KenKen is an arithmetic and logic puzzle . It is a Constraint Satisfaction Problem(CSP), that the particular program solves using algorithms like BT, BT+MRV, FC, FC+MRV and MAC provided by aima-code.
The KenKen board is represented by a square n-by-n grid of cells. The grid may contain between 1 and n boxes (cages) represented by a heavily outlined perimeter. Each cage will contain in superscript: the target digit value for the cage followed by a mathematical operator.
Constraints
Each valid solution must follow the below rules:
The only numbers you may write are 1 to N for a NxN size puzzle.
A number cannot be repeated within the same row.
A number cannot be repeated within the same column.
In a one-cell cage, just write the target number in that cell.
Each “cage” (region bounded by a heavy border) contains a “target number” and an arithmetic operation. You must fill that cage with numbers that produce the target number, using only the specified arithmetic operation. Numbers may be repeated within a cage, if necessary, as long as they do not repeat within a single row or column.
For example, the text representing the above puzzle is:
6
[(0,0),(1,0)] add 11
[(0,1),(0,2)] div 2
[(0,3),(1,3)] mult 20
[(0,4),(0,5),(1,5),(2,5)] mult 6
[(1,1),(1,2)] sub 3
[(1,4),(2,4)] div 3
[(2,0),(2,1),(3,0),(3,1)] mult 240
[(2,2),(2,3)] mult 6
[(3,2),(4,2)] mult 6
[(3,3),(4,3),(4,4)] add 7
[(3,4),(3,5)] mult 30
[(4,0),(4,1)] mult 6
[(4,5),(5,5)] add 9
[(5,0),(5,1),(5,2)] add 8
[(5,3),(5,4)] div 2
Step 3: Name the key and value in your .env file as
MONGO_CONNECTION_STRING=
MONGO_URI=<Your MongoDB Connection String>
PORT=5000
JWT_SECRET=<Your JWT secret>
EMAIL_USERNAME=<Your Email>
EMAIL_PASSWORD=<Your App Password created from google account>
CLIENT_URL=http://localhost:<Frontend PORT>
STRIPE_SECRET_KEY=<Your Stripe Secret Key>
STRIPE_WEBHOOK_SECRET=<Your Stripe Webhook Secret Key>
Step 4: Add the .env in .gitignore file Step 5:
npm run dev
Step 6: Use the below API endpoints for Authentication and Base URL is http://localhost:<PORT>/api/v1/auth:
"/me" - Get authenticated user (GET)
"/:token" - If the token is in VerifyUser collections, move the user to `users` collections (GET)
"/register" - Signup user (POST). eg., {"name": "name", "email": "example@email.com", "password":"pass123"}
"/login" - Login user (POST). eg., {"email": "example@email.com", "password":"pass123"}
Step 7: Use the below API endpoints for User and Base URL is http://localhost:<PORT>/api/v1/user:
"/getUserHostedVehicleStatus" - Get specific user hosted vehicles status list (GET)
"/update" - Update user details (PUT)
"/forgotpassword" - User email is verified, and reset password link is sent to verified email. (POST)
"/passwordreset/:resetToken" - Check the reset token is expired and update the password. (PUT)
Step 8: Use the below API endpoints for Vehicle and Base URL is http://localhost:<PORT>/api/v1/vehicles:
"https://github.com/" - Get the filtered vehicles (GET).
"/getAllVehicles" - Search and Get all vehicles (GET) (Admin).
"/getUnapprovedVehicles" - Get the unapproved host vehicles and update the hostCarStatus (Admin)
"/:id" - Get specific vehicle details (GET).
"https://github.com/" - Create new vehicle (POST).
"/:id" - Update vehicle details (PUT) (Admin).
"/:id" - Delete vehicle (Delete) (Admin).
Step 9: Use the below API endpoints for Booking and Base URL is http://localhost:<PORT>/api/v1/bookings:
"https://github.com/" - Get the booked vehicles (GET).
"https://github.com/" - Book a vehicle (POST).
