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web/build | ||
nlp/best_model.pt | ||
nlp/google_creds.js | ||
nlp/pathnlp | ||
pathnlp |
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1. Install an Apache and MySQL server. XAMPP is a good option that comes as a bundle and compatible with all major OS: https://www.apachefriends.org/download.html | ||
2. (Optional) Create a virtual host and put all the files from this repository at the root of this new virtual host. Example URL: pathwi.se or path.wise | ||
3. Create a Database named "pathwise_prototype" with a username of 'root' and password ''. Copy of these details can be found at validate/index.php line no 32-35 | ||
4. Install the Open AI based Emotion and Comment Type classification system from here: https://github.com/UIC-LIT/misty-emot/ Update the origins value in the src/server/main.py file with the virtual host URL from Step 2. You may use "*" as value too for the staging/dev environemnt | ||
4. (Skip this step if you don't want to test AI powred comments) Install the Open AI based Emotion and Comment Type classification system from here: https://github.com/UIC-LIT/misty-emot/ Update the origins value in the src/server/main.py file with the virtual host URL from Step 2. You may use "*" as value too for the staging/dev environemnt | ||
5. Update the SERVER_URL variable at the begining of the following files: assets/main.js and assets/main-working.js of this repositry. The value should match the server URL you get from Step 4. | ||
6. Update the misty_IP variable in assets/robot-play.js file with the appropriate robot IP | ||
6. Update the misty_IP variable in assets/robot-play.js file with the appropriate robot IP. (This step makes the robot speak on the go, need to configure the speech parameters to make it more human sounding) | ||
7. That makes the system running with all dependencies. You may now open the teachers side of the editor from pathwi.se/index-working.htm or the other virtual host option from Step 2 if you choose so. Make annotations as you seem fit and save them. The student facing one fetches the latest data from your latest save. Please use the 'Cold nose article' for this simulation for now. Thanks |
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