Create a README_CODER.md that will guide the coder agents in their journey

[kvnn]

README_CODER.md should start with the following:

AI Agents Starter Kit
Demo Project 01

This Demo Project is a Fast API project. The following command should begin a server that can be opened on a browser : `uvicorn main:app --reload`.

The purpose of this app is to:
1. fetch Project Gutenberg book contents via a `txt_url` parameter whose value will be provided from the FastAPI client interface
2. download the file to `{project_path}/books`
3. find a random paragraph in the file
4. perform text-to-speech on the chosen text section
5. save the audio file to `{project_path}/audio` folder

[kvnn]

[architect] c# Technical Design Document for AI Agents Starter Kit

Overview

The AI Agents Starter Kit is a FastAPI project aimed at fetching Project Gutenberg book contents, downloading the file, finding a random paragraph, performing text-to-speech on the chosen text section, and saving the audio file. This document outlines the technologies, libraries, packages, and vendors to be used in the implementation of this project.

Technologies and Tools

1. Backend Framework: FastAPI will be used for the backend to provide a fast and efficient API.
2. Frontend Framework: React Native with Mui will be used for the frontend to create a responsive and user-friendly interface.
3. Database: Postgres will be used as the database to store book contents and audio files.
4. Hosting: The application will be hosted on a single AWS instance for scalability and reliability.
5. Version Control: Git will be used for version control to track changes and collaborate effectively.
6. Documentation: Markdown will be used for documentation to ensure clear and consistent information.
7. Video Processing: Ffmpeg will be used for text-to-speech functionality to convert text to audio files.
8. Scripting: Bash scripting will be used for automation and system compatibility on both OSX and Ubuntu.

Architecture

The architecture of the AI Agents Starter Kit will follow a simple and efficient design:

• Frontend: The React Native frontend will interact with the FastAPI backend to send requests and display results to the user.
• Backend: The FastAPI backend will handle requests from the frontend, fetch book contents from Project Gutenberg, process text-to-speech, and save audio files to the database.
• Database: Postgres will store book contents and audio files for easy retrieval and management.
• Hosting: The application will be deployed on a single AWS instance to ensure scalability and performance.

Implementation Plan

1. Setup Environment: Configure development environments for backend and frontend development.
2. Backend Development:
   • Implement FastAPI endpoints for fetching book contents and processing text-to-speech.
   • Integrate Ffmpeg for text-to-speech functionality.
   • Set up database connections and schema for storing book contents and audio files.
3. Frontend Development:
   • Develop React Native components for user interface and interaction with the backend.
   • Implement Mui for styling and responsive design.
4. Integration:
   • Connect the frontend and backend to enable seamless communication.
   • Test end-to-end functionality for fetching, processing, and saving audio files.
5. Deployment:
   • Deploy the application on a single AWS instance for public access.
   • Configure server settings and environment variables for production.
6. Testing and Optimization:
   • Conduct thorough testing to ensure functionality and performance.
   • Optimize code and database queries for efficiency.
7. Documentation:
   • Create detailed documentation using Markdown for setup, usage, and maintenance instructions.

Timeline

• Week 1-2: Environment setup and backend development
• Week 3-4: Frontend development and integration
• Week 5: Deployment and testing
• Week 6: Optimization and documentation

Risks and Mitigation

• Technical Challenges: Regular code reviews and pair programming to address complex issues.
• Resource Constraints: Prioritize tasks and allocate resources effectively.
• Integration Issues: Conduct thorough testing and implement error handling mechanisms.

By following this technical design document, the development team can successfully implement the AI Agents Starter Kit with the specified technologies and tools, ensuring a high-quality and efficient solution.

[kvnn]

refactor :

Error Handling and Logging: The document could include a section on implementing robust error handling mechanisms and logging practices to facilitate debugging and troubleshooting in case of issues or errors during development and production.

[kvnn]

[architect] c# Technical Design Document for AI Agents Starter Kit

Overview

The AI Agents Starter Kit is a FastAPI project aimed at fetching Project Gutenberg book contents, downloading the file, finding a random paragraph, performing text-to-speech on the chosen text section, and saving the audio file. This document outlines the technologies, libraries, packages, and vendors to be used in the implementation of this project.