"https://github.com/" - Update the booking (PUT).
Step 10: Use the below API endpoints for Review and Base URL is http://localhost:<PORT>/api/v1/reviews:
"https://github.com/" - Get the reviews of specific user (GET).
"https://github.com/" - Post a reatings and comment for the booked vehicle (POST).
Step 10: Use the below API endpoints for Payment and Base URL is http://localhost:<PORT>/api/v1/payment:
"/create-checkout-session/:id" - Proceed with the vehicle rental by initiating the checkout session (POST).
Translations in languages other than English are machine translated and are not yet accurate. No errors have been fixed yet as of March 21st 2021. Please report translation errors here. Make sure to backup your correction with sources and guide me, as I don’t know languages other than English well (I plan on getting a translator eventually) please cite wiktionary and other sources in your report. Failing to do so will result in a rejection of the correction being published.
Note: due to limitations with GitHub’s interpretation of markdown (and pretty much every other web-based interpretation of markdown) clicking these links will redirect you to a separate file on a separate page that isn’t the intended page. You will be redirected to the .github folder of this project, where the README translations are hosted.
Translations are currently done with Bing translate and DeepL. Support for Google Translate translations is coming to a close due to privacy concerns.
Try it out! The sponsor button is right up next to the watch/unwatch button.
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Software status
All of my works are free some restrictions. DRM (Digital Restrictions Management) is not present in any of my works.
This sticker is supported by the Free Software Foundation. I never intend to include DRM in my works.
I am using the abbreviation “Digital Restrictions Management” instead of the more known “Digital Rights Management” as the common way of addressing it is false, there are no rights with DRM. The spelling “Digital Restrictions Management” is more accurate, and is supported by Richard M. Stallman (RMS) and the Free Software Foundation (FSF)
This section is used to raise awareness for the problems with DRM, and also to protest it. DRM is defective by design and is a major threat to all computer users and software freedom.
This application is a starter for the creation of bots for Facebook Messenger and WorkChat (Workplace) for demonstration and education purposes. Its configuration is robust and scalable and can be used in a productive environment. Use this application to learn, experiment, retouch and practice the different options offered by the Facebook API.
For more information about the Facebook API you can read the documentation that the Messenger team prepared.
Messaging bots use a web server to process the messages they receive or to find out which messages to send. It is also necessary for the bot to be authenticated to talk to the web server and for the bot to be approved by Facebook to talk to the public.
When a person sends a message to a company in Messenger, the following happens, as long as the page uses an app to partially or completely automate the conversations. The Facebook server sends webhooks to the URL of the company’s server where the message app is hosted. That app can then reply to the person in Messenger using the Send API. This allows developers to create guided conversations for people to perform an automated process or develop an app that serves as a link between your agents and your company’s Messenger presence.
🤖 Live Demo
You can try some functions of the bot by entering here.
And you can try other kind of messages from the server documentation, don’t forget to get your ID from the chat bot persistent menu.
🙌 Let’s start
Before starting to work on our bot, we must have installed some tools in our computer that will facilitate us to work locally and be able to test some functionalities that the starter has available, and I will take for granted some basic concepts so as not to go into detail and extend the documentation.
When we have the basic requirements, we clone the repository, go to the project folder and install its dependencies.
npm install
We download the latest version of Ngrok compatible with our operating system, and decompress it in the server root.
⚙ Configurations
This application uses the config dependency to facilitate the configuration of environment variables, which makes it scalable and robust when deploying the application in different environments.
In the path ./config you will find a file called development.json which contains the settings for a local environment, while the file custom-environment-variables.json gets the key values of the environment variables displayed on the server.
Basically the file works as an object that is exported and can be consumed by invoking it in the file that requires consuming the loaded information.
If you need to add another type of data to consume, like the connection to a database, the url of some microservice, etc. you just have to add it to both files keeping the scheme.
You may find that you can’t configure some values for now, but that’s not a problem, when using the nodemon dependency, the server is in a watching state that at the slightest change of code, the server will run again.
