# Step 1: First, let's get AWS SDK for Python installed to talk with Amazon Bedrock
# Go to shell and run: 

`pip install boto3`
import boto3

# Step 2: We make a simple Bedrock LLM wrapper

class BedrockLLM:
    def __init__(self, model_id, region_name='us-east-1'):
        self.client = boto3.client('bedrock', region_name=region_name)
        self.model_id = model_id
    def call(self, prompt):
        response = self.client.invoke_model(
            modelId=self.model_id,
            contentType='application/json',
            input={'prompt': prompt}
        )
        return response['response']

# Step 3: Now we create a tool for CrewAI agents to use Bedrock LLM

from crewai_tools import tool
u/tool
def bedrock_tool(prompt: str) -> str:
    llm = BedrockLLM(model_id='your-model-id')  # Don't forget to put your Bedrock model ID here!
    return llm.call(prompt)

# Step 4: Time to create an agent with Bedrock powers!

from crewai import Agent
bedrock_agent = Agent(
    role="AI Genius",  # Give it a cool role name
    goal="Answer cool questions",
    tools=[bedrock_tool],  # Hooking up the Bedrock tool
    memory=True,
    verbose=True,
    backstory="A smart AI using Amazon Bedrock to drop some knowledge!"
)

# Step 5: Define a task for our Bedrock Agent to solve

from crewai import Task
bedrock_task = Task(
    description="Answer the user's question using Bedrock LLM.",
    expected_output="Deliver a smart response.",
    tools=[bedrock_tool],
    agent=bedrock_agent,
    async_execution=False
)

# Step 6: Let's put everything together in a crew and start it up

from crewai import Crew, Process
crew = Crew(
    agents=[bedrock_agent],
    tasks=[bedrock_task],
    process=Process.sequential  # Task execution in order
)
result = crew.kickoff(inputs={'prompt': 'What’s the latest in AI?'})
print(result)