Run your Conversational Agent

Once you have the SIC infrastructure up and running, you do not need to relaunch SIC every time. You can thus skip the first part once that has been done. For each change that you make to your MARBEL agent, of course, you need to restart it to see the effects of those changes.

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

To stop any running servers in a terminal press ctrl C.

DON’T FORGET PIP INSTALL . IF YOU HAVE MADE ANY CHANGES IN THE SOCIAL-INTERACTOIN-CLOUD OR SIC_APPLICAITONS. DO IT TO BOTH OF THEM BEFORE RERUNNIGN EVERYTHING.

Step 1 for all Runs: Launch the Redis Server

Open the project in PyCharm (or another IDE or teriminal).
Go to your cloned repository.
Navigate to the sic_applications directory:
```
cd sic_applications
```
Start the Redis server using the provided configuration file:
```
redis-server conf/redis/redis.conf
```

If you encounter this error Could not create server TCP listening socket *:6379: bind: Address already in use read through the following collapsable section.

Error Problem Solving

Troubleshoot (Could not create server TCP listening socket *:6379: bind: Address already in use)

For Ubuntu/Debian users, if you encounter the error Could not create server TCP listening socket *:6379: bind: Address already in use., please use the following command to stop the Redis server first

sudo systemctl stop redis-server.service

And, if you wish to prevent Redis server from starting automatically at boot, you can run

sudo systemctl disable redis-server.service

If you still can’t kill Redis server, you can use ps aux | grep redis-server command to find the PID (process ID) of the Redis server. And, terminate the process using kill PID

For macOS users, the process should be similar; just find the PID of the Redis server and kill the process:

lsof -i tcp:6379

And find the *PID in the terminal response, kill the pid shown:

kill -9 *Insert PID here

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.

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

Part 1: Launch the SIC Infrastructure

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.
Run the Following Commands (in separate terminals):
- Dialogflow:
```
run-dialogflow
```

Webserver:
```
run-webserver
```
EIS:
```
start-framework
```
Run EIS Component:
```
run-eis
```

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. The link starts with localhost! Be patient and it should appear on the terminal you wrote run-eis. If you are not patient you could also try this link but it might not work considering the page is not connected yet: http://localhost:8080/start.html.
- You should see the start.html page.
Inspect Terminals (Optional):
- Do not close the terminals used for launching the SIC infrastructure.
- You can inspect these terminals to debug or monitor what is happening, such as interactions with Dialogflow.

Part 2: In Eclipse Launch the MARBEL Agent

Open the .mas2g File:
- In your agent project, locate the .mas2g file.
- Right-click on the file and choose:
```
Debug As → MARBEL
```
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.
  - 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.

Run your Intent and Slot Classifier with WHISPER

YOU CANNOT RUN THIS PART UNTIL YOU ARE DOWN WITH YOUR ENTIRE INTENT AND SLOT CLASSIFIER.

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

Step 2: Start WHISPER and NLU Services

In a new terminal WHISPER, and the NLU classifier in the background:
```
run-whisper & run-nlu &
```

Step 3: Run the Demo

Execute the demo script in the sic_applications/demos/desktop directory either in Terminal or with Pycharm:
```
python sic_applications/demo_asr_nlu.py
```

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

We will complete this shortly…