Kim Adams commited on
Commit
80b838c
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1 Parent(s): 6ca1dcd

tuning prompts

Browse files
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+ "message": "I call this \"lights-out grilled chicken nachos\"",
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+ "message": "@here Who's going in on Wednesday!? We will be having Tacos from Velvet Taco. If want lunch please drop a :taco: by EOD today:alert0:. This will help me determine how much to order! Thank you :build_heart: Buffalo Chicken - crisp tenders, house buffalo sauce, danish bleu cheese, ranch crema, carrots, micro celery, flour tortilla Picnic chicken - rotisserie chicken, avocado crema, warm honey-dijon potato salad, crispy chicken skin, cilantro, flour tortilla Mediterranean mushroom - grilled portobello mushrooms, french fries, cucumber, grilled heirloom tomatoes, dill, flour tortilla - Vegan Grilled salmon - napa slaw, citrus lime crema, pickled fresnos, roasted corn pico, avocado crema, micro cilantro, corn tortilla Side: Elote & chips- queso listo, Valentina, citrus lime crema, queso fresco, lime (edited)",
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+ "message": "@here :ai:Hey HOU Build the second Hackathon Subject Matter Expert Series hosted by Carrick Carpenter, Miles Erickson and Etienne Ohl is this Wednesday, June 7th at 10:30am PT. Learn how to cruise quicker and securely with Generative AI! Check out the Hackathon events page.",
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+ "message": "My notebook indicates there was a lunch-and-learn on robert's rules of order today, but I don't see it on the calendar. Was it cancelled/rescheduled? I don't even see the invite in my email. (edited)",
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+ "message": "Also happening tomorrow~ Wednesday June 7th at 5pm sharp is BUILD KARAOKE NIGHT!!!! :celebrate::micdrop-boom::dancefloor: @here",
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+ "message": "Hey @channel, oddly specific request: If you\u2019re an artistic human who plays Pok\u00e9mon Go, please come find me when you have a little spare time. I\u2019ve got a fun project for you.",
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+ {
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+ "message": "All thats left is shoes!!",
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+ },
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+ {
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+ "datetime": "2023-07-11 9:21 AM",
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+ "theme": "challenge",
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+ "message": "Let\u2019s see who is up to the challenge @Doug Bowen",
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+ "message": "Just FYI, our arcade machine (JOHN) is open for business! Let me know if you have any requests, concerns, or suggestions. For those asking, we have a digital marquee coming in the next few weeks and we'll be vinyl wrapping the cabinet closer to August (when our UX designer returns from leave) Have fun!",
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+ {
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+ "theme": "food",
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+ "message": "@here Hope everyone had a restful 3-day weekend! Who's going in tomorrow!? We will be having Bowls from Genghis Grill. If want lunch please drop a :dumpling: by EOD today:alert0:. This will help me determine how much to order! Thank you :build_heart: Menu: Tofu 4 U Bowl - Tofu with dragon salt, yellow onions, broccoli, roasted bell peppers, roasted sesame garlic sauce, and white rice. Topped with toasted sesame seeds and green onions. Teriyaki Chicken - Chicken, broccoli, green onion, and pineapple in a sweet soy-ginger teriyaki sauce served with white rice. Topped with crunchy chow mein. Bangkok Bowl - Chicken, crushed red pepper, ginger, yellow & green onions, sugar snap peas, red bell peppers, carrots, and Udon noodles with a savory sauce. Topped with toasted sesame seeds and green onions. Supreme Fried Rice Bowl - Steak, chicken, and shrimp with fried rice (w/ yellow & green onions, red bell peppers, carrots, & egg).",
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+ {
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+ "datetime": "2023-07-11 9:21 AM",
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+ "theme": "food",
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+ "modifier": 0,
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+ "message": "I\u2019ll take a Bangkok bowl!",
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+ "person": "Phillip Nguyen",
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+ },
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+ {
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+ "datetime": "2023-07-11 9:21 AM",
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+ "theme": "slalomversary",
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+ "modifier": 0,
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+ "message": "Happy 6 year anniversary to the formation of Houston :_b: QE :celebrate-all: @Logan Le @Blake Bryce @King Khan",
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+ "theme": "volunteer opportunity",
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+ "message": "Hey hey hey Houston! Hope you all had a relaxing and enjoyable 3-day weekend. Partners 4 Good will be building Worthy Bags Friday June 2 from 12-1pm 12:30-1:30pm. If you are interested in helping, reply here and I\u2019ll forward you the invite. Also, feel free to just stop by and help out. Hope to see you Friday! (edited)",
