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This project is based on the Watson Recipe Bot example. The Watson Recipe Bot is a Slack bot that recommends recipes based on ingredients or cuisines. This project is essentially a fork of the Watson Recipe Bot with some additional features, including:
- Multi-user support - the original application supported only a single user interacting with the bot at a time. This application supports multiple users interacting with the bot at the same time.
- Deploy to Bluemix - the original application was designed to be run locally. This application can be run locally, or deployed as a web application to Bluemix.
- Cloudant integration - this application adds Cloudant integration for caching 3rd party API calls and storing each user's chat history (the ingredients, cuisines, and recipes they have selected).
- Additional Watson Conversation intent - this application adds a "favorites" intent which allows a user to request their favorite recipes based on the history stored in Cloudant.
####Prefer Node.js?
There is a Node.js version of this project here.
Before you get started read the original blog post to understand how the Watson Recipe Bot works. You do not need to follow the instructions in the blog post. All the instructions required to run the bot are below. After cloning this repo follow the steps below.
The following environment variables are required to run the application:
SLACK_BOT_TOKEN=xxxx-xxxxxxxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxx
SLACK_BOT_ID=UXXXXXXXX
SPOONACULAR_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
CONVERSATION_USERNAME=xxxxxxx-xxxx-xxxx-xxxxx-xxxxxxxxxxxxx
CONVERSATION_PASSWORD=xxxxxxxxxxxx
CONVERSATION_WORKSPACE_ID=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
CLOUDANT_USERNAME=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx-bluemix
CLOUDANT_PASSWORD=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
CLOUDANT_URL=https://xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx-bluemix.cloudant.com
CLOUDANT_DB_NAME=watson_recipe_bot
We will show you how to configure the necessary services and retrieve these values in the instructions below:
The following prerequisites are required to run the application.
- A Bluemix account.
- A Watson Conversation service provisioned in your Bluemix account.
- A Cloudant service provisioned in your Bluemix account.
- A Spoonacular API key. A free tier is available, however a credit card is required.
- A Slack account and permission in your Slack team to register a Slack bot.
To run locally you will need Python 2 or 3, pip and virtualenv.
To push your application to Bluemix from your local development environment you will need the Bluemix CLI and Dev Tools.
We'll start by getting your local development environment set up. If you haven't already install Python, pip, and virtualenv.
You can install Python by following the instructions here.
You can install pip by following the instructions here.
You can install virtualenv by following the instructions here.
From the command-line cd into the watson-recipe-bot-python-cloudant directory:
git clone https://github.com/ibm-cds-labs/watson-recipe-bot-python-cloudant
cd watson-recipe-bot-python-cloudant
Create and activate a new virtual environment:
virtualenv venv
source ./venv/bin/activate
Install the application requirements:
pip install -r requirements.txt
Copy the .env.template file included in the project to .env. This file will contain the environment variable definitions:
cp .env.template .env
In this next step we'll create a new Slack bot in your Slack team.
In your web browser go to https://my.slack.com/services/new/bot. Make sure you sign into the appropriate Slack team. You can also change the Slack team from the pulldown in the top right.
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You'll start by choosing a username for your bot. In the field provided enter sous-chef.
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Click the Add bot integration button.
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On the following screen you will find the API Token. Copy this value to your clipboard.
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Open the .env file in a text editor.
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Paste the copied token from your clipboard as the SLACK_BOT_TOKEN value:
SLACK_BOT_TOKEN=xoxb-xxxxxxxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxx
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Save the .env file
Next, we need to get the Slack ID of the bot.
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From the command-line run the following command:
python scripts/get_bot_id.py
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The script should print out the bot ID. The output should be similar to the following:
Bot ID for 'sous-chef' is U3XXXXXXX
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Copy and paste the bot ID into your .env file:
SLACK_BOT_ID=U3XXXXXXX
In this next step we'll set up your Spoonacular account. Spoonacular is a Food and Recipe API. The application uses Spoonacular to find recipes based on ingredient or cuisines requested by the user.
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In your web browser go to https://spoonacular.com/food-api.
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Click the Get Access button.
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Click the appropriate button to gain access (i.e. Get Regular Access)
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Choose the appropriate Pricing plan (i.e. Basic) and click the Subscribe button.
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Follow the instructions to sign into or sign up for a Mashape account.
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After you have subscribed to Spoonacular in the Documentation tab find a curl example on the right. It should look similar to this:
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Copy the value of the X-Mashape-Key and paste it into your .env file:
SPOONACULAR_KEY=vxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
If you do not already have a Bluemix account click here to sign up.
