However, after turning the workspace to Nx, run the build command against all apps and libraries: yarn nx run-many --target=build --all Notice it will take much less time the 2nd run. Full stack project for andika
- Node.js version 16.16
- Java JDK version 11 or higher. Requirement to use firebase emulator
- NX
- Yarn
- Firebase Tools
- Angular Cli
- NVM (optional to wasily install node.js)
- npm i -g yarn
- npm install -g firebase-tools
- yarn install
- npm i -g @angular/cli
- npm i -g nx
- firebase use andika-16cf6
- firebase setup:emulators:database
- firebase setup:emulators:ui
Before you run the dev server, you must create a keys.json file in the root directory must have the following keys with values:
{
"PRODUCTION": false,
"NEXIA_API_BASE_URL": "https://example.com/api/v1",
"FIREBASE_API_KEY": "**************",
"FIREBASE_AUTH_DOMAIN": "example.com",
"FIREBASE_PROJECT_ID": "example-098488",
"FIREBASE_MEASUREMENT_ID": "G-example433",
"FIREBASE_MESSAGING_SENDER_ID": "000000000000",
"FIREBASE_APP_ID": "1:exampleddygyy:web:example763525522",
"GOOGLE_CLIENT_ID": "example747666.apps.example.com",
"GOOGLE_CLIENT_DOMAIN": "https://example.com",
"GOOGLE_CLIENT_REDIRECT_URL": "https://example/dashboard"
}1; Veryfy config environment was created:
npm run verify-env 2; Setup config for environment and create a environment.ts file:
npm run env-config 3; Setup config for environment and create a environment.ts file:
npm run env-config 4; Run nx s for a dev server. Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.
To run the emulator run:
Windows
Run yarn emu:start
CTRL+ C - stop emulators
Linux
Run yarn emulator:start
Run nx graph to see a diagram of the dependencies of the projects.
Run npx nx connect-to-nx-cloud to enable remote caching and make CI faster.
Visit the Nx Documentation to learn more.
- intercomm feature
- business idea pitch
- business ideas
- call to action
- copy writing framework aida
- copy writing framework pas
- coverletter [x]
- facebook,twitter,linkedin ads
- googlesearch ads
- email [x]
- interview questions
- job description [x]
- keyword generator
- landing page website copies
- post caption ideas
- product description bullets
- profile bio [x]
- question answer
- reply to review and messages
- sms notifications
- song lyrics
- story plot
- custom use case
Personalization: One way to implement personalization could be to use machine learning algorithms to analyze the user's writing style and preferences. For example, the AI assistant could learn the user's preferred writing tone (formal or casual), sentence structure, and choice of words. Once the AI assistant has learned the user's writing style, it could provide more personalized suggestions and corrections.
Emotion detection and language generation: This feature could be implemented using natural language processing (NLP) techniques to analyze the emotional tone of a piece of text. Once the tone has been determined, the AI assistant could suggest words and phrases that match the desired tone. For example, if the text is determined to be sad, the AI assistant could suggest words and phrases that are more upbeat to improve the overall tone.
Multi-language support: This feature could be implemented using machine translation algorithms to translate text from one language to another in real-time. For example, the AI assistant could translate a piece of text from English to Spanish or vice versa.
Sentiment analysis: This feature could be implemented using NLP techniques to analyze the overall sentiment of a piece of text. The AI assistant could then provide feedback on how to improve the sentiment of the text, such as suggesting words or phrases that are more positive.
Integration with other tools: This feature could be implemented by integrating the AI assistant with other productivity tools such as calendars, task managers, and project management software. This would allow the AI assistant to provide context-aware suggestions and corrections.
Content generation: This feature could be implemented using GPT based models to generate original content based on specific topics or prompts.
Collaborative Writing: This feature could be implemented by allowing multiple users to work on a document together in real-time, with the AI assistant providing suggestions and corrections for each user.
Audio-based dictation and transcription: This feature could be implemented using automatic speech recognition (ASR) and natural language understanding (NLU) technologies to transcribe spoken words into written text and vice versa.
Summarization: This feature could be implemented by using NLP algorithms to extract key points from a piece of text and condense them into a shorter summary.
