BedrockModel

Environment variables: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION, BEDROCK_MODEL_ID

import os
from elsai_model.bedrock import BedrockModel

model = BedrockModel(
    model_id=os.getenv("BEDROCK_MODEL_ID", "us.anthropic.claude-3-5-sonnet-20241022-v2:0"),
    region_name=os.getenv("AWS_REGION", "us-east-1"),
    max_tokens=256,
    temperature=0.2,
)
messages = [{"role": "user", "content": "Say hello in one short sentence."}]

response = model.invoke(messages)

for chunk in model.stream_text(messages):
    print(chunk, end="", flush=True)

Or via the factory (AWS credentials, not api_key / params):

from elsai_model import LLM, Provider

model = LLM(
    provider=Provider.BEDROCK,
    model=os.getenv("BEDROCK_MODEL_ID", "us.anthropic.claude-3-5-sonnet-20241022-v2:0"),
    region_name=os.getenv("AWS_REGION", "us-east-1"),
    aws_access_key=os.environ["AWS_ACCESS_KEY_ID"],
    aws_secret_key=os.environ["AWS_SECRET_ACCESS_KEY"],
    max_tokens=256,
    temperature=0.2,
)

Configuration

Parameter	Description
model_id	Bedrock foundation model ID (e.g. us.anthropic.claude-3-5-sonnet-20241022-v2:0)
region_name	AWS region where the model is enabled
max_tokens	Maximum tokens to generate
temperature	Sampling temperature

Credentials are read from the environment (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY) or the default AWS credential chain (IAM role, ~/.aws/credentials).

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See also

• LLM Models overview — install, extras, factory
• LLM factory