MapBot | A chatbot developed in Python | Learning library
kandi X-RAY | MapBot Summary
kandi X-RAY | MapBot Summary
The primary motivation of the developers of MapBot is to provide a playground to tech enthusiasts, both beginners and advanced to try algorithms, approaches and ideas while contributing to a real-life project.
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Top functions reviewed by kandi - BETA
- Translate a text message to a bot
- Return a dictionary of features
- Return a connection to the MySQL database
- Add a question to the database
- Adds alear statement to the database
- Generate a CSV file
- Generate a dictionary of features
- Handles bot suggestions
- Gets a suggested elevation suggestion for a given text
- Search directions between two directions
- Gives geocoding suggestions from Google Maps API
- Clear all tables from the database
- Describe a table
- Setup the trained model
- Train a forest model
- Setup the database
- Setup nltk
- Receive a message
- Verify that the token sent
- Get the last chat ID and chat id
- Get the latest updates
- Get JSON from a given URL
- Get the content of the given URL
- Process user input
- Convert a text message to a bot
- Send a message to a chat
- Send a chat message
MapBot Key Features
MapBot Examples and Code Snippets
Community Discussions
Trending Discussions on Learning
QUESTION
I have been trying to learn about functional programming, but I still struggle with thinking like a functional programmer. One such hangup is how one would implement index-heavy operations which rely strongly on loops/order-of-execution.
For example, consider the following Java code:
...ANSWER
Answered 2022-Mar-07 at 21:17This is not an index-heavy operation, in fact you can do this with a one-liner with scanl1 :: (a -> a -> a) -> [a] -> [a]:
QUESTION
system：Mac OS software：AnyLogic 8 Personal Learning Edition 8.7.6 language: Java
When I run my model, the console print this info:
...Warning: the fonts "Times" and "Times" are not available for the Java logical font "Serif", which may have unexpected appearance or behavior. Re-enable the "Times" font to remove this warning.
ANSWER
Answered 2021-Aug-01 at 11:11We also recently had this issue on a mac running the latest public beta of Monterey.
For some reason the Times font was no longer installed or active on the Mac.
You can check in FontBook
You can simply reinstall it
I struggled to find a source online - her is one suggestion - https://www.freebestfonts.com/timr45w-font
QUESTION
Im attempting to find model performance metrics (F1 score, accuracy, recall) following this guide https://machinelearningmastery.com/how-to-calculate-precision-recall-f1-and-more-for-deep-learning-models/
This exact code was working a few months ago but now returning all sorts of errors, very confusing since i havent changed one character of this code. Maybe a package update has changed things?
I fit the sequential model with model.fit, then used model.evaluate to find test accuracy. Now i am attempting to use model.predict_classes to make class predictions (model is a multi-class classifier). Code shown below:
...ANSWER
Answered 2021-Aug-19 at 03:49This function were removed in TensorFlow version 2.6. According to the keras in rstudio reference
update to
QUESTION
I started learning about discord.js but now I am facing this issue. I tried some googling but couldn't manage to fix it.
...ANSWER
Answered 2021-Aug-07 at 16:34You need to specify the events which you want your bot to receive using gateway intents.
Instead of
const client = new Discord.Client();
Use
const client = new Discord.Client({ intents: [Enter intents here] })
For example
const client = new Discord.Client({ intents: ["GUILDS", "GUILD_MESSAGES"] })
Here's another useful link: https://discord.com/developers/docs/topics/gateway
QUESTION
I got this error when learning Next.js, using npx create-next-app command according to site documentation here https://nextjs.org/docs/api-reference/create-next-app. Everything works until I start the server,
Error stack:
...ANSWER
Answered 2021-Nov-24 at 21:38I found this solution https://github.com/webpack/webpack/issues/14532
if using bash just run
NODE_OPTIONS=--openssl-legacy-providerbefore any commandadding
NODE_OPTIONS=--openssl-legacy-providerto package.json
QUESTION
ANSWER
Answered 2021-Aug-16 at 13:32The ItemProperties component has multiple root nodes because it renders a list in the root with v-for.