Real-time feedback and error correction: This feature could be implemented by using NLP algorithms to identify grammar, spelling, and style errors as the user writes and providing feedback in real-time.
It's possible that an AI writing assistant could be a viable business in the Kenyan market, but it would depend on a number of factors such as the target market, the quality of the application, and the pricing model.
Kenya is a developing country with a growing economy and a relatively high penetration of technology, especially mobile phones and internet. There is a large pool of talented people in Kenya, who can benefit from AI-based tools like writing assistant. Additionally, Kenya has a large pool of young people who are proficient in English and are in need of tools that can improve their writing skills.
However, there are a few things to consider:
The Kenyan market for AI writing assistant might be relatively small compared to other countries, so it's important to target the right market segments and price the product accordingly. It's also important to consider the competition in the Kenyan market and differentiate your product from others on the market. There may be cultural and linguistic barriers to adoption of an AI writing assistant in Kenya, so it's important to consider local market factors when developing the product. It would be a good idea to conduct market research and speak with industry experts to get a better understanding of the viability of an AI writing assistant in the Kenyan market, and to validate your business model.
TODO: provide attributions for the assets in use to: Cover letter icons created by Flat Icons - Flaticon Mail icons created by Freepik - Flaticon Grammar icons created by Freepik - Flaticon Interview icons created by Freepik - Flaticon Job description icons created by surang - Flaticon Search icons created by Smashicons - Flaticon Meeting icons created by Freepik - Flaticon Dictionary icons created by Freepik - Flaticon Idea icons created by Freepik - Flaticon Blog icons created by Freepik - Flaticon Briefing icons created by Freepik - Flaticon Call to action icons created by Flat Icons - Flaticon Portal icons created by Freepik - Flaticon Search icons created by Freepik - Flaticon Marketing icons created by Freepik - Flaticon
Send mail icons created by Md Tanvirul Haque - Flaticon
Email icons created by Pixel perfect - Flaticon
Speak icons created by Mayor Icons - Flaticon Personalization icons created by Freepik - Flaticon Seo and web icons created by paonkz - Flaticon Typing icons created by Freepik - Flaticon Data analysis icons created by orvipixel - Flaticon Landing page icons created by Freepik - Flaticon Description icons created by phatplus - Flaticon Content copy icons created by juicy_fish - Flaticon Letter icons created by srip - Flaticon Newsletter icons created by Freepik - Flaticon Copywriting icons created by Freepik - Flaticon Caption icons created by Eucalyp - Flaticon Marketing icons created by Freepik - Flaticon
Based on my research, the following professionals in Kenya could potentially benefit from an AI writing tool:
Content creators: Including bloggers, journalists, and copywriters who need to produce high-quality content quickly and efficiently.
Marketing professionals: Including social media managers, email marketers, and content marketers who need to create engaging marketing materials on a regular basis.
Software developers: Including web developers, mobile developers, and software engineers who need to generate code documentation, bug reports, and release notes.
Business owners: Including entrepreneurs and small business owners who need to create professional business documents such as reports, proposals, and contracts.
Legal professionals: Including lawyers, paralegals, and legal secretaries who need to generate legal documents and contracts.
Educators: Including teachers, lecturers, and trainers who need to create educational materials and assessments.
Here's a general list of categories that can be added in the navigation bar for an AI writing tool:
Home: A landing page that provides an overview of the tool and its features.
Use Cases: A section detailing various use cases for the tool, such as business proposals, financial reports, and bug reports.
Features: A section highlighting the key features of the tool, such as custom templates, real-time updates, and collaborative editing.
Pricing: A section detailing the pricing plans available for the tool, including free and paid options.
Integration: A section outlining the integration options for the tool, such as integration with other software or services.
Support: A section with resources for getting help with the tool, including a knowledge base, forums, and contact information.
About: A section with information about the company or organization behind the tool, including mission, values, and team.
Note: This list is a general guide and the specific categories added to the navigation bar will depend on the needs and requirements of the tool.
add test
For conventional commits
This example of SemVer tells you that this is the fourth major release. It has 7 minor versions with new features. It is also the sixth patch in this minor version (six versions of bug fixes). Keep in mind, that SemVer starts at 0.1.0. Not at 0.0.1, as you might assume. The reason is that there were no bug fixes yet as would the number 0.0.1 suggest. We have to start with a set of features.