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+ "message": "@here a quick note, the first session of the Hackathon Subject Matter Expert Series with Bethany Mudd and Chris Samuels is tomorrow, May 31st at 10:30am PT. Learn how to reimagine the art of the possible with Generative AI:ai:. You can join by using the add to calendar function from the Hackathon events page.",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "message": "@here Hey everyone! If you are currently at the Slalom office and drive a white Mercedes SUV (license plate OKPAKO), please move it immediately as it is parked in a reserved spot on Level 3 and will be towed if not moved by 1pm. giphy (4).gif",
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+ "message": "Hello fellow builders, :brad-badge: BRAD :brad-badge: will be down for the rest of the month as he undergoes an external rework and final physical build. Please ask the Ops team to validate your ticket in the mean time. Thanks everyone!",
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+ "message": "@channel Who's going in on Wednesday!? For lunch, We will be having lunch from Bellagreen. If want lunch please drop a :lunch-bag: by EOD today. This will help me determine how much to order! Thank you:build_heart: Options Below , comes with chips and fresh fruit...",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "message": "@channel Also happening on Wednesday is the Woodside Build Center Tour beginning at 9am. I would like to have as many Builders in the office as possible. Please make every effort to be on-site. Thank you.",
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+ "message": "how to tell someone sitting behind you chewing ice from a solo cup that it is really on your nerves? - asking for a friend",
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+ "message": "Please wish @Christy Nolan a happy 2 year Slalomversary!",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "message": "@here Good morning everyone! We are having our CCC today in the rice room from 9:00-10:00am!",
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+ "message": "Is anyone else getting signed out of their sessions from one day to the next? My Chrome tab that had a sharepoint open, logged me out, my Salesforce link, logged out... Anyone else?",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "theme": "lost and found",
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+ "message": "UPDATE: They've been found! Thank you @Alexa De La Garza and @Josh Mascorro :meow_heart: If anyone sees/saw the wine bottles I won from the auction for Target Hunger can you please put them by Melanie\u2019s desk :melting_face: I think I left them by Rice where we were having karaoke or maybe even by the elevators.",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "message": "@here :alert-blue:calling all bakers!! Want to show off your skills & take on a challenge to be titled the best baker in the Houston Build Center?? Then enter The Great Build Bake Off!! :chefkiss::blob-birthdaycake::first_place_medal::blobwhee: We are doing Cakes this round:blob-birthdaycake:! Sign up HERE & bring your best slices on Wednesday, June 14th. More deets below :point_down: Please be sure to pre-cut the cake into bite-size, before the judging There will be a People\u2019s Choice and Judges\u2019 Choice as winners You do not need to be present during the judging time to enter. Bakeoff (2).png",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "message": "@here Hello folks! B.R.A.D is working again if anyone in the office needs parking validation :brad-badge::blue_car:",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "message": "Severe T storms just hit Northside. High winds, torrential downpour, and the traditional ceremonial power outage.",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "theme": "food",
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+ "message": "I call this \"lights-out grilled chicken nachos\"",
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+ "theme": "lunch and learn",
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+ "message": "@here Who's going in on Wednesday!? We will be having Tacos from Velvet Taco. If want lunch please drop a :taco: by EOD today:alert0:. This will help me determine how much to order! Thank you :build_heart: Buffalo Chicken - crisp tenders, house buffalo sauce, danish bleu cheese, ranch crema, carrots, micro celery, flour tortilla Picnic chicken - rotisserie chicken, avocado crema, warm honey-dijon potato salad, crispy chicken skin, cilantro, flour tortilla Mediterranean mushroom - grilled portobello mushrooms, french fries, cucumber, grilled heirloom tomatoes, dill, flour tortilla - Vegan Grilled salmon - napa slaw, citrus lime crema, pickled fresnos, roasted corn pico, avocado crema, micro cilantro, corn tortilla Side: Elote & chips- queso listo, Valentina, citrus lime crema, queso fresco, lime (edited)",
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+ "message": "@here :ai:Hey HOU Build the second Hackathon Subject Matter Expert Series hosted by Carrick Carpenter, Miles Erickson and Etienne Ohl is this Wednesday, June 7th at 10:30am PT. Learn how to cruise quicker and securely with Generative AI! Check out the Hackathon events page.",
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+ "datetime": "2023-07-11 9:21 AM",
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+ "message": "My notebook indicates there was a lunch-and-learn on robert's rules of order today, but I don't see it on the calendar. Was it cancelled/rescheduled? I don't even see the invite in my email. (edited)",