Technologies and Tools

1. Backend Framework: FastAPI will be used for the backend to provide a fast and efficient API.
2. Frontend Framework: React Native with Mui will be used for the frontend to create a responsive and user-friendly interface.
3. Database: Postgres will be used as the database to store book contents and audio files.
4. Hosting: The application will be hosted on a single AWS instance for scalability and reliability.
5. Version Control: Git will be used for version control to track changes and collaborate effectively.
6. Documentation: Markdown will be used for documentation to ensure clear and consistent information.
7. Video Processing: Ffmpeg will be used for text-to-speech functionality to convert text to audio files.
8. Scripting: Bash scripting will be used for automation and system compatibility on both OSX and Ubuntu.

Architecture

The architecture of the AI Agents Starter Kit will follow a simple and efficient design:

• Frontend: The React Native frontend will interact with the FastAPI backend to send requests and display results to the user.
• Backend: The FastAPI backend will handle requests from the frontend, fetch book contents from Project Gutenberg, process text-to-speech, and save audio files to the database.
• Database: Postgres will store book contents and audio files for easy retrieval and management.
• Hosting: The application will be deployed on a single AWS instance to ensure scalability and performance.

Implementation Plan

1. Setup Environment: Configure development environments for backend and frontend development.
2. Backend Development:
   • Implement FastAPI endpoints for fetching book contents and processing text-to-speech.
   • Integrate Ffmpeg for text-to-speech functionality.
   • Set up database connections and schema for storing book contents and audio files.
3. Frontend Development:
   • Develop React Native components for user interface and interaction with the backend.
   • Implement Mui for styling and responsive design.
4. Integration:
   • Connect the frontend and backend to enable seamless communication.
   • Test end-to-end functionality for fetching, processing, and saving audio files.
5. Deployment:
   • Deploy the application on a single AWS instance for public access.
   • Configure server settings and environment variables for production.
6. Testing and Optimization:
   • Conduct thorough testing to ensure functionality and performance.
   • Optimize code and database queries for efficiency.
7. Documentation:
   • Create detailed documentation using Markdown for setup, usage, and maintenance instructions.

Error Handling and Logging

To facilitate debugging and troubleshooting in case of issues or errors during development and production, robust error handling mechanisms and logging practices will be implemented. This includes:

• Implementing try-except blocks in the backend code to catch and handle exceptions.
• Logging relevant information such as errors, warnings, and debug messages to a designated log file.
• Using logging levels to differentiate between different types of messages for better analysis.

Timeline

• Week 1-2: Environment setup and backend development
• Week 3-4: Frontend development and integration
• Week 5: Deployment and testing
• Week 6: Optimization and documentation

Risks and Mitigation

• Technical Challenges: Regular code reviews and pair programming to address complex issues.
• Resource Constraints: Prioritize tasks and allocate resources effectively.
• Integration Issues: Conduct thorough testing and implement error handling mechanisms.

By following this technical design document, the development team can successfully implement the AI Agents Starter Kit with the specified technologies and tools, ensuring a high-quality and efficient solution.

[kvnn]

refactor remove Risks and Mitigation

[kvnn]

[architect] c```markdown c# Technical Design Document for AI Agents Starter Kit

Overview

The AI Agents Starter Kit is a FastAPI project aimed at fetching Project Gutenberg book contents, downloading the file, finding a random paragraph, performing text-to-speech on the chosen text section, and saving the audio file. This document outlines the technologies, libraries, packages, and vendors to be used in the implementation of this project.

Technologies and Tools

1. Backend Framework: FastAPI will be used for the backend to provide a fast and efficient API.
2. Frontend Framework: React Native with Mui will be used for the frontend to create a responsive and user-friendly interface.
3. Database: Postgres will be used as the database to store book contents and audio files.
4. Hosting: The application will be hosted on a single AWS instance for scalability and reliability.
5. Version Control: Git will be used for version control to track changes and collaborate effectively.
6. Documentation: Markdown will be used for documentation to ensure clear and consistent information.
7. Video Processing: Ffmpeg will be used for text-to-speech functionality to convert text to audio files.
8. Scripting: Bash scripting will be used for automation and system compatibility on both OSX and Ubuntu.

