1380 Streaming A39c5aea

# Streaming Messages

---

When creating a Message, you can set `"stream": true` to incrementally stream the response using [server-sent events](https://developer.mozilla.org/en-US/Web/API/Server-sent%5Fevents/Using%5Fserver-sent%5Fevents) (SSE).

## Streaming with SDKs

Our [Python](https://github.com/anthropics/anthropic-sdk-python) and [TypeScript](https://github.com/anthropics/anthropic-sdk-typescript) SDKs offer multiple ways of streaming. The Python SDK allows both sync and async streams. See the documentation in each SDK for details.

<CodeGroup>
    ```python Python
    import anthropic

    client = anthropic.Anthropic()

    with client.messages.stream(
        max_tokens=1024,
        messages=[{"role": "user", "content": "Hello"}],
        model="claude-sonnet-4-5",
    ) as stream:
      for text in stream.text_stream:
          print(text, end="", flush=True)
    ```

    ```typescript TypeScript
    import Anthropic from '@anthropic-ai/sdk';

    const client = new Anthropic();

    await client.messages.stream({
        messages: [{role: 'user', content: "Hello"}],
        model: 'claude-sonnet-4-5',
        max_tokens: 1024,
    }).on('text', (text) => {
        console.log(text);
    });
    ```
</CodeGroup>

## Event types

Each server-sent event includes a named event type and associated JSON data. Each event will use an SSE event name (e.g. `event: message_stop`), and include the matching event `type` in its data.

Each stream uses the following event flow:

1. `message_start`: contains a `Message` object with empty `content`.
2. A series of content blocks, each of which have a `content_block_start`, one or more `content_block_delta` events, and a `content_block_stop` event. Each content block will have an `index` that corresponds to its index in the final Message `content` array.
3. One or more `message_delta` events, indicating top-level changes to the final `Message` object.
4. A final `message_stop` event.

  <Warning>
  The token counts shown in the `usage` field of the `message_delta` event are *cumulative*.
  </Warning>

### Ping events

Event streams may also include any number of `ping` events.

### Error events

We may occasionally send [errors](/docs/en/api/errors) in the event stream. For example, during periods of high usage, you may receive an `overloaded_error`, which would normally correspond to an HTTP 529 in a non-streaming context:

```json Example error
event: error
data: {"type": "error", "error": {"type": "overloaded_error", "message": "Overloaded"}}
```

### Other events

In accordance with our [versioning policy](/docs/en/api/versioning), we may add new event types, and your code should handle unknown event types gracefully.

## Content block delta types

Each `content_block_delta` event contains a `delta` of a type that updates the `content` block at a given `index`.

### Text delta

A `text` content block delta looks like:
```json Text delta
event: content_block_delta
data: {"type": "content_block_delta","index": 0,"delta": {"type": "text_delta", "text": "ello frien"}}
```

### Input JSON delta

The deltas for `tool_use` content blocks correspond to updates for the `input` field of the block. To support maximum granularity, the deltas are _partial JSON strings_, whereas the final `tool_use.input` is always an _object_.

You can accumulate the string deltas and parse the JSON once you receive a `content_block_stop` event, by using a library like [Pydantic](https://docs.pydantic.dev/latest/concepts/json/#partial-json-parsing) to do partial JSON parsing, or by using our [SDKs](/docs/en/api/client-sdks), which provide helpers to access parsed incremental values.

A `tool_use` content block delta looks like:
```json Input JSON delta
event: content_block_delta
data: {"type": "content_block_delta","index": 1,"delta": {"type": "input_json_delta","partial_json": "{\"location\": \"San Fra"}}}
```
Note: Our current models only support emitting one complete key and value property from `input` at a time. As such, when using tools, there may be delays between streaming events while the model is working. Once an `input` key and value are accumulated, we emit them as multiple `content_block_delta` events with chunked partial json so that the format can automatically support finer granularity in future models.