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+ "message": "Also happening tomorrow~ Wednesday June 7th at 5pm sharp is BUILD KARAOKE NIGHT!!!! :celebrate::micdrop-boom::dancefloor: @here",
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+ "person": "Linh Ta",
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+ "postId": 41,
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+ "themeSimilarity": "[0.59027778 0.6547619 0.43729575 0.34188034 0.33193277 0.37777778\n 0.13247863 0.27678571 0.52418301 0.44047619 0.59027778 0.13247863\n 0. 0.28431373 0.62727273 0.55769231 0. 0.41991342\n 0.43859649 0. 0.27378917]"
334
+ },
335
+ {
336
+ "datetime": "2023-07-11 9:21 AM",
337
+ "theme": "availability",
338
+ "modifier": 0,
339
+ "message": "BRAD is down this morning.",
340
+ "person": "Steven Murray",
341
+ "postId": 43,
342
+ "themeSimilarity": "1.0"
343
+ },
344
+ {
345
+ "datetime": "2023-07-11 9:21 AM",
346
+ "theme": "artistic pok\u00e9mon go",
347
+ "modifier": 0,
348
+ "message": "Hey @channel, oddly specific request: If you\u2019re an artistic human who plays Pok\u00e9mon Go, please come find me when you have a little spare time. I\u2019ve got a fun project for you.",
349
+ "person": "Melanie Halbert",
350
+ "postId": 44,
351
+ "themeSimilarity": "[0.53333333 1. 0.47619048 0.46052632 0.26666667 0.33333333\n 0.44444444 0.51785714 0.66666667 0.35294118 0.42857143 0.47222222\n 0. 0.26666667 0.35294118 0.55555556 0. 0.66666667\n 0.52631579 0.55555556 0. 0.50490196]"
352
+ },
353
+ {
354
+ "datetime": "2023-07-11 9:21 AM",
355
+ "theme": "shoes",
356
+ "modifier": 0,
357
+ "message": "All thats left is shoes!!",
358
+ "person": "Doug Bowen",
359
+ "postId": 47,
360
+ "themeSimilarity": "[0.30769231 0.30769231 0.38888889 0.26666667 0.42857143 0.57142857\n 0.66666667 0.25 0.39285714 0.37362637 0.5 0.33333333\n 0.26785714 0. 0.28571429 0.58823529 0.82352941 0.\n 0.40336134 0.30769231 0.25 0. 0.40225564]"
361
+ },
362
+ {
363
+ "datetime": "2023-07-11 9:21 AM",
364
+ "theme": "challenge",
365
+ "modifier": 0,
366
+ "message": "Let\u2019s see who is up to the challenge @Doug Bowen",
367
+ "person": "DataNinja",
368
+ "postId": 48,
369
+ "themeSimilarity": "[0.46153846 0.61538462 0.55555556 0.54761905 0.375 0.46153846\n 0.66666667 0.57142857 0.2 0.38181818 0.71428571 0.54545455\n 0.66666667 0.31428571 0. 0.57142857 0.4 0.66666667\n 0. 0.60180995 0.55555556 0.26666667 0. 0.30796654]"
370
+ },
371
+ {
372
+ "datetime": "2023-07-11 9:21 AM",
373
+ "theme": "arcade machine updates",
374
+ "modifier": 0,
375
+ "message": "Just FYI, our arcade machine (JOHN) is open for business! Let me know if you have any requests, concerns, or suggestions. For those asking, we have a digital marquee coming in the next few weeks and we'll be vinyl wrapping the cabinet closer to August (when our UX designer returns from leave) Have fun!",
376
+ "person": "Doug Bowen",
377
+ "postId": 49,
378
+ "themeSimilarity": "[0.34700855 0.59197012 0.35286935 0.26495726 0.460466 0.30357143\n 0.24542125 0.33730159 0.22857143 0.27478632 0.31498316 0.33913309\n 0.28787879 0.3989899 0.40487179 0. 0.34065934 0.59385965\n 0.61645299 0. 0.24442959 0.26495726 0.21388889 0.\n 0.4144244 ]"
379
+ },
380
+ {
381
+ "datetime": "2023-07-11 9:21 AM",
382
+ "theme": "lunch and learn",
383
+ "modifier": 0,
384
+ "message": "@here Hope everyone had a restful 3-day weekend! Who's going in tomorrow!? We will be having Bowls from Genghis Grill. If want lunch please drop a :dumpling: by EOD today:alert0:. This will help me determine how much to order! Thank you :build_heart: Menu: Tofu 4 U Bowl - Tofu with dragon salt, yellow onions, broccoli, roasted bell peppers, roasted sesame garlic sauce, and white rice. Topped with toasted sesame seeds and green onions. Teriyaki Chicken - Chicken, broccoli, green onion, and pineapple in a sweet soy-ginger teriyaki sauce served with white rice. Topped with crunchy chow mein. Bangkok Bowl - Chicken, crushed red pepper, ginger, yellow & green onions, sugar snap peas, red bell peppers, carrots, and Udon noodles with a savory sauce. Topped with toasted sesame seeds and green onions. Supreme Fried Rice Bowl - Steak, chicken, and shrimp with fried rice (w/ yellow & green onions, red bell peppers, carrots, & egg).",
385
+ "person": "Ahmad Shareef",
386
+ "postId": 50,
387
+ "themeSimilarity": "0.6878782910462792"
388
+ },
389
+ {
390
+ "datetime": "2023-07-11 9:21 AM",
391
+ "theme": "topic: food",
392
+ "modifier": 0,
393
+ "message": "I\u2019ll take a Bangkok bowl!",
394
+ "person": "Phillip Nguyen",
395
+ "postId": 51,
396
+ "themeSimilarity": "[0.91666667 0.32051282 0.56410256 0.35828877 0.67424242 0.57142857\n 0.32051282 0.48095238 0.2967033 0.23076923 0.31223262 0.58791209\n 0.53333333 0.91666667 0.37299922 0.46153846 0. 0.48717949\n 0.625 0.375 0. 0.59027778 0.35828877 0.27619048\n 0. 0.38327228]"
397
+ },
398
+ {
399
+ "datetime": "2023-07-11 9:21 AM",
400
+ "theme": "topic: slalomversary",
401
+ "modifier": 0,
402
+ "message": "Happy 6 year anniversary to the formation of Houston :_b: QE :celebrate-all: @Logan Le @Blake Bryce @King Khan",
403
+ "person": "Blake Bryce",
404
+ "postId": 52,
405
+ "themeSimilarity": "1.0"
406
+ },
407
+ {
408
+ "datetime": "2023-07-11 9:21 AM",
409
+ "theme": "volunteer opportunity",
410
+ "modifier": 0,
411
+ "message": "Hey hey hey Houston! Hope you all had a relaxing and enjoyable 3-day weekend. Partners 4 Good will be building Worthy Bags Friday June 2 from 12-1pm 12:30-1:30pm. If you are interested in helping, reply here and I\u2019ll forward you the invite. Also, feel free to just stop by and help out. Hope to see you Friday! (edited)",
