pawait-llm-qa-app

A modern, production-ready full-stack Q&A web application powered by FastAPI (backend) and Next.js + TailwindCSS + TypeScript (frontend), integrating an LLM (Language Learning Model) for AI-generated responses.

GitHub Repository: https://github.com/Cypherfelix/pawait-llm-qa-app

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Table of Contents

• Project Overview
• Architecture
• Backend Documentation
  • Features
  • Tasks
  • Requirements
  • Testing
  • Implementation
• Frontend Documentation
  • Features
  • Tasks
  • Requirements
  • Testing
  • Implementation
• Deployment Strategy
• Contributing
• License

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Project Overview

pawait-llm-qa-app is a full-stack application that allows users to input questions and receive AI-generated answers using an LLM. The project demonstrates modern web development practices, clean code, and effective API integration. It is designed for scalability, maintainability, and ease of deployment.

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Architecture

graph TD
    A[User] -->|Types Question| B[Next.js Frontend]
    B -->|API Request| C[FastAPI Backend]
    C -->|LLM API Call| D[LLM Provider]
    D -->|Response| C
    C -->|API Response| B
    B -->|Displays Answer| A

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• Frontend: Next.js (TypeScript, TailwindCSS) for a modern, responsive UI.
• Backend: FastAPI (Python) for robust, high-performance API endpoints.
• LLM Integration: Easily switchable between providers (OpenAI, Gemini, etc.).
• Deployment: Ready for Vercel, Netlify, Render, Railway, or Docker.

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Backend Documentation

• Features
• Tasks
• Requirements
• Testing
• Implementation

Frontend Documentation

• Features
• Tasks
• Requirements
• Testing
• Implementation

Deployment Strategy

Overview

Our deployment strategy is designed for speed, reliability, and zero-cost hosting during development and demonstration phases. We leverage modern cloud platforms that integrate seamlessly with GitHub for CI/CD and environment management.

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Architecture Diagram

graph TD
    A(User) --> B(Vercel - Next.js Frontend)
    B --> C(Railway - FastAPI Backend)
    C --> D(LLM Provider - OpenAI)

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Frontend (Next.js)

• Platform: Vercel
• Why: Vercel is optimized for Next.js, offers instant global deployment, automatic HTTPS, and a generous free tier. It supports environment variables and integrates directly with GitHub for continuous deployment.
• Strategy: Every push to the main branch triggers an automatic build and deployment. Environment variables (such as the backend API URL) are managed securely in the Vercel dashboard.

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Backend (FastAPI)

• Platform: Railway
• Why: Railway provides a fast, free, and developer-friendly platform for Python web apps. It supports automatic deployments from GitHub, easy environment variable management, and public URLs for API access.
• Strategy: The backend is deployed as a web service. On each push to the main branch, Railway builds and redeploys the FastAPI app. Environment variables (such as LLM API keys) are managed securely in the Railway dashboard.

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Key Points

• CI/CD: Both frontend and backend are continuously deployed from GitHub.
• Environment Variables: Managed securely on each platform, never committed to code.
• Scalability: Both platforms allow for easy scaling or migration to paid plans if needed.
• Custom Domains: Supported on both Vercel and Railway for production readiness.

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Contributing

Contributions are welcome! Please open issues or submit pull requests via GitHub.

License

This project is licensed under the MIT License.