Architecture

The architecture of the AI Agents Starter Kit will follow a simple and efficient design:

• Frontend: The React Native frontend will interact with the FastAPI backend to send requests and display results to the user.
• Backend: The FastAPI backend will handle requests from the frontend, fetch book contents from Project Gutenberg, process text-to-speech, and save audio files to the database.
• Database: Postgres will store book contents and audio files for easy retrieval and management.
• Hosting: The application will be deployed on a single AWS instance to ensure scalability and performance.

Implementation Plan

1. Setup Environment: Configure development environments for backend and frontend development.
2. Backend Development:
   • Implement FastAPI endpoints for fetching book contents and processing text-to-speech.
   • Integrate Ffmpeg for text-to-speech functionality.
   • Set up database connections and schema for storing book contents and audio files.
3. Frontend Development:
   • Develop React Native components for user interface and interaction with the backend.
   • Implement Mui for styling and responsive design.
4. Integration:
   • Connect the frontend and backend to enable seamless communication.
   • Test end-to-end functionality for fetching, processing, and saving audio files.
5. Deployment:
   • Deploy the application on a single AWS instance for public access.
   • Configure server settings and environment variables for production.
6. Testing and Optimization:
   • Conduct thorough testing to ensure functionality and performance.
   • Optimize code and database queries for efficiency.
7. Documentation:
   • Create detailed documentation using Markdown for setup, usage, and maintenance instructions.

Error Handling and Logging

To facilitate debugging and troubleshooting in case of issues or errors during development and production, robust error handling mechanisms and logging practices will be implemented. This includes:

• Implementing try-except blocks in the backend code to catch and handle exceptions.
• Logging relevant information such as errors, warnings, and debug messages to a designated log file.
• Using logging levels to differentiate between different types of messages for better analysis.

By following this technical design document, the development team can successfully implement the AI Agents Starter Kit with the specified technologies and tools, ensuring a high-quality and efficient solution.

[kvnn]

Refactor : The coding agent needs to understand what we are asking it to do. We want the coding agent to create a Readme with the contents of your previous comment. Include instructions for the coding agent in your response.

[kvnn]

[architect]

# Technical Design Document for AI Agents Starter Kit

## Overview
The AI Agents Starter Kit is a FastAPI project designed to fetch Project Gutenberg book contents, process text-to-speech, and save audio files. This document outlines the technologies, libraries, packages, and vendors to be used in the implementation of this project.

## Technologies and Tools
1. **Backend Framework**: FastAPI
2. **Frontend Framework**: React Native with Mui
3. **Database**: Postgres
4. **Hosting**: AWS
5. **Version Control**: Git
6. **Documentation**: Markdown
7. **Video Processing**: Ffmpeg
8. **Scripting**: Bash

## Architecture
- **Frontend**: React Native frontend interacts with FastAPI backend.
- **Backend**: FastAPI handles requests, fetches book contents, and processes text-to-speech.
- **Database**: Postgres stores book contents and audio files.
- **Hosting**: AWS instance for scalability.
- **Error Handling**: Implement try-except blocks and logging for debugging.

## Implementation Plan
1. **Environment Setup**: Configure backend and frontend development environments.
2. **Backend Development**:
   - Implement FastAPI endpoints for fetching book contents and text-to-speech.
   - Integrate Ffmpeg for audio processing.
   - Set up database schema for storage.
3. **Frontend Development**:
   - Develop React Native components for user interface.
   - Use Mui for styling.
4. **Integration**:
   - Connect frontend and backend for communication.
   - Test end-to-end functionality.
5. **Deployment**:
   - Deploy on AWS instance.
   - Configure server settings.
6. **Testing and Optimization**:
   - Conduct thorough testing.
   - Optimize code and queries.
7. **Documentation**:
   - Create detailed Markdown documentation.

By following this technical design document, the team can successfully implement the AI Agents Starter Kit with the specified technologies and tools.

Instructions for Coding Agent:

1. Create a README file with the content provided in the technical design document.
2. Include instructions for error handling and logging in the README.
3. Ensure the document is clear, concise, and easy to follow for the development team.