412
+ "person": "Michelle Francisco",
413
+ "postId": 53,
414
+ "themeSimilarity": "[0.33566434 0.5210084 0.52197802 0.2967033 0.29662005 0.35811119\n 0.38333333 0.29120879 0.38888889 0.40952381 0.37777778 0.36388889\n 0.35347985 0.34090909 0.25757576 0.45702435 0.40634921 0.\n 0.21978022 0.43333333 0.54298643 0. 0.27838522 0.2967033\n 0.19166667 0. 0.34090713]"
415
+ },
416
+ {
417
+ "datetime": "2023-07-11 9:21 AM",
418
+ "theme": "hackathon event",
419
+ "modifier": 0,
420
+ "message": "@here a quick note, the first session of the Hackathon Subject Matter Expert Series with Bethany Mudd and Chris Samuels is tomorrow, May 31st at 10:30am PT. Learn how to reimagine the art of the possible with Generative AI:ai:. You can join by using the add to calendar function from the Hackathon events page.",
421
+ "person": "Ahmad Shareef",
422
+ "postId": 54,
423
+ "themeSimilarity": "[0.6 0.71428571 0.72727273 0.53333333 0.6 0.48181818\n 0.33333333 0.42857143 0.66666667 0.66666667 0.8 0.35555556\n 0.76363636 0.46753247 0.5 0.6 0.36565657 0.30769231\n 0. 0.36363636 0.42857143 0.76923077 0. 0.57142857\n 0.53333333 0.30769231 0. 0.42637363]"
424
+ },
425
+ {
426
+ "datetime": "2023-07-11 9:21 AM",
427
+ "theme": "parking",
428
+ "modifier": 0,
429
+ "message": "@here Hey everyone! If you are currently at the Slalom office and drive a white Mercedes SUV (license plate OKPAKO), please move it immediately as it is parked in a reserved spot on Level 3 and will be towed if not moved by 1pm. giphy (4).gif",
430
+ "person": "Ahmad Shareef",
431
+ "postId": 55,
432
+ "themeSimilarity": "1.0"
433
+ },
434
+ {
435
+ "datetime": "2023-07-11 9:21 AM",
436
+ "theme": "topic: unknown",
437
+ "modifier": 0,
438
+ "message": "Hello fellow builders, :brad-badge: BRAD :brad-badge: will be down for the rest of the month as he undergoes an external rework and final physical build. Please ask the Ops team to validate your ticket in the mean time. Thanks everyone!",
439
+ "person": "Ethan Bowen",
440
+ "postId": 57,
441
+ "themeSimilarity": "1.0"
442
+ },
443
+ {
444
+ "datetime": "2023-07-11 9:21 AM",
445
+ "theme": "topic: food",
446
+ "modifier": 0,
447
+ "message": "Hi there - a few of us are meeting at RA Sushi for an impromptu happy hour! :cheers::kawaii-sushi: Join us - it's BYOD (Buy Your Own Drink)! :blob-wink:",
448
+ "person": "Linh Ta",
449
+ "postId": 58,
450
+ "themeSimilarity": "1.0"
451
+ },
452
+ {
453
+ "datetime": "2023-07-11 9:21 AM",
454
+ "theme": "relatable joy",
455
+ "modifier": 0,
456
+ "message": "Tell me this isn\u2019t relatable :joy: https://youtu.be/BKorP55Aqvg",
457
+ "person": "Jane",
458
+ "postId": 59,
459
+ "themeSimilarity": "[0.57142857 0.57142857 0.61538462 0.33333333 0.57142857 0.42857143\n 0.26666667 0.42857143 0.57142857 0.5 0.53333333 0.33333333\n 0.5 0.45 0.48571429 0.5 0.57142857 0.29206349\n 0.41666667 0. 0.28571429 0.44444444 0.61538462 0.\n 0.48571429 0.33333333 0.25 0. 0.2962963 ]"
460
+ },
461
+ {
462
+ "datetime": "2023-07-11 9:21 AM",
463
+ "theme": "relatable joy",
464
+ "modifier": 0,
465
+ "message": "replied to a thread: Tell me this isn\u2019t relatable :joy:\u2026 A classic, alongside this one: https://www.youtube.com/watch?v=y8OnoxKotPQ",
466
+ "person": "Stefano",
467
+ "postId": 60,
468
+ "themeSimilarity": "0.6674378132850192"
469
+ },
470
+ {
471
+ "datetime": "2023-07-11 9:21 AM",
472
+ "theme": "topic: unknown",
473
+ "modifier": 0,
474
+ "message": "Happy birthday @Ray Lopez! H-Town and Prime days are Ray\u2019s Day. balloons.jpeg balloons.jpeg",
475
+ "person": "Michelle Francisco",
476
+ "postId": 64,
477
+ "themeSimilarity": "1.0"
478
+ },
479
+ {
480
+ "datetime": "2023-07-11 9:21 AM",
481
+ "theme": "topic: artistic pok\u00e9mon",
482
+ "modifier": 0,
483
+ "message": "Hey Houston fam!:flamingo-dance: Love community theater? :performing_arts: Enjoy supporting local arts? Check out Theatre Southwest's Festival of Originals (FOO)! :tada: Theatre Southwest is a hidden gem :gem: just a hop, skip, and jump from the Build Center. In a single show, catch 5 short original works by different playwrights, each with a different director and cast. FOO runs weekends from July 28 to August 12 :spiral_calendar_pad: More info and tickets are available at the TSW website. Don't miss out!",
484
+ "person": "Keri W",
485
+ "postId": 65,
486
+ "themeSimilarity": "[0.83333333 0.33333333 0.66666667 0.36363636 0.91666667 0.66666667\n 0.46428571 0.33333333 0.6 0.64285714 0.30769231 0.38461538\n 0.4125 0.58791209 0.33838384 0.53333333 1. 0.3989899\n 0.15384615 0. 0.66666667 0.625 0.375 0.57142857\n 0. 0.59027778 0.36363636 0.28571429 0. 0.38012821]"
487
+ },
488
+ {
489
+ "datetime": "2023-07-11 9:21 AM",
490
+ "theme": "fun",
491
+ "modifier": 0,
492
+ "message": "Next Friday - Bring Your Kids to Work Day Have your kiddos ever wondered what you do all day at work or wanted to see the office? Get ready for a fun time that will surely leave them wide-eyed with wonder and brimming with excitement! It\u2019s time to mark your calendars for our. Kindly fill out the RSVP link here by July 14th. Here are some additional things to know: Kid Age Range 6 -16 Parents must be involved during this time frame (this is not a babysitting event) Have some fun!",
493
+ "person": "Michelle Francisco",
494
+ "postId": 66,
495
+ "themeSimilarity": "[0.46153846 0.46153846 0.71428571 0.55555556 0.59440559 0.59440559\n 0.4 0.72727273 0.46153846 0.72727273 0.8 0.42857143\n 0.14285714 0.29946524 0.71428571 0.31410256 0.54545455 0.72727273\n 0.36752137 0.14285714 0. 0.61538462 0.42857143 0.58823529\n 0.46153846 0. 0.58371041 0.55555556 0.26666667 0.\n 0.34351923]"
