Tired of Bedrock Latency? Build a Serverless Claude Chatbot Using API Gateway and Lambda

Tired of Bedrock Latency? Build a Serverless Claude Chatbot Using API Gateway and Lambda

Question 

"Hi there! I’ve been running into serious latency issues with Bedrock, and I’ve decided to move my chatbot over to the Claude API instead. I want to build and deploy it using API Gateway and Lambda, but I’m not sure how to set it up. Can you walk me through the process step by step? Thanks!" – Jurgen

Greeting 

Hi Jurgen! Thanks for reaching out. It sounds like you’ve made a solid decision to simplify your architecture and take control of your chatbot’s performance. Let’s walk through exactly how you can deploy your Claude-powered chatbot using API Gateway and Lambda. We’ve got your back! 😊

Clarifying the Issue 

Latency can be a dealbreaker for chatbots, and Bedrock’s extra abstraction might not be ideal for your needs. By moving to the Claude API directly and setting it up with API Gateway and Lambda, you’ll create a fast, serverless solution that avoids Bedrock’s latency overhead while remaining tightly integrated with AWS’s other services.

Why It Matters 

Having a responsive chatbot is critical to user engagement. API Gateway and Lambda offer a simple yet powerful framework to:

• Eliminate infrastructure management with serverless hosting.
• Scale automatically with traffic demands.
• Reduce costs by only paying for what you use.
• Integrate smoothly with other AWS tools like S3 and DynamoDB.

This approach ensures your chatbot is both efficient and easy to maintain.

Key Terms 

• API Gateway: A fully managed service to expose your chatbot’s HTTP endpoint. 
• AWS Lambda: A serverless compute service to handle the chatbot’s logic. 
• Claude API: The API powering your chatbot’s AI capabilities. 
• Serverless: A computing model where you focus on code, not infrastructure.

Steps at a Glance

1. Write or adapt your chatbot code to work with the Claude API.
2. Deploy your code to AWS Lambda.
3. Create an HTTP API in API Gateway.
4. Understand the architecture flow.
5. Test your endpoint and monitor performance.

Detailed Steps

Step 1: Prepare Your Chatbot Code 

Here’s how your chatbot function might look in Python, broken down step by step:

Python

import json
import requests  # Import the library for making API calls to Claude

# Lambda function handler
def lambda_handler(event, context):
    # Step 1: Extract user input from the API Gateway event
    user_input = event['body']

    # Step 2: Send a request to the Claude API
    response = requests.post(
        "https://api.claude.ai/endpoint",  # Replace with the Claude API URL
        headers={"Authorization": "Bearer YOUR_API_KEY"},  # Insert your API key here
        json={"input": user_input}  # Pass the user's input to the Claude API
    )

    # Step 3: Format the Claude API response for the user
    return {
        "statusCode": 200,  # HTTP success status
        "body": json.dumps(response.json())  # Return the API response as JSON
    }

How This Works: The code is structured to take the user's input, pass it to the Claude API, and return the response seamlessly. AWS Lambda will trigger this function whenever a request is made to your API Gateway endpoint.

Step 2: Deploy to AWS Lambda 

1. Log in to AWS Lambda Console:
   Click "Create Function" and choose "Author from scratch." 
2. Set Runtime:
   Select Python (or your chatbot’s language). 
3. Upload Code:
   ZIP your chatbot script and upload it. 
4. Set Environment Variables:
   Add YOUR_API_KEY as an environment variable for the Claude API key. 
5. Test Your Function:
   Use the built-in Lambda test feature to ensure it responds correctly to mock input.

Step 3: Set Up API Gateway

1. Navigate to the API Gateway Console and create a new HTTP API. 
2. Define a route:
   Path: /chatbot
   Method: POST
3. Link the route to your Lambda function:
   Choose your function from the dropdown. 
4. Deploy the API:
   Create a stage (e.g., “prod”) and deploy your API.

Step 4: Understand the Architecture Flow

This step provides a high-level view of how your chatbot operates within the API Gateway and Lambda setup. Here's the interaction flow represented visually as a Linux tree-style diagram:

Chatbot Interaction
├── User Input
│   └── Sent via an HTTP request to API Gateway
├── API Gateway
│   └── Routes the request to the Lambda function
├── Lambda Function
│   ├── Executes chatbot logic
│   ├── Calls the Claude API
│   └── Formats the response
├── Claude API
│   └── Returns the chatbot's response to Lambda
├── Lambda Function (Again)
│   └── Sends the response back to API Gateway
└── API Gateway
    └── Forwards the response to the user

This hierarchy simplifies the workflow and makes it easy to visualize the flow of data.

Step 5: Test Your Endpoint

Use Postman or cURL to test your API:

Bash

curl -X POST -H "Content-Type: application/json" \
-d '{"body":"Hello"}' \
https://api-id.execute-api.region.amazonaws.com/prod/chatbot

Verify that your Lambda function is triggered and responds correctly.

Closing Thoughts

Great job, Jurgen! With API Gateway and Lambda, you now have a serverless chatbot that’s lightweight, scalable, and free from Bedrock’s latency issues. This solution also gives you the flexibility to expand with other AWS services as your chatbot evolves. Let us know how it works out—your users will thank you for the improved speed and responsiveness!

Farewell

Best of luck with your Claude-powered chatbot, Jurgen! Keep innovating, and let us know if you need more help along the way. 🚀😊

Need AWS Expertise?

If you're looking for guidance on AWS challenges or want to collaborate, feel free to reach out! We'd love to help you tackle your cloud projects. 🚀

Email us at: info@pacificw.com

Image: Vilkasss from Pixabay