Content Comparison

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• If you choose to keep your intent and slot classifier and MARBEL+Dialogflow agent separate, that is completely fine and will not negatively affect your grade.

• Connecting the entire pipeline is now optional but is considered an "easier" extension and will count significantly toward your extensions.

If you choose not to connect your entire pipeline, you can focus on implementing your exclusion features and extensions directly in Dialogflow. For detailed guidance, refer to the Exclusion Features section and its related subpages.

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1. Activate PCA25:
   Ensure that PCA25 is activated in your environment.

2. Model Checkpoints:
   Confirm you have a trained model checkpoint saved in the nlu.utils.checkpoints folder.

3. Replace File:
   Replace the existing file located at:

   Code Block
   social-interaction-cloud/sic_framework/services/eis/eiscomponent.py

   with the updated eiscomponent.py file provided:

   View file
   name eiscomponent.py

   . To use Dialogflow with this file this variable should be changed to False on line 105.

   Code Block
   # If true then you use your intent and slot classifier including Whisper otherwise Dialogflow self.params.nlu = False

Steps to Run the Pipeline:

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1. Run Whisper:
   Start the Whisper component to handle speech-to-text conversion:

   Code Block
   run-whisper

   Note: The first time you use Whisper, the transcription may take some time due to downloading the model. Be patient during this process. If it still takes a long time after the first time read the top of the eiscomponent.py file.

2. Run NLU:
   Start the natural language understanding (NLU) module:

   Code Block
   run-nlu

3. Run Webserver:
   Launch the webserver for pipeline integration:

   Code Block
   run-webserver

4. Start Framework:
   Initialize the framework:

   Code Block
   start-framework

5. Run EIS:
   Start the External Interface Service (EIS):

   Code Block
   run-eis

6. Launch Localhost:
   Open your browser and navigate to the localhost start page.

7. Run MARBEL Agent in Eclipse:
   Start the MARBEL agent within Eclipse. Ensure the agent connects successfully to the pipeline.

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