496
+ },
497
+ {
498
+ "datetime": "2023-07-11 9:21 AM",
499
+ "theme": "topic: food",
500
+ "modifier": 0,
501
+ "message": "I love subway. I'm going to order 10 footlongs for the team. Please drop a :subway: if you want to join in. I'll be ordering at 11:30. Thanks",
502
+ "person": "Doug Bowen",
503
+ "postId": 67,
504
+ "themeSimilarity": "1.0"
505
+ },
506
+ {
507
+ "datetime": "2023-07-11 9:21 AM",
508
+ "theme": "topic: food",
509
+ "modifier": 0,
510
+ "message": "Is it time for Blake to take the Milk Challenge?!?",
511
+ "person": "Srijaya Suresh",
512
+ "postId": 68,
513
+ "themeSimilarity": "1.0"
514
+ },
515
+ {
516
+ "datetime": "2023-07-11 9:21 AM",
517
+ "theme": "milk",
518
+ "modifier": 0,
519
+ "message": "Did someone say MILK? @BlakeBryce?!?",
520
+ "person": "Michelle Francisco",
521
+ "postId": 70,
522
+ "themeSimilarity": "[0.83333333 0.26666667 0.28571429 0.28571429 0.57051282 0.30769231\n 0.75 0.30769231 0.26666667 0.33333333 0.47058824 0.25\n 0.28571429 0.26666667 0.41666667 0.28571429 0.28717949 0.4\n 0.30769231 0.2952381 0.56666667 0. 0.26666667 0.26666667\n 0.28571429 0.33333333 0. 0.26495726 0.42857143 0.23529412\n 0. 0.28888889]"
523
+ },
524
+ {
525
+ "datetime": "2023-07-11 9:21 AM",
526
+ "theme": "topic: food",
527
+ "modifier": 0,
528
+ "message": "Never drank milk.",
529
+ "person": "Blake Bryce",
530
+ "postId": 71,
531
+ "themeSimilarity": "1.0"
532
+ },
533
+ {
534
+ "datetime": "2023-07-11 9:21 AM",
535
+ "theme": "topic: food",
536
+ "modifier": 0,
537
+ "message": "Blake should drink milk.",
538
+ "person": "Kim Adams",
539
+ "postId": 72,
540
+ "themeSimilarity": "1.0"
541
+ }
542
+ ]
slack_processing/data/unknown_themes.json ADDED
@@ -0,0 +1,101 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [
2
+ {
3
+ "datetime": "2023-07-11 9:21 AM",
4
+ "theme": "Unknown",
5
+ "modifier": 0,
6
+ "message": "#greenshirts #nomemoneeded IMG_6103",
7
+ "person": "DataNinja",
8
+ "postId": 45,
9
+ "themeSimilarity": 0
10
+ },
11
+ {
12
+ "datetime": "2023-07-11 9:21 AM",
13
+ "theme": "Unknown",
14
+ "modifier": 0,
15
+ "message": "Ooo.",
16
+ "person": "carlos.salazar",
17
+ "postId": 1,
18
+ "themeSimilarity": 0
19
+ },
20
+ {
21
+ "datetime": "2023-07-11 9:21 AM",
22
+ "theme": "Unknown",
23
+ "modifier": 0,
24
+ "message": ":alert0: :blob-policeangry: :oncoming_police_car: :alert0: Saw :eyes-intensify: :pirate_flag: this the other day :exploding_head: ...someone please forward :mailbox: this to :slalom:lalom :build:uild Legal:judge:",
25
+ "person": "derreck.stellpflug",
26
+ "postId": 12,
27
+ "themeSimilarity": 0
28
+ },
29
+ {
30
+ "datetime": "2023-07-11 9:21 AM",
31
+ "theme": "Unknown",
32
+ "modifier": 0,
33
+ "message": "Happy Friday",
34
+ "person": "Naeem",
35
+ "postId": 14,
36
+ "themeSimilarity": 0
37
+ },
38
+ {
39
+ "datetime": "2023-07-11 9:21 AM",
40
+ "theme": "Unknown",
41
+ "modifier": 0,
42
+ "message": "BuildersAssemblesmaller.png",
43
+ "person": "Michelle Francisco",
44
+ "postId": 24,
45
+ "themeSimilarity": 0
46
+ },
47
+ {
48
+ "datetime": "2023-07-11 9:21 AM",
49
+ "theme": "Unknown",
50
+ "modifier": 0,
51
+ "message": "., .,.;\u2019/bcv=hc=bgx[pL;IKQWSDFGHNM,////",
52
+ "person": "Jordan Lene",
53
+ "postId": 25,
54
+ "themeSimilarity": 0
55
+ },
56
+ {
57
+ "datetime": "2023-07-11 9:21 AM",
58
+ "theme": "Unknown",
59
+ "modifier": 0,
60
+ "message": "I'll miss WFWW with a cough and a fever :face_with_thermometer:",
61
+ "person": "jmoney",
62
+ "postId": 42,
63
+ "themeSimilarity": 0
64
+ },
65
+ {
66
+ "datetime": "2023-07-11 9:21 AM",
67
+ "theme": "Unknown",
68
+ "modifier": 0,
69
+ "message": "replied to a thread: #greenshirts #nomemoneeded Well, we just had to! IMG_8782.JPG.jpg",
70
+ "person": "Jane",
71
+ "postId": 46,
72
+ "themeSimilarity": 0
73
+ },
74
+ {
75
+ "datetime": "2023-07-11 9:21 AM",
76
+ "theme": "Unknown",
77
+ "modifier": 0,
78
+ "message": ":alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0: :derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0: :alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0: I'M BACK :terminator: :derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0: :alert0::derreck_5_aws::alert0: :derreck_5_aws::ampersand: Can happily :happy-fox: :speaking_head_in_silhouette: Reeeport :bangbang: :alert0: :derreck_5_aws::alert0::derreck_5_aws::alert0: :alert0::derreck_5_aws: That the wrong :sadblob: has FINALLY been righted :face_exhaling: :derreck_5_aws::alert0::derreck_5_aws::alert0: :alert0::derreck_5_aws: I'VE RECEIVED :mailbox: MY SPECIALICZAR MEDALION :promptitude: :derreck_5_aws::alert0: :alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0: :derreck_5_aws::alert0::derreck_5_aws::alert0::derreck_5_aws::alert0: IMG_3492.heic",
79
+ "person": "derreck.stellpflug",
80
+ "postId": 56,
81
+ "themeSimilarity": 0
82
+ },
83
+ {
84
+ "datetime": "2023-07-11 9:21 AM",
85
+ "theme": "Unknown",
86
+ "modifier": 0,
87
+ "message": "HTOWN TIL WE DROWN",
88
+ "person": "Chase",
89
+ "postId": 62,
90
+ "themeSimilarity": 0
91
+ },
92
+ {
93
+ "datetime": "2023-07-11 9:21 AM",
94
+ "theme": "Unknown",
95
+ "modifier": 0,
96
+ "message": "trill (896 kB) https://media4.giphy.com/media/x0vDHDAkAxS3S/giphy.gif?cid=6104955e484j64k7mgl4ober5tdsyqegtkuaok7gl1i14eta&ep=v1_gifs_translate&rid=giphy.gif&ct=g",
97
+ "person": "Chase",
98
+ "postId": 63,
99
+ "themeSimilarity": 0
100
+ }
101
+ ]
slack_processing/slack_data_prep.py CHANGED
@@ -24,9 +24,11 @@ SAMPLE_SIZE = 500
24
  MAX_TOKENS = 100
25
  EMBEDDING_MODEL = "text-embedding-ada-002"
26
  EMBEDDING_ENCODING = "cl100k_base"
 