See all available configuration properties in detail.
Server
url: It is the url of the server deployed in some environment, in the case of running it locally, you enter the url with ssl provided by ngrok.
Type: String
Default:
port: Is the port in which the application is deployed.
Type: Number
Default: 8080
context: It is the context from which the server’s api can be accessed, this way the routes in the main path of the application are not exposed.
Type: String
Default: /api
origins: The origins serve so that the application can only be consumed by reliable urls and avoid any kind of unwanted and malicious requests. You should write the urls separated with comma.
showLogInterceptor: Enables the display of the request interceptors in the logs.
Type: Boolean
Default: false
Params
fbApiVersion: Is the api version of facebook
Type: String
Default: v8.0
verifyToken: It is the verification token required by the application when invoked by facebook, this token is private and should not be exposed.
Type: String
Default: my_awesome_bot_verify_token
appSecret: It is the secret key to the app, it is required if you are going to use the security settings for the requests.
Type: String
Default:
accessToken: The access token is the alphanumeric hash that is generated when you create the application on Fecebook or Workplace.
Type: String
Default:
subscribedFields: Are the permissions required to subscribe to the application in order to interact with the user. These permissions are only required for Facebook bots and must be typed separately by comma.
userFields: It is a comma-separated list to obtain the user’s information.Documentation
Type: String
Default: id,name,first_name,last_name,email
secrets: Here you can enter any value you want to hide in the server logs of the bot, for example the id of the sender or the id of the sender. The values to hide must be written separated by comma.
Type: String
Default:
requireProof: Enables or disables the use of appsecret_proof and appsecret_time for security requests, it is required to have configured the secret key of the app to work.
Type: Boolean
Default: false
services
fbApiUrl: It is the url of the Graph API of Feacebook
Type: String
Default: https://graph.facebook.com
swagger
enabled: Enable or disable the documentation of the bot’s server endpoints with swagger.
Type: Boolean
Default: true
💻 Run server
We start the bot’s server.
npm run start
Once the server is started, we must start ngrok to create the connection tunnel between the bot’s local server and the Facebook server.
./ngrok http 8080
Windows
./ngrok.exe http 8080
To see other tunnel configurations, you can check the documentation
📚 Swagger
The project has a Swagger that has documented the most important endpoints of the project, and facilitates the configuration of the fields for the bot, such as the get started button, persistent menu and the greeting.
This documentation can be enabled or disabled from the configuration files.
Default: http://localhost:8080/api-docs
URL Scheme
<http|https>://<server_url><:port>/api-docs
🖥️ Deploy server in heroku (free)
You can run the bot server in a productive environment on any node server, in this case I will explain the steps to raise the server on the platform Heroku, which has a free version to deploy node servers, you can also hire a paid service which gives you more features.
We will need a file called Procfile, which is the one Heroku will use to initialize the server once deployed.
Its content is:
web: npm start
After logging into Heroku, click on Create new app
We write the name of our app, and select a region, and then click on Create App.
💬 note: Remember to save the name of the app, as you will need it later to replace the value of <app_name> with the name of the app.
Heroku gives you several options to deploy your server. You can do it with Heroku CLI by following the steps in the documentation, or you can deploy it directly from Github, which is much easier.
For existing repositories, simply add the heroku remote
heroku git:remote -a <app_name>
Deployment method: GitHub
We click on the connect to GitHub button, if you’ve never connected Heroku to Github, a window will open to authorize the connection so you can continue with the step of entering the name of the repository and searching it in your GitHub account, and once you find it, we click on the Connect button.
Then we select the branch we want to deploy, and click on Deploy Branch, and it will start running the deployment, downloading the code from the repository, installing the dependencies, etc.
Now we have to configure the environment variables of the server, although we can do it manually from Settings > Config Vars, there is a bash script prepared that will raise the environment variables of our .env file that is located in the ./variables folder.
npm run heroku:envs
or
bash heroku-envs.sh
📱 Setup the Facebook App
The time has come to create and configure our app on Facebook.