Based on the class name (infobox-item-properties), I think you want the class to be applied to a container element, so a simple solution is to just add that element (e.g., a div) in your component at the root:
QUESTION
I am trying to use tailwindCSS in a ReactJS app
These are the scripts commands in package.json file
ANSWER
Answered 2021-Dec-18 at 22:00It looks like the Tailwind configuration from CRACO is not needed anymore.
https://github.com/facebook/create-react-app/issues/11771#issuecomment-997217680
Look at Tailwind 3.0 install steps: https://tailwindcss.com/docs/guides/create-react-app
QUESTION
I have a large dataset (~5 Mio rows) with results from a Machine Learning training. Now I want to check to see if the results hit the "target range" or not. Lets say this range contains all values between -0.25 and +0.25. If it's inside this range, it's a Hit, if it's below Low and on the other side High.
I now would create this three columns Hit, Low, High and calculate for each row which condition applies and put a 1 into this col, the other two would become 0. After that I would group the values and sum them up. But I suspect there must be a better and faster way, such as calculate it directly while grouping. I'm happy for any idea.
ANSWER
Answered 2022-Feb-10 at 16:13You could use cut to define the groups and pivot_table to reshape:
QUESTION
#include
int& addOne(int& x)
{
x += 1;
return x;
}
int main()
{
int x {5};
addOne(x) = x;
std::cout << x << ' ' << addOne(x);
}
ANSWER
Answered 2022-Feb-02 at 00:42Since C++17 the order of evaluation is specified such that the operands of = are evaluated right-to-left and those of << are evaluated left-to-right, matching the associativity of these operators. (But this doesn't apply to all operators, e.g. + and other arithmetic operators.)
So in
QUESTION
I am new to flutter and recently tried to develop a test app for learning sake with latest version Flutter 2.5. By looking at some tutorial online, I have added flutter_native_splash: ^1.2.3 package for splash screen. And works fine.
However, when I launch app for the first time, it shows following debug message
W/FlutterActivityAndFragmentDelegate(18569): A splash screen was provided to Flutter, but this is deprecated. See flutter.dev/go/android-splash-migration for migration steps.
After visiting the above link, I am not able to understand much what is supposed to be done.
Code in pubspec.yaml
...ANSWER
Answered 2022-Jan-19 at 05:24AndroidManifest.xml file.
Previously, Android Flutter apps would either set
io.flutter.embedding.android.SplashScreenDrawablein their application manifest, or implementprovideSplashScreenwithin their Flutter Activity. This would be shown momentarily in between the time after the Android launch screen is shown and when Flutter has drawn the first frame. This is no longer needed and is deprecated – Flutter now automatically keeps the Android launch screen displayed until Flutter has drawn the first frame. Developers should instead remove the usage of these APIs. - source
As per the flutter 2.8.0 update, The newly created project doesn't have this warning.
They removed unused API from Androidmanifest.yml but still have belove mentioned code.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install MapBot
Clone the repository
Create the mapbot database in mySQL mysql -uroot -p -hlocalhost Enter root password when prompted create database mapbot; Verify creation of the database show databases;
Unzip the StanfordCoreNLP package in the repository and keep the file paths stanford-corenlp-x.x.x.jar and stanford-corenlp-x.x.x-models.jar handy.
Run git update-index --assume-unchanged ENV/.env
Fill the existing template in ENV/.env with the corresponding values following the KEY=VALUE format
Install dependencies from requirements.txt file. Run pip install -r requirements.txt
You're all set up, run the init.py file. python init.py
It is recommended that you set this project up in a virtual environment to keep the dependencies separated and for easier debugging. Here's how you can do that - Python Conda
Clone the repository
Create the mapbot database in mySQL mysql -uroot -p -hlocalhost Enter root password when prompted create database mapbot; Verify creation of the database show databases;
Unzip the StanfordCoreNLP package in the repository and keep the file paths stanford-corenlp-x.x.x.jar and stanford-corenlp-x.x.x-models.jar handy.
Run git update-index --assume-unchanged ENV/.env
Fill the existing template in ENV/.env with the corresponding values following the KEY=VALUE format
Install dependencies from requirements.txt file. Run pip install -r requirements.txt
You're all set up. Execute python webapp.py to start up the server.
Visit http://127.0.0.1:5000/ to interact with your MapBot.