### Thinking delta

When using [extended thinking](/docs/en/build-with-claude/extended-thinking#streaming-thinking) with streaming enabled, you'll receive thinking content via `thinking_delta` events. These deltas correspond to the `thinking` field of the `thinking` content blocks.

For thinking content, a special `signature_delta` event is sent just before the `content_block_stop` event. This signature is used to verify the integrity of the thinking block.

A typical thinking delta looks like:
```json Thinking delta
event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "Let me solve this step by step:\n\n1. First break down 27 * 453"}}
```

The signature delta looks like:
```json Signature delta
event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "signature_delta", "signature": "EqQBCgIYAhIM1gbcDa9GJwZA2b3hGgxBdjrkzLoky3dl1pkiMOYds..."}}
```

## Full HTTP Stream response

We strongly recommend that you use our [client SDKs](/docs/en/api/client-sdks) when using streaming mode. However, if you are building a direct API integration, you will need to handle these events yourself.

A stream response is comprised of:
1. A `message_start` event
2. Potentially multiple content blocks, each of which contains:
    - A `content_block_start` event
    - Potentially multiple `content_block_delta` events
    - A `content_block_stop` event
3. A `message_delta` event
4. A `message_stop` event

There may be `ping` events dispersed throughout the response as well. See [Event types](#event-types) for more details on the format.

### Basic streaming request

<CodeGroup>
```bash Shell
curl https://api.anthropic.com/v1/messages \
     --header "anthropic-version: 2023-06-01" \
     --header "content-type: application/json" \
     --header "x-api-key: $ANTHROPIC_API_KEY" \
     --data \
'{
  "model": "claude-sonnet-4-5",
  "messages": [{"role": "user", "content": "Hello"}],
  "max_tokens": 256,
  "stream": true
}'
```

```python Python
import anthropic

client = anthropic.Anthropic()

with client.messages.stream(
    model="claude-sonnet-4-5",
    messages=[{"role": "user", "content": "Hello"}],
    max_tokens=256,
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
```
</CodeGroup>

```json Response
event: message_start
data: {"type": "message_start", "message": {"id": "msg_1nZdL29xx5MUA1yADyHTEsnR8uuvGzszyY", "type": "message", "role": "assistant", "content": [], "model": "claude-sonnet-4-5-20250929", "stop_reason": null, "stop_sequence": null, "usage": {"input_tokens": 25, "output_tokens": 1}}}

event: content_block_start
data: {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}}

event: ping
data: {"type": "ping"}

event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "Hello"}}

event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "!"}}

event: content_block_stop
data: {"type": "content_block_stop", "index": 0}

event: message_delta
data: {"type": "message_delta", "delta": {"stop_reason": "end_turn", "stop_sequence":null}, "usage": {"output_tokens": 15}}

event: message_stop
data: {"type": "message_stop"}

```

### Streaming request with tool use

<Tip>
Tool use now supports fine-grained streaming for parameter values as a beta feature. For more details, see [Fine-grained tool streaming](/docs/en/agents-and-tools/tool-use/fine-grained-tool-streaming).
</Tip>

In this request, we ask Claude to use a tool to tell us the weather.