With the local server and the connection tunnel initialized, we will configure the app, and with the information that it will give us we will finish configuring the data that we are missing in the bot’s server.
💬 Remember that the bot’s server is in watch mode, and any changes made will be re-initialized and take the changes made.
Enter Facebook Developers and click on create app, it will open a modal to select the type of application, in our case we will create an application type “Manage business integrations“.
Now we will have to make some basic settings for the application.
We assign a name of the app to identify it, we put a contact email, we select the purpose of the app, in this case is for us, and if we have a commercial administrator account, we select one from the list, if you do not have such an account, you can create it later.
Once the information is completed, we click on Create App identifier
Then we look for Messenger in the app’s product list, and hit the configure button.
Now we are going to make the two necessary and essential configurations to be able to connect Facebook with our bot server.
Access tokens
In this part of the configuration, we will be able to manage which page or pages of facebook will have the bot available.
We click on Add or Remove pages, and select the page.
Once the page is linked to the app, we have to generate the token by clicking on the button Generate Token, and a window will open where you give us some instructions about the token.
We must check accept in order to view the full hash, then copy it and place it in the configuration of our server, if it is for development it is put in the json of ./config/development.json in the key of accessToken, and if it is for a productive environment, we must put it in the envs file in ./variables.
Now we have to configure the connection between Facebook and our server through Webhook, for this, you must have at hand the verifyToken that you configured and the bot’s server url, in this case, we will use the one provided by ngrok with ssl.
https://<id_tunnel>.ngrok.io/api/webhook/
Then click on Verify and Save, and if everything goes well, in the server terminal you should see the successful subscription message.
If the url of the webhook by ngrok changes, or you want to configure the url of the productive server, you can do it by clicking on the button Edit Callback URL and perform again the previous steps.
Add subscriptions
Now we have to add the subscriptions that will allow the bot to have certain permissions to perform the actions we need.
For that we click on the button Add subscriptions
Select from the list the basic permissions and click on Save
Then we add each permission to the configuration files separated by a comma.
These are the last settings to be made and are optional.
It consists in executing a curl script in the terminal to implement some options, don’t forget to put the access token to make it work.
💬 Note: You can run these scripts from Swagger, but you must adjust the files that are inside the ./templates/configs folder
We have finished configuring the app so that Facebook connects to the bot’s server, now we have to test it, to do this we can enter the chat page and perform a test to verify that everything is working properly.
📡 How to share your bot
Add a chat button to your webpage, go here to learn how to add a chat button your page.
🔗 Create a shortlink
You can use page username to have someone start a chat.
https://m.me/<PAGE_USERNAME>
📱 Setup the Workplace App
The configuration of the app for Workplace is quite similar to that of Facebook, it is required to have the Workplace paid account in order to enable custom integrations.
Go to the Administrator Panel, and click on the Integrations button, and in the Custom integrations section click on the Create custom integration button.
It will open a modal where we must write the name of the application and a description, then click on Create.
Once the application is created, it takes us to the configuration page of the application.
Access token
Now we are going to generate an access token and then configure it in our config, as mentioned in the configuration of the Facebook app.
Now let’s select the permissions for our bot.
Permissions
In our case we are interested in the option of Sending a message to any member.
Now we are going to grant the integration access to groups, in this case it is going to be to a specific group.
And finally, we have to configure the Webhook and the verify token and select the subscriptions we need, as we did with the Facebook app.
💬 Note: depending on the webhook configuration you select in the tabs, the subscriptions will change.
🙌 Finally we click on the save button.
💬 Note: there is an optional configuration which is the security one, where it is required to enter the ip of the bot’s server, the domain, etc.
🔐 Security Configuration
To give more security to the application, both for Facebook and Workplace, it is important to have completed the environment variable appSecret and have set true the requireProof for the bot to work properly with these new settings.
For both cases, it is required to have the public IP of the server, since that way, it will only be limited to receive and send requests from a single authorized server.
If you have more than one public IP, or another server to balance the bot’s requests, you can add it to the list.
