app.py

import boto3

from InquirerPy import inquirer


# Create an Amazon Bedrock Runtime client
bedrock_client = boto3.client('bedrock-runtime')

# dictionary that contains multiple model ids
model_ids = [
    "mistral.mistral-7b-instruct-v0:2",
    "mistral.mistral-large-2402-v1:0",
    "mistral.mistral-large-2407-v1:0",
    "mistral.mixtral-8x7b-instruct-v0:1",
    "meta.llama3-70b-instruct-v1:0",
    "meta.llama3-8b-instruct-v1:0",
    "meta.llama3-1-8b-instruct-v1:0",
]

# Prompt the user to select a model


selected_model_name = inquirer.fuzzy(
        message="Select a model:",
        choices=model_ids
        ).execute()


# Prompt a user for a question
print("Enter your question (or 'q' to quit):")
user_input = input("> ")
if user_input.lower() == 'q':
    exit()
else:
    user_message = user_input


system_prompts = [{"text" : "You are an expert in all things Amazon Bedrock. You are a helpful assistant. But every explanation that you give uses food related puns."}] 


# Create the initial conversation with the user's message
conversation = [
    {
        "role": "user",
        "content": [{"text": user_message}]
    }
]

try:
    # Send the message to the model using the Converse API
    response = bedrock_client.converse_stream(
        modelId=selected_model_name,
        messages=conversation,
        system=system_prompts,
        inferenceConfig={"maxTokens": 512, "temperature": 0.5, "topP": 0.9}
    )

    # Process the streaming response
    stream = response.get('stream')
    if stream:
        for event in stream:
            if 'messageStart' in event:
                print(f"\nRole: {event['messageStart']['role']}")

            if 'contentBlockDelta' in event:
                print(event['contentBlockDelta']['delta']['text'], end="")

except Exception as e:
    print(f"Error: {e}")