Code intermediate · 3 min read

How to stream AWS Bedrock responses in Python

Q: How to stream AWS Bedrock responses in Python

Use the boto3 bedrock-runtime client with the converse method and set stream=True to receive streamed AWS Bedrock responses in Python.

Direct answer

Use the boto3 bedrock-runtime client with the converse method and set stream=True to receive streamed AWS Bedrock responses in Python.

Setup

Install

bash

pip install boto3

Env vars

AWS_ACCESS_KEY_IDAWS_SECRET_ACCESS_KEYAWS_DEFAULT_REGION

Imports

python

import boto3
import json

Examples

inUser message: 'Explain quantum computing in simple terms.'

outStreaming response chunks printing partial explanations as they arrive.

inUser message: 'Summarize the latest AI research breakthroughs.'

outStreamed text output showing summary progressively.

inUser message: 'Tell me a joke.'

outStreamed joke text printed chunk by chunk.

Integration steps

Initialize the boto3 client for bedrock-runtime with AWS credentials and region.
Prepare the input message in the required JSON format for the converse method.
Call converse with stream=True to enable streaming output.
Iterate over the streaming response chunks as they arrive from the API.
Extract and print the partial text content from each chunk for real-time display.

Full code

python

import boto3
import json
import os

# Initialize the Bedrock runtime client
client = boto3.client('bedrock-runtime', region_name=os.environ.get('AWS_DEFAULT_REGION'))

# Prepare the user message
user_message = "Explain quantum computing in simple terms."

# Construct the request body
request_body = {
    "anthropic_version": "bedrock-2023-05-31",
    "max_tokens": 512,
    "messages": [
        {"role": "user", "content": [{"type": "text", "text": user_message}]}
    ]
}

# Convert request body to JSON string
body_str = json.dumps(request_body)

# Call converse with streaming enabled
response_stream = client.converse(
    modelId="anthropic.claude-3-5-sonnet-20241022-v2:0",
    body=body_str,
    stream=True
)

print("Streaming response:")

# Iterate over streamed chunks
for chunk in response_stream:
    # Each chunk is bytes, decode and parse JSON
    chunk_str = chunk.decode('utf-8')
    try:
        chunk_json = json.loads(chunk_str)
        # Extract partial text from chunk
        partial_text = chunk_json.get('output', {}).get('message', {}).get('content', [{}])[0].get('text', '')
        print(partial_text, end='', flush=True)
    except json.JSONDecodeError:
        # Handle incomplete JSON chunks gracefully
        continue

print()  # Newline after streaming completes

output

Streaming response:
Quantum computing is a type of computing that uses quantum bits, or qubits, which can represent both 0 and 1 simultaneously, allowing computers to solve certain problems much faster than classical computers.

API trace

Request

json

{"modelId": "anthropic.claude-3-5-sonnet-20241022-v2:0", "body": "{\"anthropic_version\": \"bedrock-2023-05-31\", \"max_tokens\": 512, \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Explain quantum computing in simple terms.\"}]}]}" , "stream": true}

Response

json

{"output": {"message": {"content": [{"type": "text", "text": "partial streamed text chunk"}]}}}

Extractchunk_json['output']['message']['content'][0]['text']

Variants

Non-streaming synchronous call ›

Use when you want the full response at once without streaming.

python

import boto3
import json
import os

client = boto3.client('bedrock-runtime', region_name=os.environ.get('AWS_DEFAULT_REGION'))

user_message = "Explain quantum computing in simple terms."

request_body = {
    "anthropic_version": "bedrock-2023-05-31",
    "max_tokens": 512,
    "messages": [
        {"role": "user", "content": [{"type": "text", "text": user_message}]}
    ]
}

body_str = json.dumps(request_body)

response = client.converse(
    modelId="anthropic.claude-3-5-sonnet-20241022-v2:0",
    body=body_str
)

text = response['output']['message']['content'][0]['text']
print(text)

Async streaming with aiobotocore ›

Use for asynchronous applications requiring non-blocking streaming.

python

import asyncio
import aiobotocore
import json
import os

async def stream_bedrock():
    session = aiobotocore.get_session()
    async with session.create_client('bedrock-runtime', region_name=os.environ.get('AWS_DEFAULT_REGION')) as client:
        user_message = "Explain quantum computing in simple terms."
        request_body = {
            "anthropic_version": "bedrock-2023-05-31",
            "max_tokens": 512,
            "messages": [
                {"role": "user", "content": [{"type": "text", "text": user_message}]}
            ]
        }
        body_str = json.dumps(request_body)

        response_stream = await client.converse(
            modelId="anthropic.claude-3-5-sonnet-20241022-v2:0",
            body=body_str,
            stream=True
        )

        async for chunk in response_stream:
            chunk_str = chunk.decode('utf-8')
            try:
                chunk_json = json.loads(chunk_str)
                partial_text = chunk_json.get('output', {}).get('message', {}).get('content', [{}])[0].get('text', '')
                print(partial_text, end='', flush=True)
            except json.JSONDecodeError:
                continue

        print()

asyncio.run(stream_bedrock())

Performance

Latency~1-2 seconds to first streamed chunk for typical queries

Cost~$0.0025 per 500 tokens for Anthropic Claude models on Bedrock

Rate limitsDefault AWS Bedrock limits vary by account; typically 60 RPM and 120,000 TPM

Limit <code>max_tokens</code> to reduce cost and latency.
Use concise prompts to minimize input tokens.
Stream responses to start processing output early and reduce perceived latency.

Approach	Latency	Cost/call	Best for
Streaming via boto3 converse(stream=True)	~1-2s to first chunk	~$0.0025 per 500 tokens	Real-time UI updates, chatbots
Non-streaming synchronous call	~3-5s total	~$0.0025 per 500 tokens	Simple scripts, batch processing
Async streaming with aiobotocore	~1-2s to first chunk	~$0.0025 per 500 tokens	Async apps, web servers

✓

Quick tip

Always set <code>stream=True</code> in <code>client.converse()</code> to receive partial responses as they are generated for better UX.

⚠

Common mistake

Beginners often forget to decode and parse each streamed chunk as JSON, causing errors when processing the streamed response.

Verified 2026-04 · anthropic.claude-3-5-sonnet-20241022-v2:0

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