Facebook App
In the configuration of the app, we go to the left side menu and go to Settings > Advanced, and then down to the Security section, where we will enter our public IP, and then we will activate the option Require secret key of the app.
Workplace App
In the configuration of the app, we go down to the Security Settings section, where we will activate the option to require a secret key test of the app, and then we will enter our public IP.
🤦♂️Troubleshooting
Workplace App
❌ (#200) To subscribe to the messages field
(#200) To subscribe to the messages field, one of these permissions is needed: pages_messaging. To subscribe to the messaging_postbacks field, one of these permissions is needed: pages_messaging
You can solve this problem by configuring the webhook without selecting the subscriptions, then saving the configuration, then re-entering the app configuration and re-validating the webhook with the selected subscriptions.
💡 Contributing
Requests are welcome. For important changes, please open a topic first to discuss what you would like to change.
Please be sure to update the tests and documentation as appropriate.
This application is a starter for the creation of bots for Facebook Messenger and WorkChat (Workplace) for demonstration and education purposes. Its configuration is robust and scalable and can be used in a productive environment. Use this application to learn, experiment, retouch and practice the different options offered by the Facebook API.
For more information about the Facebook API you can read the documentation that the Messenger team prepared.
Messaging bots use a web server to process the messages they receive or to find out which messages to send. It is also necessary for the bot to be authenticated to talk to the web server and for the bot to be approved by Facebook to talk to the public.
When a person sends a message to a company in Messenger, the following happens, as long as the page uses an app to partially or completely automate the conversations. The Facebook server sends webhooks to the URL of the company’s server where the message app is hosted. That app can then reply to the person in Messenger using the Send API. This allows developers to create guided conversations for people to perform an automated process or develop an app that serves as a link between your agents and your company’s Messenger presence.
🤖 Live Demo
You can try some functions of the bot by entering here.
And you can try other kind of messages from the server documentation, don’t forget to get your ID from the chat bot persistent menu.
🙌 Let’s start
Before starting to work on our bot, we must have installed some tools in our computer that will facilitate us to work locally and be able to test some functionalities that the starter has available, and I will take for granted some basic concepts so as not to go into detail and extend the documentation.
When we have the basic requirements, we clone the repository, go to the project folder and install its dependencies.
npm install
We download the latest version of Ngrok compatible with our operating system, and decompress it in the server root.
⚙ Configurations
This application uses the config dependency to facilitate the configuration of environment variables, which makes it scalable and robust when deploying the application in different environments.
In the path ./config you will find a file called development.json which contains the settings for a local environment, while the file custom-environment-variables.json gets the key values of the environment variables displayed on the server.
Basically the file works as an object that is exported and can be consumed by invoking it in the file that requires consuming the loaded information.
If you need to add another type of data to consume, like the connection to a database, the url of some microservice, etc. you just have to add it to both files keeping the scheme.
You may find that you can’t configure some values for now, but that’s not a problem, when using the nodemon dependency, the server is in a watching state that at the slightest change of code, the server will run again.
See all available configuration properties in detail.
Server
url: It is the url of the server deployed in some environment, in the case of running it locally, you enter the url with ssl provided by ngrok.
Type: String
Default:
port: Is the port in which the application is deployed.
Type: Number
Default: 8080
context: It is the context from which the server’s api can be accessed, this way the routes in the main path of the application are not exposed.
Type: String
Default: /api
origins: The origins serve so that the application can only be consumed by reliable urls and avoid any kind of unwanted and malicious requests. You should write the urls separated with comma.
showLogInterceptor: Enables the display of the request interceptors in the logs.
Type: Boolean
Default: false
Params
fbApiVersion: Is the api version of facebook
Type: String
Default: v8.0
verifyToken: It is the verification token required by the application when invoked by facebook, this token is private and should not be exposed.
Type: String
Default: my_awesome_bot_verify_token
appSecret: It is the secret key to the app, it is required if you are going to use the security settings for the requests.
