Running with Dialogflow

Running with Your Own Intent and Slot Classifier and WHISPER

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First part: Launch the SIC infrastructure

• Open a command terminal in your machine and navigate to the folder (called docker by default) where you cloned the SICproject.

• Enter docker-compose up dialogflow webserver and hit enter.

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• Open a second terminal and navigate to the subfolder sic-local in the docker folder.

• Enter java -jar computer-browser.jar and hit enter. After running java -jar computer-browser.jar a pop-up should appear like the one in the left-hand corner of the picture below. Click okay without filling in a username and password.

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• Then a Google Chrome window should open. It should say it is being controlled by automated test software and displays a long string of random characters. In your terminal, it should say ‘ChromeDriver was started successfully’ in one of the lines.

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There are three different runs you can do for this project, MARBEL with Dialogflow to test your dialogue manager (MARBEL Agent), Intent and Slot Classifier with ASR(WHISPER), all of them together without Dialogflow

Run your MARBEL agent with web pages and Dialogflow

Follow these steps to set up and run your MARBEL agent along with the SIC infrastructure.

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Step 1: Launch the Redis Server

1. Open the project in PyCharm (or another IDE).

2. Open the terminal in PyCharm:

   • Go to View > Tool Windows > Terminal.

3. Navigate to the sic_applications directory:

   Code Block
   cd sic_applications

4. Start the Redis server using the provided configuration file:

   Code Block
   redis-server conf/redis/redis.conf

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Step 2: Run Your MARBEL Agent with Web Pages and Dialogflow

Part 1: Launch the SIC Infrastructure

1. Open a New Terminal for Each Component:

   • Each component of the SIC infrastructure should run in its own terminal. You can do that really nicely in Pycharm.

   • You can even name them by right-clicking on the session like Local(2) and renaming it to reflect if it has Dialogflow or whatever.

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2. Run the Following Commands (in separate terminals):

   • Dialogflow:

     Code Block
     run-dialogflow

   • Text-to-Speech:

     Code Block
     run-text2speech

   • Webserver:

     Code Block
     run-webserver

   • EIS:

     Code Block
     start-eis

   • Run EIS Component:

     Code Block
     run-eis

3. Open the Web Interface:

   • Open any browser and navigate to the local host link printed in the terminal where you run-eis or run-webserver.

   • You should see the start.html page.

4. Inspect Terminals (Optional):

   • Do not close the terminals used for launching the SIC infrastructure.

   • You can inspect these terminals

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1. • to

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1. • debug or monitor what is

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1. • happening, such as interactions with Dialogflow

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If the Chrome browser shows Disconnected, you need to relaunch the SIC infrastructure. You can use the docker-compose down command in a terminal to clean up your docker engine.

Second part: Launch the MARBEL agent

• Launch the .mas2g file in your agent project, for example, by right-clicking on it and choosing Debug As → MARBEL from the menu. A popup should appear like the one in the left-hand corner of the picture below. The empty box in the popup next to the browser code should be ticked. Note: The browser code should match the code that is displayed in the Google Chrome window used by the agent. Finally, hit OK.

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If you want to restart your MARBEL agent, make sure your previous agent has been terminated before you restart it!

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1. • .

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Part 2: In Eclipse Launch the MARBEL Agent

1. Open the .mas2g File:

   • In your agent project, locate the .mas2g file.

   • Right-click on the file and choose:

     Code Block
     Debug As → MARBEL

2. Restarting the MARBEL Agent:

   • If you need to restart the MARBEL agent, ensure the previous instance is terminated:

     • Switch to the Debug perspective in Eclipse.

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1. • • Check if the MARBEL Debugging Engine is still running.

     • If it is running:

       • Select it and press the Terminate button (red square icon).

       • Press Remove All Terminated Launches (XX icon) to clean up the perspective.

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Run your Intent and Slot Classifier with WHISPER

Follow these steps to launch your Intent and Slot Classifier with WHISPER and run the demonstration.

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Step 1: Launch the Redis Server

1. Open the project in PyCharm (or another IDE).

2. Navigate to the sic_applications directory using the terminal:

   Code Block
   cd sic_applications

3. Start the Redis server with the provided configuration file:

   Code Block
   redis-server conf/redis/redis.conf

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Step 2: Start WHISPER and NLU Services

1. In a new terminal WHISPER, and the NLU classifier in the background:

   Code Block
   run-whisper & run-nlu &

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Step 3: Start WHISPER and NLU Services

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Step 4: Run the Demo

1. Execute the demo script in the sic_applications/demos/desktop directory either in Terminal or with Pycharm:

   Code Block
   sic_applications/demos/desktop/demo_asr_nlu.py

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Important Notes

• Ensure all required services (Redis, WHISPER, and NLU) are running before executing the demo script.

• Monitor the terminal logs for each component to ensure they are functioning correctly.

• Keep the terminals open to maintain active services while running the demo.

You’re now ready to test the Intent and Slot Classifier with WHISPER! 😊

Run the entire pipeline altogether

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