27
 
28
  INPUT_PATH = "slack_processing/data/slack.json"
29
  OUTPUT_THEME_PATH = "slack_processing/data/themes.json"
 
30
  OUTPUT_THEME_EMBEDDINGS_PATH = "slack_processing/data/slack_with_theme_embeddings.json"
31
  TOPIC_TEXT_PATH="slack_processing/data/topics.txt"
32
  TOPIC_TEXT_OUTPUT_PATH="slack_processing/data/topics_with_synonyms.txt"
@@ -38,68 +40,39 @@ SYSTEM_MESSAGE="You are categorizing slack messages into topics that will be use
38
  NUM_RESULTS=5
39
  TEMP=.15
40
  TOP_P=.15
41
-
42
  NUM_RESULTS1=5
43
  TEMP1=.35
44
  TOP_P1=.35
45
-
46
  TOPIC_TOKENS2=50
47
  NUM_RESULTS2=5
48
  TEMP2=.65
49
  TOP_P2=.65
50
 
51
- SIMILARITY_THRESHOLD = 0.6
52
-
53
  df=pd.DataFrame()
54
  themes = []
55
- topics_with_synonyms = []
56
  game_topics = UniqueQueue()
57
- track_unknowns=[]
58
-
59
- with open(TOPIC_TEXT_PATH, 'r') as file:
60
- for line in file:
61
- main_topic_and_synonyms = line.strip().lower().split(',')
62
- main_topic = main_topic_and_synonyms[0].strip()
63
- synonyms = [synonym.strip() for synonym in main_topic_and_synonyms[1:]]
64
- topics_with_synonyms.append((main_topic, synonyms))
65
-
66
- for main_topic, synonyms in topics_with_synonyms:
67
- game_topics.enqueue(main_topic, synonyms)
68
 
69
- #print("***topics****")
70
- for topic in game_topics._queue.queue:
71
- print(topic) # Output: "slalomversary"
72
-
73
- #print ("---topics with synonyms helper list---")
74
- '''for canonical, synonyms in game_topics.review():
75
- print("Canonical term:", canonical)
76
- print("Canonical with synonyms:", canonical + ", " + ", ".join(synonyms))
77
- print() # Optional: Add a blank line '''
78
-
79
- #print("+++ synonyms for canonical")
80
- #print(game_topics.synonyms_for_canonical("Lunch and Learn")) # Output: ['L&L', 'lunch-and-learn', 'Lunch & Learn']
81
-
82
-
83
- def ProcessReactions(reactions,id):
84
- highestcount=0
85
- highestcount_reaction=""
86
- if not isinstance(reactions, list):
87
- return ""
88
- else:
89
- for reaction in reactions:
90
- stripped_reaction = reaction['emoji'].strip(':')
91
- if reaction['count'] > highestcount:
92
- highestcount = reaction['count']
93
- highestcount_reaction = stripped_reaction
94
- #print("returning highestcount_reaction:", highestcount_reaction)
95
- return highestcount_reaction
96
 
97
  def CleanMessage(message):
98
- # Remove emojis represented as :something:
99
  cleaned_message = re.sub(r':(\w+):', r'\1', message)
100
- # Remove URLs
101
  cleaned_message = re.sub(r'http\S+|www.\S+', '', cleaned_message)
102
- # Remove specific punctuation
103
  custom_punctuation = ':,.!?'
104
  translator = str.maketrans('', '', custom_punctuation)
105
  cleaned_message = cleaned_message.translate(translator)
@@ -110,11 +83,18 @@ def TruncateWords(topic,count):
110
  truncated_topic = " ".join(words[:count])
111
  return truncated_topic.title()
112
 
113
- def WriteThemes(themes):
 
114
  themes_dict = [theme for theme in themes]
115
  with open(OUTPUT_THEME_PATH, "w") as json_file:
116
  json.dump(themes_dict, json_file, indent=4)
117
 
 
 
 
 
 
 
118
  def ProcessDateTime(date_time):
119
  date_time = dt(2023, 7, 11, 9, 21)
120
  formatted_time = date_time.strftime("%Y-%m-%d %-I:%M %p")
@@ -126,8 +106,7 @@ def CompletionEngine(sys_message, user_message, num_tokens, num_results, tempera
126
  model=topic_model,
127
  messages=[
128
  {"role": "system", "content": sys_message},
129
- {"role": "user", "content": user_message},
130
- ],
131
  max_tokens=num_tokens,
132
  n=num_results,
133
  temperature=temperature,
@@ -153,6 +132,21 @@ def ConcatenateMessageAndTopics(message):
153
  print("*** prompt_message for third round is: ", prompt_message)
154
  return prompt_message
155
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
156
  # Update the process_message function
157
  def ProcessMessage(datetime, message, replies, person, id):
158
  global game_topics
@@ -168,15 +162,15 @@ def ProcessMessage(datetime, message, replies, person, id):
168
  completion=CompletionEngine(SYSTEM_MESSAGE,ConcatenateMessageAndTopics(CleanMessage(message)),TOPIC_TOKENS2, NUM_RESULTS2, TEMP2, TOPIC_MODEL,TOP_P2)
169
  options = list(set(TruncateWords(topic.strip(),3) for choice in completion.choices for concatenated_topics in choice.message.content.strip().split("\n") for topic in concatenated_topics.split(',')))
170
  print("---options: ", options)
 
171
  # Compute semantic similarity between generated topics and existing reference topics
172
  similarity_scores = []
173
  generated_topics_indices = []
174
  counter=0
175
  exact_match=False
176
  most_similar_topic = "Unknown"
177
-
178
- topic_length = len(options)
179
  unidentified_topic_count=0
 
180
  for generated_topic in options:
181
  if generated_topic != "Unknown":
182
  generated_topics_indices.append(counter)
@@ -186,7 +180,7 @@ def ProcessMessage(datetime, message, replies, person, id):
186
  for reference_topic in game_topics.all_canonicals():
187
  reference_tokens = word_tokenize(reference_topic)
188
  reference_tokens_str = " ".join(reference_tokens)
189
- similarity_score, exact_match = compute_similarity(generated_tokens_str, reference_tokens_str)
190
  if exact_match:
191
  most_similar_topic = reference_topic
192
  most_similar_score = 1.0
@@ -215,17 +209,17 @@ def ProcessMessage(datetime, message, replies, person, id):
215
  if most_similar_topic in game_topics.all_words():
216
  #if it's in all words, and a synonym, set topic to canonical, otherwise set to canonical
217
  if most_similar_topic in game_topics.all_synonyms():
218
- most_similar_topic = game_topics.canonical_for_synonym(most_similar_topic)
219
- most_similar_score=1.0
220
  else:
221
  most_similar_topic = game_topics.get_canonical(most_similar_topic)
 
222
  else:
223
  #not in all words, look for similar topics, see if it's like something in list
224
  highest_similarity = 0
225
  best_match = None
226
  for known_word in game_topics.all_words():
227
  #compute similarity against all topics
228
- similarity_score = compare_topic_to_game_topic(most_similar_topic, known_word)
229
  print("\tsimilarity_score: "+ str(similarity_score)+ " for known_word: "+ known_word)
230
  if similarity_score > highest_similarity:
231
  highest_similarity = similarity_score
@@ -243,14 +237,15 @@ def ProcessMessage(datetime, message, replies, person, id):
243
  else:
244
  #add the new topic
245
  game_topics.enqueue(most_similar_topic)
246
- theme_obj = Theme(datetime=datetime, theme=most_similar_topic, modifier=0, person=person, postId=id, message=message, similarity=str(most_similar_score))
247
- themes.append(theme_obj.to_dict())
248
 