Type: String
Default:
accessToken: The access token is the alphanumeric hash that is generated when you create the application on Fecebook or Workplace.
Type: String
Default:
subscribedFields: Are the permissions required to subscribe to the application in order to interact with the user. These permissions are only required for Facebook bots and must be typed separately by comma.
userFields: It is a comma-separated list to obtain the user’s information.Documentation
Type: String
Default: id,name,first_name,last_name,email
secrets: Here you can enter any value you want to hide in the server logs of the bot, for example the id of the sender or the id of the sender. The values to hide must be written separated by comma.
Type: String
Default:
requireProof: Enables or disables the use of appsecret_proof and appsecret_time for security requests, it is required to have configured the secret key of the app to work.
Type: Boolean
Default: false
services
fbApiUrl: It is the url of the Graph API of Feacebook
Type: String
Default: https://graph.facebook.com
swagger
enabled: Enable or disable the documentation of the bot’s server endpoints with swagger.
Type: Boolean
Default: true
💻 Run server
We start the bot’s server.
npm run start
Once the server is started, we must start ngrok to create the connection tunnel between the bot’s local server and the Facebook server.
./ngrok http 8080
Windows
./ngrok.exe http 8080
To see other tunnel configurations, you can check the documentation
📚 Swagger
The project has a Swagger that has documented the most important endpoints of the project, and facilitates the configuration of the fields for the bot, such as the get started button, persistent menu and the greeting.
This documentation can be enabled or disabled from the configuration files.
Default: http://localhost:8080/api-docs
URL Scheme
<http|https>://<server_url><:port>/api-docs
🖥️ Deploy server in heroku (free)
You can run the bot server in a productive environment on any node server, in this case I will explain the steps to raise the server on the platform Heroku, which has a free version to deploy node servers, you can also hire a paid service which gives you more features.
We will need a file called Procfile, which is the one Heroku will use to initialize the server once deployed.
Its content is:
web: npm start
After logging into Heroku, click on Create new app
We write the name of our app, and select a region, and then click on Create App.
💬 note: Remember to save the name of the app, as you will need it later to replace the value of <app_name> with the name of the app.
Heroku gives you several options to deploy your server. You can do it with Heroku CLI by following the steps in the documentation, or you can deploy it directly from Github, which is much easier.
For existing repositories, simply add the heroku remote
heroku git:remote -a <app_name>
Deployment method: GitHub
We click on the connect to GitHub button, if you’ve never connected Heroku to Github, a window will open to authorize the connection so you can continue with the step of entering the name of the repository and searching it in your GitHub account, and once you find it, we click on the Connect button.
Then we select the branch we want to deploy, and click on Deploy Branch, and it will start running the deployment, downloading the code from the repository, installing the dependencies, etc.
Now we have to configure the environment variables of the server, although we can do it manually from Settings > Config Vars, there is a bash script prepared that will raise the environment variables of our .env file that is located in the ./variables folder.
npm run heroku:envs
or
bash heroku-envs.sh
📱 Setup the Facebook App
The time has come to create and configure our app on Facebook.
With the local server and the connection tunnel initialized, we will configure the app, and with the information that it will give us we will finish configuring the data that we are missing in the bot’s server.
💬 Remember that the bot’s server is in watch mode, and any changes made will be re-initialized and take the changes made.
Enter Facebook Developers and click on create app, it will open a modal to select the type of application, in our case we will create an application type “Manage business integrations“.
Now we will have to make some basic settings for the application.
We assign a name of the app to identify it, we put a contact email, we select the purpose of the app, in this case is for us, and if we have a commercial administrator account, we select one from the list, if you do not have such an account, you can create it later.
Once the information is completed, we click on Create App identifier
Then we look for Messenger in the app’s product list, and hit the configure button.
Now we are going to make the two necessary and essential configurations to be able to connect Facebook with our bot server.
Access tokens
In this part of the configuration, we will be able to manage which page or pages of facebook will have the bot available.
We click on Add or Remove pages, and select the page.