Login to your Bluemix account.
First, we'll walk you through provisioning a Watson Conversation service in your Bluemix account:
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From your Bluemix Applications or Services Dashboard click the Create Service button.
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In the IBM Bluemix Catalog search for Watson Conversation.
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Select the Conversation service.
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Click the Create button on the Conversation detail page.
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On your newly created Conversation service page click the Service Credentials tab.
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Find your newly created Credentials and click View Credentials
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Copy the username and password into your .env file:
CONVERSATION_USERNAME=xxxxxxx-xxxx-xxxx-xxxxx-xxxxxxxxxxxxx CONVERSATION_PASSWORD=xxxxxxxxxxxx
Next, let's launch the Watson Conversation tool and import our conversation workspace.
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Go back to the Manage tab.
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Click the Launch tool button.
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Log in to Watson Conversation with your Bluemix credentials if prompted to do so.
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On the Create workspace page click the Import button.
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Choose the workspace.json file in the application directory (watson-recipe-bot-python-cloudant/workspace.json).
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Click the Import button.
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Under Workspaces you should now see the Recipe Bot.
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Click the menu button (3 vertical dots) and click View Details
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Copy the Workspace ID and paste it into your .env file:
CONVERSATION_WORKSPACE_ID=40xxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
We're almost there! Next, we'll provision an instance of Cloudant in our Bluemix account. After this step we will be able to run our bot locally.
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From your Bluemix Applications or Services Dashboard click the Create Service button.
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In the IBM Bluemix Catalog search for Cloudant.
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Select the Cloudant NoSQL DB service.
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Click the Create button on the Cloudant detail page.
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On your newly created Cloudant service page click the Service Credentials tab.
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Find your newly created Credentials and click View Credentials
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Copy the username, password, and the url into your .env file:
CLOUDANT_USERNAME=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx-bluemix CLOUDANT_PASSWORD=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx CLOUDANT_URL=https://xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx-bluemix.cloudant.com
We're now ready to test our bot. From the command-line run the following command:
python run.py
If all is well you should see output similar to the following:
Getting database...
Creating database watson_recipe_bot...
sous-chef is connected and running!
To interact with the bot open Slack, go to the Slack team where you installed the bot, start a direct conversation with sous-chef, and say "hi".
You can deploy the application to Bluemix by following a few simple steps.
We will be using the cf push
command to deploy the application to Bluemix from our local environment.
If you have not yet installed the Bluemix CLI and Dev Tools click here
for instructions on how to download and configure the CLI tools.
Once you have the CLI tools run the following command (make sure you are in the watson-recipe-bot-python-cloudant directory):
cf push
It will take a few minutes for the application to be uploaded and created in Bluemix. The first time you deploy the application it will fail to start. This is because we need to add our environment variables to the application in Bluemix.
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After a few minutes has passed and your
cf push
command has completed log in to Bluemix. -
Find and click the watson-recipe-bot-cloudant application under Cloud Foundry Applications in your Apps Dashboard.
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On the application page click Runtime in the menu on the left then click Environment Variables:
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Add each environment variable from your .env file and click the Save button:
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Your app will automatically restart, but it may fail again. Wait for a minute or two and restart your app again.
To verify that your bot is running open Slack and start a direct conversation with sous-chef. Slack should show that sous-chef is active:
Here are some sample conversations you can have with sous-chef:
For more information on how the sous-chef bot works read the original blog post.
We will be publishing a new blog post soon that will discuss the enhancements we have made to the original application, including how we are using Cloudant to store chat history and enable the new "favorites" intent.
This application includes code to track deployments to IBM Bluemix and other Cloud Foundry platforms. The following information is sent to a Deployment Tracker service on each deployment:
- Application Name (
application_name
) - Space ID (
space_id
) - Application Version (
application_version
) - Application URIs (
application_uris
)
This data is collected from the VCAP_APPLICATION
environment variable in IBM Bluemix and other Cloud Foundry platforms. This data is used by IBM to track metrics around deployments of sample applications to IBM Bluemix to measure the usefulness of our examples, so that we can continuously improve the content we offer to you. Only deployments of sample applications that include code to ping the Deployment Tracker service will be tracked.
Deployment tracking can be disabled by removing or commenting out the following line in server.py
:
deployment_tracker.track()
Licensed under the Apache License, Version 2.0.