<CodeGroup>
```bash Shell
  curl https://api.anthropic.com/v1/messages \
    -H "content-type: application/json" \
    -H "x-api-key: $ANTHROPIC_API_KEY" \
    -H "anthropic-version: 2023-06-01" \
    -d '{
      "model": "claude-sonnet-4-5",
      "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"]
          }
        }
      ],
      "tool_choice": {"type": "any"},
      "messages": [
        {
          "role": "user",
          "content": "What is the weather like in San Francisco?"
        }
      ],
      "stream": true
    }'
```

```python Python
import anthropic

client = anthropic.Anthropic()

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"]
        }
    }
]

with client.messages.stream(
    model="claude-sonnet-4-5",
    max_tokens=1024,
    tools=tools,
    tool_choice={"type": "any"},
    messages=[
        {
            "role": "user",
            "content": "What is the weather like in San Francisco?"
        }
    ],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
```
</CodeGroup>

```json Response
event: message_start
data: {"type":"message_start","message":{"id":"msg_014p7gG3wDgGV9EUtLvnow3U","type":"message","role":"assistant","model":"claude-sonnet-4-5-20250929","stop_sequence":null,"usage":{"input_tokens":472,"output_tokens":2},"content":[],"stop_reason":null}}

event: content_block_start
data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}

event: ping
data: {"type": "ping"}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Okay"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":","}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" let"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"'s"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" check"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" the"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" weather"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" for"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" San"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" Francisco"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":","}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" CA"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":":"}}

event: content_block_stop
data: {"type":"content_block_stop","index":0}

event: content_block_start
data: {"type":"content_block_start","index":1,"content_block":{"type":"tool_use","id":"toolu_01T1x1fJ34qAmk2tNTrN7Up6","name":"get_weather","input":{}}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":""}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"{\"location\":"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":" \"San"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":" Francisc"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"o,"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":" CA\""}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":", "}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"\"unit\": \"fah"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"renheit\"}"}}

event: content_block_stop
data: {"type":"content_block_stop","index":1}

event: message_delta
data: {"type":"message_delta","delta":{"stop_reason":"tool_use","stop_sequence":null},"usage":{"output_tokens":89}}

event: message_stop
data: {"type":"message_stop"}
```

### Streaming request with extended thinking

In this request, we enable extended thinking with streaming to see Claude's step-by-step reasoning.

<CodeGroup>
```bash Shell
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": 20000,
    "stream": true,
    "thinking": {
        "type": "enabled",
        "budget_tokens": 16000
    },
    "messages": [
        {
            "role": "user",
            "content": "What is 27 * 453?"
        }
    ]
}'
```

```python Python
import anthropic

client = anthropic.Anthropic()

with client.messages.stream(
    model="claude-sonnet-4-5",
    max_tokens=20000,
    thinking={
        "type": "enabled",
        "budget_tokens": 16000
    },
    messages=[
        {
            "role": "user",
            "content": "What is 27 * 453?"
        }
    ],
) as stream:
    for event in stream:
        if event.type == "content_block_delta":
            if event.delta.type == "thinking_delta":
                print(event.delta.thinking, end="", flush=True)
            elif event.delta.type == "text_delta":
                print(event.delta.text, end="", flush=True)
```
</CodeGroup>

```json Response
event: message_start
data: {"type": "message_start", "message": {"id": "msg_01...", "type": "message", "role": "assistant", "content": [], "model": "claude-sonnet-4-5-20250929", "stop_reason": null, "stop_sequence": null}}

event: content_block_start
data: {"type": "content_block_start", "index": 0, "content_block": {"type": "thinking", "thinking": ""}}

event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "Let me solve this step by step:\n\n1. First break down 27 * 453"}}

event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "\n2. 453 = 400 + 50 + 3"}}

event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "\n3. 27 * 400 = 10,800"}}

event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "\n4. 27 * 50 = 1,350"}}

event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "\n5. 27 * 3 = 81"}}

event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "\n6. 10,800 + 1,350 + 81 = 12,231"}}

event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "signature_delta", "signature": "EqQBCgIYAhIM1gbcDa9GJwZA2b3hGgxBdjrkzLoky3dl1pkiMOYds..."}}

event: content_block_stop
data: {"type": "content_block_stop", "index": 0}

event: content_block_start
data: {"type": "content_block_start", "index": 1, "content_block": {"type": "text", "text": ""}}

event: content_block_delta
data: {"type": "content_block_delta", "index": 1, "delta": {"type": "text_delta", "text": "27 * 453 = 12,231"}}

event: content_block_stop
data: {"type": "content_block_stop", "index": 1}

event: message_delta
data: {"type": "message_delta", "delta": {"stop_reason": "end_turn", "stop_sequence": null}}

event: message_stop
data: {"type": "message_stop"}
```

### Streaming request with web search tool use

In this request, we ask Claude to search the web for current weather information.