Once the page is linked to the app, we have to generate the token by clicking on the button Generate Token, and a window will open where you give us some instructions about the token.
We must check accept in order to view the full hash, then copy it and place it in the configuration of our server, if it is for development it is put in the json of ./config/development.json in the key of accessToken, and if it is for a productive environment, we must put it in the envs file in ./variables.
Now we have to configure the connection between Facebook and our server through Webhook, for this, you must have at hand the verifyToken that you configured and the bot’s server url, in this case, we will use the one provided by ngrok with ssl.
https://<id_tunnel>.ngrok.io/api/webhook/
Then click on Verify and Save, and if everything goes well, in the server terminal you should see the successful subscription message.
If the url of the webhook by ngrok changes, or you want to configure the url of the productive server, you can do it by clicking on the button Edit Callback URL and perform again the previous steps.
Add subscriptions
Now we have to add the subscriptions that will allow the bot to have certain permissions to perform the actions we need.
For that we click on the button Add subscriptions
Select from the list the basic permissions and click on Save
Then we add each permission to the configuration files separated by a comma.
These are the last settings to be made and are optional.
It consists in executing a curl script in the terminal to implement some options, don’t forget to put the access token to make it work.
💬 Note: You can run these scripts from Swagger, but you must adjust the files that are inside the ./templates/configs folder
We have finished configuring the app so that Facebook connects to the bot’s server, now we have to test it, to do this we can enter the chat page and perform a test to verify that everything is working properly.
📡 How to share your bot
Add a chat button to your webpage, go here to learn how to add a chat button your page.
🔗 Create a shortlink
You can use page username to have someone start a chat.
https://m.me/<PAGE_USERNAME>
📱 Setup the Workplace App
The configuration of the app for Workplace is quite similar to that of Facebook, it is required to have the Workplace paid account in order to enable custom integrations.
Go to the Administrator Panel, and click on the Integrations button, and in the Custom integrations section click on the Create custom integration button.
It will open a modal where we must write the name of the application and a description, then click on Create.
Once the application is created, it takes us to the configuration page of the application.
Access token
Now we are going to generate an access token and then configure it in our config, as mentioned in the configuration of the Facebook app.
Now let’s select the permissions for our bot.
Permissions
In our case we are interested in the option of Sending a message to any member.
Now we are going to grant the integration access to groups, in this case it is going to be to a specific group.
And finally, we have to configure the Webhook and the verify token and select the subscriptions we need, as we did with the Facebook app.
💬 Note: depending on the webhook configuration you select in the tabs, the subscriptions will change.
🙌 Finally we click on the save button.
💬 Note: there is an optional configuration which is the security one, where it is required to enter the ip of the bot’s server, the domain, etc.
🔐 Security Configuration
To give more security to the application, both for Facebook and Workplace, it is important to have completed the environment variable appSecret and have set true the requireProof for the bot to work properly with these new settings.
For both cases, it is required to have the public IP of the server, since that way, it will only be limited to receive and send requests from a single authorized server.
If you have more than one public IP, or another server to balance the bot’s requests, you can add it to the list.
Facebook App
In the configuration of the app, we go to the left side menu and go to Settings > Advanced, and then down to the Security section, where we will enter our public IP, and then we will activate the option Require secret key of the app.
Workplace App
In the configuration of the app, we go down to the Security Settings section, where we will activate the option to require a secret key test of the app, and then we will enter our public IP.
🤦♂️Troubleshooting
Workplace App
❌ (#200) To subscribe to the messages field
(#200) To subscribe to the messages field, one of these permissions is needed: pages_messaging. To subscribe to the messaging_postbacks field, one of these permissions is needed: pages_messaging
You can solve this problem by configuring the webhook without selecting the subscriptions, then saving the configuration, then re-entering the app configuration and re-validating the webhook with the selected subscriptions.
💡 Contributing
Requests are welcome. For important changes, please open a topic first to discuss what you would like to change.
Please be sure to update the tests and documentation as appropriate.