The Three Phases of SemVer:
Initial Development Major version zero (0.y.z.) is for initial product development. The public API is not stable and anything may change during this phase. Keeping major version at zero lets everyone know that the software is not production-ready yet. Pre-release A lot of tests and code changes are done during this product version. A pre-release version is for testing that everything is ok and ready to release. This version is still not production-ready. Add a hyphen and identifier at the end of the version number. For example, a pre-release for version 1.0.0 could be 1.0.0-alpha.1. When you need another build, it becomes 1.0.0-alpha.2, and so on. Production When the public API is stable and the product is ready, you can release the major software version (1.y.z). Version numbers in this phase are equal to releases. Why You Might Want the Semantic Versioning Versioning the software ensures you that every team member or user can keep track of what has been changed and when. SemVer helps to explain what type of changes were made. It also informs users about possible software updates. SemVer lets you know which version of a product is no longer backwards compatible. Problems the Semantic Versioning Solves Demotivated team Meaningless work Unsuccessful product Unnecessary functions Increased cost Bad product-market fit Unhappy client Toxic team culture How to Implement the Semantic Versioning To use SemVer efficiently, follow these steps:
Look through the commits since the last release and decide if this will be a major, a minor or a patch release. Add a new appropriate version number. Tag your releases. You can use, for example, GitHub. Track all of the changes in a Changelog (a file with a list of changes) so the users know what is the difference between the product versions. Common Pitfalls of the Semantic Versioning Weak version management neglects users. Users judge product value based on the version number. The stakeholder asks for a specific version number based on marketing choices or client’s preferences. Too many major versions are being released in a short time period. It discourages the users from adopting new versions. If you are required to make breaking changes, you need to thoroughly think through the impact of those changes. Plan the changes ahead with deprecation notices.
https://nx.dev/recipes/ci/monorepo-ci-github-actions
https://svdoscience.com/2020-10-31/versioning-with-semantic-release
nx g @nrwl/workspace:library pages --import-path=@andika/pages --dry-run Analogous Palette:
bg-yellow-500 (#F59E0B) bg-yellow-400 (#FBBF24) bg-yellow-300 (#FCD34D) Complementary Palette:
bg-yellow-500 (#F59E0B) bg-purple-500 (#9333EA) bg-purple-400 (#A855F7) Monochromatic Palette:
bg-yellow-500 (#F59E0B) bg-yellow-400 (#FBBF24) bg-yellow-300 (#FCD34D) Triadic Palette:
bg-yellow-500 (#F59E0B) bg-blue-500 (#3B82F6) bg-red-500 (#EF4444) Tetradic Palette:
bg-yellow-500 (#F59E0B) bg-blue-500 (#3B82F6) bg-purple-500 (#9333EA) bg-red-500 (#EF4444)
To use the suggested color palette in your AI writing tool theme, you can apply the colors to various components and typography elements. Here are some suggestions:
Background Color:
Set the background color of the main content area or editor to bg-yellow-500 (#F59E0B) to maintain consistency with the primary color. Text Color:
Use a contrasting text color for readability. For example, you can use text-gray-900 (#111827) for dark text on the yellow background. Button Styling:
Apply the bg-yellow-500 (#F59E0B) as the background color for buttons to create a cohesive look. Use a contrasting text color, such as text-white (#FFFFFF), for button labels. Accent Color:
Choose one of the complementary or analogous colors from the palette to use as an accent color for interactive elements, such as links or highlighted text. For example, you can use bg-purple-500 (#9333EA) as an accent color for links. Typography:
Adjust the text colors for headings and body text to ensure readability on the yellow background. Consider using text-gray-900 (#111827) for headings and text-gray-700 (#4B5563) for regular body text. Error/Success Messages:
Utilize a different color, such as bg-red-500 (#EF4444) for error messages or bg-green-500 (#10B981) for success messages, to convey feedback or alerts to the user. Remember to maintain a consistent visual hierarchy and ensure that the color choices enhance the user experience by providing clear differentiation between different elements. These suggestions provide a starting point, and you can further customize the color palette based on your specific design preferences and requirements.
TODO: Documents component exists in elements and pages move from documents to the element.