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Run locally

This document shows how to run the watson-voice-bot server on your local machine.

Steps

  1. Clone the repo
  2. Create Watson services on IBM Cloud
  3. Upload the Watson Assistant workspace
  4. Configure .env with credentials
  5. Run the application

1. Clone the repo

Use the following command to clone the watson-voice-bot GitHub repository.

git clone https://github.com/IBM/watson-voice-bot

2. Create Watson services on IBM Cloud

Use the following links to create the Watson services on IBM Cloud:

3. Upload the Watson Assistant workspace

  • Find the Assistant service in your IBM Cloud Dashboard Services.
  • Click on your Watson Assistant service and then click on Launch Watson Assistant.
  • Use the left sidebar and click on the Skills icon.
  • Click the Create skill button.
  • Select the Dialog skill card and click Next.
  • Select the Import skill tab.
  • Click the Choose JSON File button and choose the data/skill-insurance-voice-bot.json file in your cloned watson-voice-bot repo.
  • Make sure the Everything button is enabled.
  • Click Import.
  • Go back to the Skills page (use the left sidebar).
  • Look for insurance-voice-bot card.
  • Click on the three dots in the upper right-hand corner of the card and select View API Details.
  • Copy the Workspace ID GUID. Save it for the next step. "Get Workspace ID"

4. Configure .env with credentials

Our services are created and the workspace is uploaded. It's now time to let our application run locally and to do that we'll configure a simple text file with the environment variables we want to use. We begin by copying the sample.env file and naming it .env.

cp sample.env .env

First, edit the .env file and set the WORKSPACE_ID to the value that was retrieved in the previous step.

Next, set the key-value pairs with credentials for each IBM Cloud service (Assistant, Speech to Text, and Text to Speech).

  • Find each service in your IBM Cloud Dashboard Services.
  • Click on a service to view its Manage page.
  • Use the copy icon and copy/paste the API Key and URL into your .env file for each service.

sample.env

# Copy this file to .env before starting the app.
# Replace the credentials with your own.

# Watson Speech to Text
SPEECH_TO_TEXT_APIKEY=<add_speech-to-text_apikey>
SPEECH_TO_TEXT_URL=<add_speech-to-text_url>

# Watson Text to Speech
TEXT_TO_SPEECH_APIKEY=<add_text-to-speech_apikey>
TEXT_TO_SPEECH_URL=<add_text-to-speech_url>

# Watson Assistant
ASSISTANT_APIKEY=<add_assistant_apikey>
ASSISTANT_URL=<add_assistant_url>

# Optionally, use a non-default skill by specifying your own workspace ID or name.
# WORKSPACE_ID=<add_assistant_workspace_id>
# WORKSPACE_NAME=<add_assistant_workspace_name>

5. Run the application

  • The server requires Python 3.5 and above. It has been tested with Python 3.8.0.

  • The general recommendation for Python development is to use a virtual environment (venv). To install and initialize a virtual environment, use the venv module on Python 3:

Create the virtual environment using Python. Use one of the two commands depending on your Python version.

Note: python may be named python3 on your system.

python -m venv mytestenv

Now source the virtual environment. Use one of the two commands depending on your OS.

source mytestenv/bin/activate  # Mac or Linux
./mytestenv/Scripts/activate   # Windows PowerShell

TIP 💡 To terminate the virtual environment use the deactivate command.

  1. Start the app by running:
pip install -r requirements.txt
python app.py
  1. Launch a browser and navigate to http://localhost:5000
  2. Click on the microphone icon to begin speaking and click it again when you are finished.

return