.md)
+ [Get validated JSON results from models](claude-messages-structured-outputs.md)
+ [Request and Response](model-parameters-anthropic-claude-messages-request-response.md)
+ [Code examples](api-inference-examples-claude-messages-code-examples.md)
+ [Supported models](claude-messages-supported-models.md)
## Anthropic Claude Messages API overview
You can use the Messages API to create chat bots or virtual assistant applications. The API manages the conversational exchanges between a user and an Anthropic Claude model (assistant).
**Note**
This topic shows how to use the Anthropic Claude messages API with the base inference operations ([InvokeModel](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_InvokeModel.html) or [InvokeModelWithResponseStream](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_InvokeModelWithResponseStream.html)). However, we recommend that you use the Converse API to implement messages in your application. The Converse API provides a unified set of parameters that work across all models that support messages. For more information, see [Carry out a conversation with the Converse API operations](conversation-inference.md).
Restrictions apply to the following operations: `InvokeModel`, `InvokeModelWithResponseStream`, `Converse`, and `ConverseStream`. See [API restrictions](inference-api-restrictions.md) for details.
Anthropic trains Claude models to operate on alternating user and assistant conversational turns. When creating a new message, you specify the prior conversational turns with the messages parameter. The model then generates the next Message in the conversation.
Each input message must be an object with a role and content. You can specify a single user-role message, or you can include multiple user and assistant messages.
If you are using the technique of prefilling the response from Claude (filling in the beginning of Claude's response by using a final assistant role Message), Claude will respond by picking up from where you left off. With this technique, Claude will still return a response with the assistant role.
If the final message uses the assistant role, the response content will continue immediately from the content in that message. You can use this to constrain part of the model's response.
Example with a single user message:
```
[{"role": "user", "content": "Hello, Claude"}]
```
Example with multiple conversational turns:
```
[
{"role": "user", "content": "Hello there."},
{"role": "assistant", "content": "Hi, I'm Claude. How can I help you?"},
{"role": "user", "content": "Can you explain LLMs in plain English?"},
]
```
Example with a partially-filled response from Claude:
```
[
{"role": "user", "content": "Please describe yourself using only JSON"},
{"role": "assistant", "content": "Here is my JSON description:\n{"},
]
```
Each input message content may be either a single string or an array of content blocks, where each block has a specific type. Using a string is shorthand for an array of one content block of type "text". The following input messages are equivalent:
```
{"role": "user", "content": "Hello, Claude"}
```
```
{"role": "user", "content": [{"type": "text", "text": "Hello, Claude"}]}
```
For information about creating prompts for Anthropic Claude models, see [Intro to prompting](https://docs.anthropic.com/claude/docs/intro-to-prompting) in the Anthropic Claude documentation. If you have existing [Text Completion](model-parameters-anthropic-claude-text-completion.md) prompts that you want to migrate to the messages API, see [Migrating from Text Completions](https://docs.anthropic.com/claude/reference/migrating-from-text-completions-to-messages).
**Important**
The timeout period for inference calls to Anthropic Claude 3.7 Sonnet and Claude 4 models is 60 minutes. By default, AWS SDK clients timeout after 1 minute. We recommend that you increase the read timeout period of your AWS SDK client to at least 60 minutes. For example, in the AWS Python botocore SDK, change the value of the `read_timeout` field in [botocore.config](https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html#) to at least 3600.
### System prompts
You can also include a system prompt in the request. A system prompt lets you provide context and instructions to Anthropic Claude, such as specifying a particular goal or role. Specify a system prompt in the `system` field, as shown in the following example.
```
"system": "You are Claude, an AI assistant created by Anthropic to be helpful,
harmless, and honest. Your goal is to provide informative and substantive responses
to queries while avoiding potential harms."
```
For more information, see [System prompts](https://docs.anthropic.com/en/docs/system-prompts) in the Anthropic documentation.
### Multimodal prompts
A multimodal prompt combines multiple modalities (images and text) in a single prompt. You specify the modalities in the `content` input field. The following example shows how you could ask Anthropic Claude to describe the content of a supplied image. For example code, see [Multimodal code examples](api-inference-examples-claude-messages-code-examples.md#api-inference-examples-claude-multimodal-code-example).
```
{
"anthropic_version": "bedrock-2023-05-31",
"max_tokens": 1024,
"messages": [
{
"role": "user",
"content": [
{
"type": "image",
"source": {
"type": "base64",
"media_type": "image/jpeg",
"data": "iVBORw..."
}
},
{
"type": "text",
"text": "What's in these images?"
}
]
}
]
}
```
Each image you include in a request counts towards your token usage. For more information, see [Image costs](https://docs.anthropic.com/claude/docs/vision#image-costs) in the Anthropic documentation.