The project aims to develop an AI-powered customer support system for educational purpose that can provide personalized and efficient support to customers. It uses the Cloudflare REST API key to generate the response.

❖ Basic Chatbot: Hard-coded responses for straightforward interactions.

❖ Intelligent Responses: Leveraging Gen-AI models for dynamic user engagement.

❖ Deployment: Hosted on AWS EC2 for reliable and scalable access.

❖ Multi-language Support: Catering to a diverse global customer base.

❖ User Authentication: Personalized chat experiences.

• Objective: Develop a simple chatbot with hard-coded responses.
• Tasks:
  • Set up a Next.js project.
  • Create a basic chatbot UI using Tailwind CSS.
  • Implement hard-coded responses.

• Objective: Enhance the chatbot to handle user queries using a Gen-AI model.
• Tasks:
  • Integrate the Cloudflare API with the chatbot.
  • Implement natural language processing for dynamic responses.
  • Test and refine response accuracy.

• Objective: Deploy the web app on AWS EC2 servers.
• Tasks:
  • Set up an AWS EC2 instance with rerver proxy using NGINX

• Multi-language Support:
  • Implement language detection and translation features.
  • Test and validate multilingual responses.
• User Authentication:
  • Add user authentication for personalized experiences.
  • Ensure secure and user-specific interactions.
• Feedback Mechanism:
  • Implement a feedback system for users to rate responses.
  • Analyze feedback for continuous improvement.

• Step 1: Download the docker desktop and proceed further.

• Step 2: Pull the Docker image using the following command:

docker pull surajkumar00/ai-customer-support

• Step 3: Run the Docker container using the following command:

docker run -it -p 3000:3000 surajkumar00/ai-customer-support

• Step 4: Access the application using the following URL: http://localhost:300

1. Clone the repository using

git clone https://github.com/username/ai-customer-support.git

2. Install dependencies using

npm install
npx shadcn-ui@latest init
npm i lucide-react

3. Set the Cloudflare REST API Key

• First create .env.local file in the root directory. Then add the below code in it.

CLOUDFLARE_API_KEY=your_api_key

4. Start the development server using

npm run dev

5. Access the chatbot at http://localhost:3000

❖ Deployed Application: Check our Chatbot

❖ Video Explanation: Link of the Demo Video

• Special thanks to the open-source community for their valuable resources and tools.
• Thanks to our contributors for their dedication and hard work