249
- print(f"{id} From message:'{message}' to theme: {most_similar_topic}")
250
- #print(f"ThemeObj - id: {id}, theme:{theme_obj.theme}, modifier:{theme_obj.modifier}, person:{theme_obj.person}, topReaction:{theme_obj.topReaction}, message:{theme_obj.message}, similarity:{theme_obj.themeSimilarity}")
251
- return themes
 
 
252
 
253
- def compare_topic_to_game_topic(topic, game_topic):
254
  # Exact Match
255
  if topic == game_topic:
256
  return 1.0
@@ -263,15 +258,14 @@ def compare_topic_to_game_topic(topic, game_topic):
263
  # Semantic Similarity using OpenAI's cosine_similarity
264
  vectorizer = TfidfVectorizer()
265
  tfidf_matrix = vectorizer.fit_transform([topic, game_topic])
266
- semantic_similarity = coso(tfidf_matrix[0], tfidf_matrix[1])[0, 0] # Get the scalar value
267
 
268
  # Combine Scores
269
  final_score = 0.2 * overlap_score + 0.8 * semantic_similarity
270
  print("Tokens topic:", tokens_topic, "tokens game topic:", tokens_game_topic, " overlap score:", overlap_score," Semantic similarity:", str(semantic_similarity), " final score: " + str(final_score))
271
  return final_score
272
-
273
 
274
- def compute_similarity(tokens1, tokens2):
275
  if set(word_tokenize(tokens1.lower())) == set(word_tokenize(tokens2.lower())):
276
  return 1.0, True
277
  tokens1 = word_tokenize(tokens1)
@@ -302,11 +296,25 @@ def compute_similarity(tokens1, tokens2):
302
 
303
  def FetchSlack():
304
  return pd.read_json(INPUT_PATH, orient='records')
305
-
 
 
 
 
 
 
 
 
 
 
 
 
 
306
 
307
  def ProcessSlack():
308
  global df
309
  if not os.path.exists(OUTPUT_THEME_PATH):
 
310
  # Read JSON data into DataFrame
311
  df = pd.read_json(INPUT_PATH)
312
  # Keep selected columns and drop rows with missing values
@@ -314,8 +322,7 @@ def ProcessSlack():
314
  # Filter down to top reaction, then create theme.
315
  #df["reaction"] = df.apply(lambda row: ProcessReactions(row["reactions"],row["id"]), axis=1)
316
  df["datetime"] = df.apply(lambda row: ProcessDateTime(row["datetime"]), axis=1)
317
- df["theme"] = df.apply(lambda row: ProcessMessage(row["datetime"], row["message"], row["replies"], row["person"], row["id"]), axis=1)
318
- WriteThemes(themes)
319
  else:
320
  df = pd.read_json(OUTPUT_THEME_PATH)
321
  return df[["person", "theme", "message"]]
 
24
  MAX_TOKENS = 100
25
  EMBEDDING_MODEL = "text-embedding-ada-002"
26
  EMBEDDING_ENCODING = "cl100k_base"
27
+ SIMILARITY_THRESHOLD = 0.6
28
 
29
  INPUT_PATH = "slack_processing/data/slack.json"
30
  OUTPUT_THEME_PATH = "slack_processing/data/themes.json"
31
+ OUTPUT_UNKNOWN_THEME_PATH = "slack_processing/data/unknown_themes.json"
32
  OUTPUT_THEME_EMBEDDINGS_PATH = "slack_processing/data/slack_with_theme_embeddings.json"
33
  TOPIC_TEXT_PATH="slack_processing/data/topics.txt"
34
  TOPIC_TEXT_OUTPUT_PATH="slack_processing/data/topics_with_synonyms.txt"
 
40
  NUM_RESULTS=5
41
  TEMP=.15
42
  TOP_P=.15
 
43
  NUM_RESULTS1=5
44
  TEMP1=.35
45
  TOP_P1=.35
 
46
  TOPIC_TOKENS2=50
47
  NUM_RESULTS2=5
48
  TEMP2=.65
49
  TOP_P2=.65
50
 
 
 
51
  df=pd.DataFrame()
52
  themes = []
53
+ unknown_themes=[]
54
  game_topics = UniqueQueue()
 
 
 
 
 
 
 
 
 
 
 
55
 
56
+ def InitializeTopics():
57
+ global game_topics
58
+ topics_with_synonyms = []
59
+ with open(TOPIC_TEXT_PATH, 'r') as file:
60
+ for line in file:
61
+ main_topic_and_synonyms = line.strip().lower().split(',')
62
+ main_topic = main_topic_and_synonyms[0].strip()
63
+ synonyms = [synonym.strip() for synonym in main_topic_and_synonyms[1:]]
64
+ topics_with_synonyms.append((main_topic, synonyms))
65
+ for main_topic, synonyms in topics_with_synonyms:
66
+ game_topics.enqueue(main_topic, synonyms)
67
+ #print("***topics****")
68
+ for topic in game_topics._queue.queue:
69
+ print(topic)
70
+ #print("+++ synonyms for canonical")
71
+ #print(game_topics.synonyms_for_canonical("Lunch and Learn")) # Output: ['L&L', 'lunch-and-learn', 'Lunch & Learn']
 
 
 
 
 
 
 
 
 
 
 
72
 
73
  def CleanMessage(message):
 
74
  cleaned_message = re.sub(r':(\w+):', r'\1', message)
 
75
  cleaned_message = re.sub(r'http\S+|www.\S+', '', cleaned_message)
 
76
  custom_punctuation = ':,.!?'
77
  translator = str.maketrans('', '', custom_punctuation)
78
  cleaned_message = cleaned_message.translate(translator)
 
83
  truncated_topic = " ".join(words[:count])
84
  return truncated_topic.title()
85
 
86
+ def WriteThemes():
87
+ global themes
88
  themes_dict = [theme for theme in themes]
89
  with open(OUTPUT_THEME_PATH, "w") as json_file:
90
  json.dump(themes_dict, json_file, indent=4)
91
 
92
+ def WriteUnknownThemes():
93
+ global unknown_themes
94
+ unknown_themes_dict = [theme for theme in unknown_themes]
95
+ with open(OUTPUT_UNKNOWN_THEME_PATH, "w") as json_file:
96
+ json.dump(unknown_themes_dict, json_file, indent=4)
97
+
98
  def ProcessDateTime(date_time):
99
  date_time = dt(2023, 7, 11, 9, 21)
100
  formatted_time = date_time.strftime("%Y-%m-%d %-I:%M %p")
 
