**Let's collaborate on a comprehensive, step-by-step prompt guide to an AI coding tool that will developpes and codes the software project**

**Project Goal:**

To create a Personal Home Service Management application for Windows 11 leveraging free and open-source tools, libraries, and APIs. This application is for personal use only.

**Software Specifications:**

The application will consist of:

1. **AI Chat Interface:** A conversational interface for user interaction, enabling natural language requests for code generation, explanations, and task execution.
    
2. **Multi-Tab Interface:**
    
    - **Code Generation Tab:** Displays AI-generated code snippets in real-time, with syntax highlighting and user editing capabilities.
        
    - **File Explorer Tab:** Offers a standard file system view of the project, allowing user navigation and management of files and folders created by the AI.
        
    - **Software Preview Tab:** Presents a live, interactive preview of the application being developed, showcasing UI elements and functionalities.
        

**Key Functionalities:**

- **AI-powered Code Generation:** The AI should generate code based on user prompts, utilizing its knowledge of programming languages, libraries, and best practices.
    
- **File and Folder Management:** The AI should be able to create, delete, and modify files and folders on the user's machine within a specified project directory.
    
- **GitHub Integration:** The AI should be able to interact with GitHub repositories, enabling features like:
    
    - Fetching relevant open-source code snippets based on user requests.
        
    - Cloning existing repositories.
        
    - Committing and pushing code changes.
        
- **Open-Source Integration:** Integrate with relevant open-source services, APIs, libraries, and resources, such as:
    
    - Hugging Face for natural language processing models and datasets.
        
    - Popular UI component libraries like Material-UI, Ant Design, or Bootstrap.
        
    - Database integration (e.g., SQLite) for data persistence.
        

**Prompt Guide Requirements:**

- **Step-by-step Instructions:** Provide clear, actionable prompts to guide the AI through each development stage.
    
- **Code Examples:** Include example prompts and expected AI responses, showcasing how to request specific code snippets or functionalities.
    
- **Best Practices:** Emphasize best practices for interacting with the AI coding tool, including:
    
    - Writing clear, concise prompts.
        
    - Specifying context, dependencies, and desired coding styles.
        
    - Reviewing and refining AI-generated code for accuracy, security, and efficiency.
        
- **Testing and Debugging:** Outline prompts to guide the AI in generating unit tests and identifying potential bugs.
    
- **Deployment Considerations:** Include prompts for packaging and deploying the application, specifically for the Windows 11 environment.
    

**Focus Areas:**

- **Efficient Prompting Techniques:** Showcase how to craft effective prompts to leverage the AI's capabilities to the fullest.
    
- **Security Considerations:** Highlight best practices for secure code generation and integration with open-source resources.
    
- **User Experience (UX) Design:** Provide prompts that guide the AI in creating user-friendly interfaces and intuitive interactions.

Here's some exemple of tools/services you can use to build the prompts.

## Tool and Service Examples

**Main Resources:**

- GitHub: https://github.com
- Hugging Face: https://huggingface.co

**Useful GitHub Repositories:**

- duckduckgo-ai-chat: https://github.com/mumu-lhl/duckduckgo-ai-chat
- TensorFlow: https://github.com/tensorflow/tensorflow
- PyTorch: https://github.com/pytorch/pytorch
- Hugging Face Transformers: https://github.com/huggingface/transformers
- OpenCV: https://github.com/opencv/opencv
- Open Source AI Repository Collection: https://github.com/thebigbone/opensourceAI
- Awesome Machine Learning: https://github.com/josephmisiti/awesome-machine-learning
- LangChain: https://python.langchain.com/en/latest/index.html
- Electron: https://www.electronjs.org/
- Tauri: https://tauri.app/
- Node.js: https://nodejs.org/
- Node.js fs: https://nodejs.org/api/fs.html
- simple-git: https://github.com/steveukx/git-js
- Python: https://www.python.org/
- Python os: https://docs.python.org/3/library/os.html
- PyGithub: https://github.com/PyGithub/PyGithub
- Hugging Face Hub: https://huggingface.co/docs/hub/
- AI Assistant: https://github.com/Anuken/MegaLinter
- ONNX Runtime: https://github.com/microsoft/onnxruntime
- Ray: https://github.com/ray-project/ray
- Horovod: https://github.com/horovod/horovod
- MLflow: https://mlflow.org/
- Kubeflow: https://www.kubeflow.org/
- Scikit-learn: https://scikit-learn.org/stable/
- Pandas: https://pandas.pydata.org/
- NumPy: https://numpy.org/
- XGBoost: https://xgboost.ai/
- LightGBM: https://lightgbm.readthedocs.io/en/latest/
- DVC (Data Version Control): https://dvc.org/
- spaCy: https://spacy.io/
- NLTK: https://www.nltk.org/
- Gensim: https://radimrehurek.com/gensim/
- Flair: https://github.com/flairNLP/flair
- Detectron2: https://github.com/facebookresearch/detectron2
- MMDetection: https://github.com/open-mmlab/mmdetection
- Papers with Code: https://paperswithcode.com/
- Streamlit: https://streamlit.io/
- Gradio: https://gradio.app/


## AI Platform Accounts:

- Together.ai: https://together.ai
- Fireworks.ai: https://fireworks.ai
- Cohere.com: https://cohere.com
- GLHF.chat: https://glhf.chat/
- Deepinfra.com: https://deepinfra.com
- Openrouter.ai: https://openrouter.ai
- Groq.com: https://groq.com
- AI Studio (Google): https://aistudio.google.com
- Opper.ai: https://opper.ai


## More Useful Tools:

- Firecrawl: https://www.firecrawl.dev
- Readwise: https://readwise.io
- Serper: https://serper.dev
- ElevenLabs: https://elevenlabs.io
- Langfuse: https://langfuse.com
- Botpress: https://botpress.com/
- Tyk: https://tyk.io/
- Keras: https://keras.io/
- Scikit-learn: https://scikit-learn.org/
- MLflow: https://mlflow.org/
- Rasa: https://rasa.com/
- DeepPavlov: https://deeppavlov.ai/
- FairSeq: https://github.com/pytorch/fairseq
- Kubeflow: https://www.kubeflow.org/
- MLRun: https://github.com/mlrun/mlrun
- OpenVINO Toolkit: https://openvino.ai/
- NVIDIA CUDA and cuDNN: https://developer.nvidia.com/cuda-zone
- Electron: https://www.electronjs.org/
- Monaco Editor: https://microsoft.github.io/monaco-editor/
- React: https://reactjs.org/
- Vue.js: https://vuejs.org/


- **APIs**: REST, SOAP, GraphQL, gRPC, WebSockets, OAuth, JWT, API documentation tools (Swagger, Postman).
- **Programming Languages**: Python, JavaScript (Node.js, React, Vue), Java, C#, Ruby, Go, PHP, TypeScript, Swift, Kotlin.
- **Frameworks and Libraries**: Django, Flask, Express.js, Spring Boot, .NET, Ruby on Rails, React, Angular, Vue.js, Laravel, ASP.NET.
- **Tools and Platforms**: GitHub/GitLab/Bitbucket, Docker, Kubernetes, CI/CD tools (Jenkins, Travis CI, CircleCI), AWS, Azure, Google Cloud Platform, Terraform.
- **Databases**: SQL (MySQL, PostgreSQL, SQLite), NoSQL (MongoDB, Redis, Cassandra), ORM tools (Entity Framework, Sequelize, SQLAlchemy).