It is recommended that you set this project up in a virtual environment to keep the dependencies separated and for easier debugging. Here's how you can do that - Python Conda
Docker Take a look at this for detailed installation instructions for Docker on Windows, Linux and Mac systems. Verify the installations by docker --version and docker-compose --version
Clone the repository
Fill up the GCLOUD_API_KEY in ENV/docker.env
Run docker-compose up
Visit localhost:5000 to interact with the deployment
Clone the repository
Create the mapbot database in mySQL mysql -uroot -p -hlocalhost Enter root password when prompted create database mapbot; Verify creation of the database show databases;
Unzip the StanfordCoreNLP package in the repository and keep the file paths stanford-corenlp-x.x.x.jar and stanford-corenlp-x.x.x-models.jar handy.
Run git update-index --assume-unchanged ENV/.env
Fill the existing template in ENV/.env with the corresponding values following the KEY=VALUE format
For TELEGRAM_BOT_TOKEN=<YOUR_API_KEY_HERE>, open your Telegram app and follow this tutorial on how to create a new bot on Telegram and get your own bot token. Once your token is generated, update the .env file in /ENV with it.
Find your bot on Telegram using @bot_username that you chose, and send the first text to your new bot. Nothing is supposed to happen for now. No worries.
Install dependencies from requirements.txt file. Run pip install -r requirements.txt
You're all set up, run the telegram.py file. python telegram.py and converse with your bot in real time.
Clone the repository
Create the mapbot database in mySQL mysql -uroot -p -hlocalhost Enter root password when prompted create database mapbot; Verify creation of the database show databases;
Unzip the StanfordCoreNLP package in the repository and keep the file paths stanford-corenlp-x.x.x.jar and stanford-corenlp-x.x.x-models.jar handy.
Run git update-index --assume-unchanged ENV/.env
Fill the existing template in ENV/.env with the corresponding values following the KEY=VALUE format
Follow the steps prompted here to create a classic slack app. Navigate to Basic Information section of the slack app. Under the Add features and functionality subheading click on Bots. Click on Add Legacy Bot User and enter the display name and default username of your bot. Navigate to Basic Information section of the slack app on the sidebar and copy the Client ID and Client Secret and then paste these to the ENV/.env file as: SLACK_CLIENT_ID=<Your Client ID> and SLACK_CLIENT_SECRET=<Your Client Secret>. Navigate to the OAuth & Permissions section. Under the Redirect URLs subheading add http://localhost:5000/post_auth.
Install dependencies from requirements.txt file. Run pip install -r requirements.txt
Run python app.py. The server will start at your localhost. Navigate to http://localhost:5000/begin_auth. Click Add to Slack button. Select the workspace from the top right and hit Allow. Successfully completing this step would automate the creation of SLACK_BOT_TOKEN in the ENV/.env file.
In another terminal, run python slackbot.py.
Open the workspace in Slack and invite the bot to the channel: @YOUR_BOT_DEFAULT_USERNAME message in the channel. Click on Invite to Channel.
Clone the repository
Create the mapbot database in mySQL mysql -uroot -p -hlocalhost Enter root password when prompted create database mapbot; Verify creation of the database show databases;
Unzip the StanfordCoreNLP package in the repository and keep the file paths stanford-corenlp-x.x.x.jar and stanford-corenlp-x.x.x-models.jar handy.
Run git update-index --assume-unchanged ENV/.env
Fill the existing template in ENV/.env with the corresponding values following the KEY=VALUE format
Create Facebook app from here. Fill out basic information.
Set Up Messenger option under Add a Product.
Generate the Access Token by creating a facebook page for your bot by clicking on Create New Page button.
Click on Add or Remove Pages and add your facebook page just created.
Click on Generate Token and copy the token to the ENV/.env file as ACCESS_TOKEN=<YOUR_ACCESS_TOKEN>.
Install ngrok.
Open a terminal window, type ngrok http 5000. Once you do this, a screen will appear with a link after the “Forwarding” section — make sure to copy the link that begins with “https”.
Click on Add Callback URL under Webhooks section. Paste the above link in the Callback URL. Add Verify Token of your choice. Copy Verify Token you added in the ENV/.env file as VERIFY_TOKEN=YOUR_VERIFY_TOKEN. Hit Verify and Save
Click on Add Subscriptions. Check messages, messaging_postbacks, message_deliveries, messaging_pre_checkouts boxes.
Run python app.py
You can interact with bot on Facebook Messenger.
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