Build a Mindblowing Chat GPT WebApp with a Web Scraper Superagent and Custom Knowledge - AWS Bedrock
AI Summary
# AI Super Agent App Tutorial Summary ## Introduction - Tutorial on creating an AI super agent web application. - Utilizes [[Obsidian|Next.js]], React, Node.js, and AWS services. - Focuses on technical aspects rather than hype. - Aims to provide hands-on guidance for integrating generative AI into web applications. ## Key Concepts 1. **API and Programming Skills**: Requires knowledge of REST APIs, frontend and backend programming. 2. **AWS Services**: Uses services like Amazon Bedrock, Lambda, and API Gateway. 3. **Foundation Models**: Integrates models like GPT-4, Amazon Titan, and Cloe. 4. **Custom AI Agent**: Customizable AI agent that can be integrated into systems for various tasks. ## Tutorial Sections 1. **Direct Foundation Model Query**: Simple API calls to a chosen AI model. 2. **Knowledge Base Integration**: Utilizes retrieval-augmented generation (RAG) technique for AI models to access up-to-date, proprietary information. 3. **AI Agent with Web Research**: Develops an agent capable of conducting specific online research and providing updated information. ## Development Steps 1. **Setup AWS Bedrock**: Configure AWS Bedrock for generative AI services. 2. **Create Next.js App**: Initialize a new Next.js project for the web application. 3. **Implement WebSocket Server**: Set up a WebSocket server for real-time communication between the client and server. 4. **Develop Frontend**: Build the user interface using React components and Next.js pages. 5. **Integrate AI Models**: Connect to AI models and handle API calls for querying and generating responses. 6. **Knowledge Base Training**: Implement functionality for uploading documents and training the AI model using the RAG technique. 7. **AI Agent Functionality**: Code the AI agent to perform web research and integrate it with the system. 8. **AWS Lambda Functions**: Write Lambda functions for handling backend tasks like web scraping and data analysis. 9. **Testing and Debugging**: Test the application to ensure all components work together seamlessly. ## Conclusion - The tutorial provides a comprehensive guide to creating an AI super agent. - Emphasizes the importance of technical knowledge and hands-on experience. - Demonstrates the use of various AWS services and AI models to build a functional web application.
For the full code and resources, please refer to the GitHub repository linked in the video description.