This project is a Streamlit-based web application that leverages a Large Language Model (LLM) with Retrieval-Augmented Generation (RAG) capabilities, powered by Snowflake. The application serves as a knowledge base for FDA 510k submissions, allowing users to chat with an AI assistant and generate submission reports.
Features
Chat interface for querying about FDA medical device submissions
Report generator for creating detailed FDA 510(k) submission reports
Integration with Snowflake for data storage and retrieval
Utilization of LLM-RAG for enhanced query responses
Install the required dependencies:
Copypip install -r requirements.txt
Set up your Snowflake connection:
Ensure you have a Snowflake account and the necessary credentials
Configure your Snowflake connection in the Streamlit secrets management.
/!\ Unfortunately RAG vector database is hosted in my snowflake account, so this project can not be runned without my credentials.
Usage
Run the Streamlit app:
Copystreamlit run streamlit_app.py
Open your web browser and navigate to the provided local URL (usually http://localhost:8501)
Use the chat interface to ask questions about FDA 510k submissions
Generate submission reports using the provided form in the “Generate Report” tab
Project Structure
streamlit_app.py: Main application file containing the Streamlit interface
helper.py: Contains helper functions for LLM interactions and report generation
requirements.txt: List of Python dependencies
assets/: Directory containing additional resources (e.g., images, documents)
Dependencies
Streamlit
Snowflake Snowpark
Pandas
Other dependencies as listed in requirements.txt
Configuration
Snowflake connection: Configure in Streamlit’s secrets management
Model selection: Available in the sidebar of the application
Debug mode: Toggle in the sidebar for additional information
Notes
This application uses vectorized PDF documents as a knowledge base
The LLM-RAG system is built on top of Snowflake’s infrastructure
Ensure proper handling of sensitive information in FDA submissions
##License
This project is licensed under the MIT License.
To build all apps and packages, run the following command:
cd my-turborepo
pnpm build
Develop
To develop all apps and packages, run the following command:
cd my-turborepo
pnpm dev
Remote Caching
Turborepo can use a technique known as Remote Caching to share cache artifacts across machines, enabling you to share build caches with your team and CI/CD pipelines.
By default, Turborepo will cache locally. To enable Remote Caching you will need an account with Vercel. If you don’t have an account you can create one, then enter the following commands:
cd my-turborepo
npx turbo login
This will authenticate the Turborepo CLI with your Vercel account.
Next, you can link your Turborepo to your Remote Cache by running the following command from the root of your Turborepo:
Displays the border-radius property that CSS uses when a user creates a border. You can only change a specific side or all at once, then copy what you’ve done and paste into your code.
User sees the created border-radius and can adjust its position.
User can only correct a specific side or all at once.
User can copy the result.
Additional functionality
User can select a specific browser prefix.
User can go and see the documentation for this property.
Used technologies and libraries
React
TypeScript
CSS Modules
create-react-app
Available Scripts
In the project directory, you can run:
yarn start
Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.
The page will reload if you make edits.
You will also see any lint errors in the console.
yarn test
Launches the test runner in the interactive watch mode.
See the section about running tests for more information.
yarn build
Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about deployment for more information.
yarn eject
Note: this is a one-way operation. Once you eject, you can’t go back!
If you aren’t satisfied with the build tool and configuration choices, you can eject at any time. This command will remove the single build dependency from your project.
Instead, it will copy all the configuration files and the transitive dependencies (webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except eject will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own.
You don’t have to ever use eject. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it.
This repository contains a web application built using React.js and Vite. The application is designed to showcase best-selling books. Users can browse through a curated list of books, view details about each book, and interact with the application seamlessly.
Features
Browse a curated list of best-selling books.
View details about each book, including title, author, description, and rating.
Search functionality to find specific books.
Responsive design for optimal viewing on various devices.
Fast and efficient performance using Vite for development and production builds.
Technologies Used
React.js
Vite
JavaScript (ES6+)
HTML5
CSS3
Getting Started
To get a local copy of the project up and running, follow these steps:
https://github.com/JohnPapad/KenKen-Solver
