Integration: Amazon Bedrock

Integration with an Amazon Bedrock application is straightforward with openllmtelemetry package.

First, you need to set a few environment variables. This can be done via your container set up or via code.

import openllmtelemetry

openllmtelemetry.instrument()

Output

Set WhyLabs API Key: ··········
Using WhyLabs API key with ID:  D66fSX6Znf
Set GuardRails endpoint (leave blank to skip guardrail): https://<guardrails-endpoint>
Set GuardRails API Key: ··········
Using GuardRails API key with prefix:  wjYDn8
Do you want to save these settings to a configuration file? [y/n]: y

Once this is done, all of your Amazon Bedrock interactions will be automatically traced. If you have rulesets enabled for blocking in WhyLabs Secure policy, the library will block requests accordingly

import boto3
import json

#Create the connection to Bedrock
bedrock = boto3.client(
    service_name='bedrock',
    region_name='us-west-2', 
    
)

bedrock_runtime = boto3.client(
    service_name='bedrock-runtime',
    region_name='us-west-2', 
    
)

# Define prompt and model parameters
prompt_data = """Write me a poem about apples"""

#The Text Generation Configuration are Titans inference parameters 
text_gen_config = {
    "maxTokenCount": 512,
    "stopSequences": [], 
    "temperature": 0,
    "topP": 0.9
}

body = json.dumps({
    # "inputText": prompt_data,
    "prompt": prompt_data,
    # "textGenerationConfig": text_gen_config  
})

model_id = 'ai21.j2-ultra-v1'
accept = 'application/json' 
content_type = 'application/json'

# Invoke model 
response = bedrock_runtime.invoke_model(
    body=body, 
    modelId=model_id, 
    accept=accept, 
    contentType=content_type
)