Chat Playground using Amazon Bedrock and Streamlit

This project is a simple chat application built using Streamlit that interfaces with Amazon Bedrock's Anthropic Claude model to generate responses to user input. The application allows users to type a message and receive a generated response using the power of AI.

Features

• Real-time Chat: Interact with an AI model to generate responses based on user input.
• Streamlit Interface: Provides an easy-to-use web interface for inputting text and viewing responses.
• Amazon Bedrock Integration: Leverages AWS's Bedrock service to invoke the Claude model for text generation.

Prerequisites

Before you begin, ensure you have met the following requirements:

• AWS Account: You need an AWS account with access to the Bedrock service.
• AWS CLI Configured: Ensure that your AWS CLI is configured with the appropriate credentials and region (e.g., us-east-1).
• Python 3.x: This project is built with Python, so you'll need Python installed on your system.
• Streamlit: Install Streamlit using pip:

  pip install streamlit
  
  

Installation

1. Clone the Repository:

   git clone <repository_url>
   cd <repository_directory>

2. Install Dependencies: Install the required Python packages:

   pip install -r requirements.txt

3. Configure AWS Credentials: Ensure your AWS credentials are configured in your environment. You can do this by running:

   aws configure

Usage

To run the application, execute the following command:

streamlit run app.py

This will launch a local web server, and you can interact with the chat interface in your browser.

Code Explanation

• generate_response(prompt): This function takes a user's input (prompt) and sends a request to the Anthropic Claude model using Amazon Bedrock. It returns the model's response text.
• Streamlit Interface:
  • The user input is captured using st.text_input.
  • Upon pressing the "Send" button, the generate_response function is invoked, and the generated response is displayed.

Error Handling

The function includes a try-except block to catch and print any errors during the API call to Bedrock.

Future Enhancements

• Error Logging: Implement better error logging and handling.
• Model Selection: Allow users to choose from different models available in Bedrock.
• Styling Improvements: Enhance the UI/UX of the Streamlit app.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

• Streamlit
• Amazon Bedrock
• Anthropic Claude