When creating a Message, you can set "stream": true to incrementally stream the response using server-sent events (SSE).
The Python and TypeScript SDKs offer multiple ways of streaming. The PHP SDK provides streaming via createStream(). The Python SDK allows both sync and async streams. See the documentation in each SDK for details.
import anthropic
client = anthropic.Anthropic()
with client.messages.stream(
max_tokens=1024,
messages=[{"role": "user", "content": "Hello"}],
model="claude-opus-4-6",
) as stream:
for text in stream.text_stream:
print(text, end="", flush=True)If you don't need to process text as it arrives, the SDKs provide a way to use streaming under the hood while returning the complete Message object, identical to what .create() returns. This is especially useful for requests with large max_tokens values, where the SDKs require streaming to avoid HTTP timeouts.
with client.messages.stream(
max_tokens=128000,
messages=[{"role": "user", "content": "Write a detailed analysis..."}],
model="claude-opus-4-6",
) as stream:
message = stream.get_final_message()
The .stream() call keeps the HTTP connection alive with server-sent events, then .get_final_message() (Python) or .finalMessage() (TypeScript) accumulates all events and returns the complete Message object. In Go, you call message.Accumulate(event) inside the stream loop to build the same complete Message. In Java, use MessageAccumulator.create() and call accumulator.accumulate(event) on each event. In Ruby, call .accumulated_message on the stream. In the PHP SDK, you iterate over stream events manually to accumulate the response.
Each server-sent event includes a named event type and associated JSON data. Each event uses an SSE event name (e.g. event: message_stop), and includes the matching event type in its data.
Each stream uses the following event flow:
message_start: contains a Message object with empty content.content_block_start, one or more content_block_delta events, and a content_block_stop event. Each content block has an index that corresponds to its index in the final Message content array.message_delta events, indicating top-level changes to the final Message object.message_stop event.The token counts shown in the usage field of the message_delta event are cumulative.
Event streams may also include any number of ping events.
The API may occasionally send 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:
event: error
data: {"type": "error", "error": {"type": "overloaded_error", "message": "Overloaded"}}In accordance with the versioning policy, new event types may be added, and your code should handle unknown event types gracefully.
Each content_block_delta event contains a delta of a type that updates the content block at a given index.
A text content block delta looks like:
event: content_block_delta
data: {"type": "content_block_delta","index": 0,"delta": {"type": "text_delta", "text": "ello frien"}}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 to do partial JSON parsing, or by using the SDKs, which provide helpers to access parsed incremental values.
A tool_use content block delta looks like:
event: content_block_delta
data: {"type": "content_block_delta","index": 1,"delta": {"type": "input_json_delta","partial_json": "{\"location\": \"San Fra"}}}Note: 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, they are emitted as multiple content_block_delta events with chunked partial json so that the format can automatically support finer granularity in future models.
When using extended 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:
event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "I need to find the GCD of 1071 and 462 using the Euclidean algorithm.\n\n1071 = 2 × 462 + 147"}}The signature delta looks like:
event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "signature_delta", "signature": "EqQBCgIYAhIM1gbcDa9GJwZA2b3hGgxBdjrkzLoky3dl1pkiMOYds..."}}Use the client SDKs when using streaming mode. However, if you are building a direct API integration, you need to handle these events yourself.
A stream response is comprised of:
message_start eventcontent_block_start eventcontent_block_delta eventscontent_block_stop eventmessage_delta eventmessage_stop eventThere may be ping events dispersed throughout the response as well. See Event types for more details on the format.
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-opus-4-6",
"messages": [{"role": "user", "content": "Hello"}],
"max_tokens": 256,
"stream": true
}'event: message_start
data: {"type": "message_start", "message": {"id": "msg_1nZdL29xx5MUA1yADyHTEsnR8uuvGzszyY", "type": "message", "role": "assistant", "content": [], "model": "claude-opus-4-6", "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"}
Tool use supports fine-grained streaming for parameter values. Enable it per tool with eager_input_streaming.
This request asks Claude to use a tool to report the weather.
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-opus-4-6",
"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
}'event: message_start
data: {"type":"message_start","message":{"id":"msg_014p7gG3wDgGV9EUtLvnow3U","type":"message","role":"assistant","model":"claude-opus-4-6","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"}This request enables extended thinking with streaming to see Claude's step-by-step reasoning.
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-4-6",
"max_tokens": 20000,
"stream": true,
"thinking": {
"type": "enabled",
"budget_tokens": 16000
},
"messages": [
{
"role": "user",
"content": "What is the greatest common divisor of 1071 and 462?"
}
]
}'event: message_start
data: {"type": "message_start", "message": {"id": "msg_01...", "type": "message", "role": "assistant", "content": [], "model": "claude-opus-4-6", "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": "I need to find the GCD of 1071 and 462 using the Euclidean algorithm.\n\n1071 = 2 × 462 + 147"}}
event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "\n462 = 3 × 147 + 21"}}
event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "\n147 = 7 × 21 + 0"}}
event: content_block_delta
data: {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "\nThe remainder is 0, so GCD(1071, 462) = 21."}}
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": "The greatest common divisor of 1071 and 462 is **21**."}}
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"}This request asks Claude to search the web for current weather information.
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-4-6",
"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?"
}
]
}'event: message_start
data: {"type":"message_start","message":{"id":"msg_01G...","type":"message","role":"assistant","model":"claude-opus-4-6","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"}For Claude 4.5 models and earlier, you can recover a streaming request that was interrupted due to network issues, timeouts, or other errors by resuming from where the stream was interrupted. This approach saves you from re-processing the entire response.
The basic recovery strategy involves:
For Claude 4.6 models, you should add a user message that instructs the model to continue from where it left off. For example:
Your previous response was interrupted and ended with [previous_response]. Continue from where you left off.text, tool_use, thinking). Tool use and extended thinking blocks cannot be partially recovered. You can resume streaming from the most recent text block.Was this page helpful?