<CodeGroup>
```bash Shell
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": 1024,
    "stream": true,
    "tools": [
        {
            "type": "web_search_20250305",
            "name": "web_search",
            "max_uses": 5
        }
    ],
    "messages": [
        {
            "role": "user",
            "content": "What is the weather like in New York City today?"
        }
    ]
}'
```

```python Python
import anthropic

client = anthropic.Anthropic()

with client.messages.stream(
    model="claude-sonnet-4-5",
    max_tokens=1024,
    tools=[
        {
            "type": "web_search_20250305",
            "name": "web_search",
            "max_uses": 5
        }
    ],
    messages=[
        {
            "role": "user",
            "content": "What is the weather like in New York City today?"
        }
    ],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
```
</CodeGroup>

```json Response
event: message_start
data: {"type":"message_start","message":{"id":"msg_01G...","type":"message","role":"assistant","model":"claude-sonnet-4-5-20250929","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":2679,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":3}}}

event: content_block_start
data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"I'll check"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" the current weather in New York City for you"}}

event: ping
data: {"type": "ping"}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"."}}

event: content_block_stop
data: {"type":"content_block_stop","index":0}

event: content_block_start
data: {"type":"content_block_start","index":1,"content_block":{"type":"server_tool_use","id":"srvtoolu_014hJH82Qum7Td6UV8gDXThB","name":"web_search","input":{}}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":""}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"{\"query"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"\":"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":" \"weather"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":" NY"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"C to"}}

event: content_block_delta
data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"day\"}"}}

event: content_block_stop
data: {"type":"content_block_stop","index":1 }

event: content_block_start
data: {"type":"content_block_start","index":2,"content_block":{"type":"web_search_tool_result","tool_use_id":"srvtoolu_014hJH82Qum7Td6UV8gDXThB","content":[{"type":"web_search_result","title":"Weather in New York City in May 2025 (New York) - detailed Weather Forecast for a month","url":"https://world-weather.info/forecast/usa/new_york/may-2025/","encrypted_content":"Ev0DCioIAxgCIiQ3NmU4ZmI4OC1k...","page_age":null},...]}}

event: content_block_stop
data: {"type":"content_block_stop","index":2}

event: content_block_start
data: {"type":"content_block_start","index":3,"content_block":{"type":"text","text":""}}

event: content_block_delta
data: {"type":"content_block_delta","index":3,"delta":{"type":"text_delta","text":"Here's the current weather information for New York"}}

event: content_block_delta
data: {"type":"content_block_delta","index":3,"delta":{"type":"text_delta","text":" City:\n\n# Weather"}}

event: content_block_delta
data: {"type":"content_block_delta","index":3,"delta":{"type":"text_delta","text":" in New York City"}}

event: content_block_delta
data: {"type":"content_block_delta","index":3,"delta":{"type":"text_delta","text":"\n\n"}}

...

event: content_block_stop
data: {"type":"content_block_stop","index":17}

event: message_delta
data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"input_tokens":10682,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":510,"server_tool_use":{"web_search_requests":1}}}

event: message_stop
data: {"type":"message_stop"}
```

## Error recovery

When a streaming request is interrupted due to network issues, timeouts, or other errors, you can recover by resuming from where the stream was interrupted. This approach saves you from re-processing the entire response.

The basic recovery strategy involves:

1. **Capture the partial response**: Save all content that was successfully received before the error occurred
2. **Construct a continuation request**: Create a new API request that includes the partial assistant response as the beginning of a new assistant message
3. **Resume streaming**: Continue receiving the rest of the response from where it was interrupted

### Error recovery best practices

1. **Use SDK features**: Leverage the SDK's built-in message accumulation and error handling capabilities
2. **Handle content types**: Be aware that messages can contain multiple content blocks (`text`, `tool_use`, `thinking`). Tool use and extended thinking blocks cannot be partially recovered. You can resume streaming from the most recent text block.