106
  model=topic_model,
107
  messages=[
108
  {"role": "system", "content": sys_message},
109
+ {"role": "user", "content": user_message}, ],
 
110
  max_tokens=num_tokens,
111
  n=num_results,
112
  temperature=temperature,
 
132
  print("*** prompt_message for third round is: ", prompt_message)
133
  return prompt_message
134
 
135
+ def ProcessMessageWrapper(datetime, message, replies, person, id):
136
+ global themes, unknown_themes
137
+ theme = ProcessMessage(datetime, message, replies, person, id)
138
+ print(f"Theme id: {id}, theme:{theme.theme}, modifier:{theme.modifier}, person:{theme.person}, message:{theme.message}, similarity:{theme.themeSimilarity}")
139
+
140
+ if(theme.theme=='Unknown' or theme.themeSimilarity==0):
141
+ unknown_themes.append(theme.to_dict())
142
+ WriteUnknownThemes()
143
+
144
+ else:
145
+ themes.append(theme.to_dict())
146
+ WriteThemes()
147
+
148
+ return theme
149
+
150
  # Update the process_message function
151
  def ProcessMessage(datetime, message, replies, person, id):
152
  global game_topics
 
162
  completion=CompletionEngine(SYSTEM_MESSAGE,ConcatenateMessageAndTopics(CleanMessage(message)),TOPIC_TOKENS2, NUM_RESULTS2, TEMP2, TOPIC_MODEL,TOP_P2)
163
  options = list(set(TruncateWords(topic.strip(),3) for choice in completion.choices for concatenated_topics in choice.message.content.strip().split("\n") for topic in concatenated_topics.split(',')))
164
  print("---options: ", options)
165
+
166
  # Compute semantic similarity between generated topics and existing reference topics
167
  similarity_scores = []
168
  generated_topics_indices = []
169
  counter=0
170
  exact_match=False
171
  most_similar_topic = "Unknown"
 
 
172
  unidentified_topic_count=0
173
+ theme_obj=None
174
  for generated_topic in options:
175
  if generated_topic != "Unknown":
176
  generated_topics_indices.append(counter)
 
180
  for reference_topic in game_topics.all_canonicals():
181
  reference_tokens = word_tokenize(reference_topic)
182
  reference_tokens_str = " ".join(reference_tokens)
183
+ similarity_score, exact_match = ComputeSimilarity(generated_tokens_str, reference_tokens_str)
184
  if exact_match:
185
  most_similar_topic = reference_topic
186
  most_similar_score = 1.0
 
209
  if most_similar_topic in game_topics.all_words():
210
  #if it's in all words, and a synonym, set topic to canonical, otherwise set to canonical
211
  if most_similar_topic in game_topics.all_synonyms():
212
+ most_similar_topic = game_topics.canonical_for_synonym(most_similar_topic)
 
213
  else:
214
  most_similar_topic = game_topics.get_canonical(most_similar_topic)
215
+ most_similar_score=1.0
216
  else:
217
  #not in all words, look for similar topics, see if it's like something in list
218
  highest_similarity = 0
219
  best_match = None
220
  for known_word in game_topics.all_words():
221
  #compute similarity against all topics
222
+ similarity_score = float(CompareTopicToGameTopic(most_similar_topic, known_word))
223
  print("\tsimilarity_score: "+ str(similarity_score)+ " for known_word: "+ known_word)
224
  if similarity_score > highest_similarity:
225
  highest_similarity = similarity_score
 
237
  else:
238
  #add the new topic
239
  game_topics.enqueue(most_similar_topic)
240
+ most_similar_score=1.0
 
241
 
242
+ theme_obj = Theme(datetime=datetime, theme=most_similar_topic, modifier=0, person=person, postId=id, message=message, similarity=str(most_similar_score))
243
+ print(f"{id} From message:'{message}' to theme: {most_similar_topic}")
244
+ else:
245
+ theme_obj = Theme(datetime=datetime, theme='Unknown', modifier=0, person=person, postId=id, message=message, similarity=0)
246
+ return theme_obj
247
 
248
+ def CompareTopicToGameTopic(topic, game_topic):
249
  # Exact Match
250
  if topic == game_topic:
251
  return 1.0
 
258
  # Semantic Similarity using OpenAI's cosine_similarity
259
  vectorizer = TfidfVectorizer()
260
  tfidf_matrix = vectorizer.fit_transform([topic, game_topic])
261
+ semantic_similarity = coso(tfidf_matrix[0], tfidf_matrix[1])[0, 0] # Get the scalar value
262
 
263
  # Combine Scores
264
  final_score = 0.2 * overlap_score + 0.8 * semantic_similarity
265
  print("Tokens topic:", tokens_topic, "tokens game topic:", tokens_game_topic, " overlap score:", overlap_score," Semantic similarity:", str(semantic_similarity), " final score: " + str(final_score))
266
  return final_score
 
267
 
268
+ def ComputeSimilarity(tokens1, tokens2):
269
  if set(word_tokenize(tokens1.lower())) == set(word_tokenize(tokens2.lower())):
270
  return 1.0, True
271
  tokens1 = word_tokenize(tokens1)
 
296
 
297
  def FetchSlack():
298
  return pd.read_json(INPUT_PATH, orient='records')
299
+
300
+ def ProcessReactions(reactions,id):
301
+ highestcount=0
302
+ highestcount_reaction=""
303
+ if not isinstance(reactions, list):
304
+ return ""
305
+ else:
306
+ for reaction in reactions:
307
+ stripped_reaction = reaction['emoji'].strip(':')
308
+ if reaction['count'] > highestcount:
309
+ highestcount = reaction['count']
310
+ highestcount_reaction = stripped_reaction
311
+ #print("returning highestcount_reaction:", highestcount_reaction)
312
+ return highestcount_reaction
313
 
314
  def ProcessSlack():
315
  global df
316
  if not os.path.exists(OUTPUT_THEME_PATH):
317
+ InitializeTopics()
318
  # Read JSON data into DataFrame
319
  df = pd.read_json(INPUT_PATH)
320
  # Keep selected columns and drop rows with missing values
 
322
  # Filter down to top reaction, then create theme.
323
  #df["reaction"] = df.apply(lambda row: ProcessReactions(row["reactions"],row["id"]), axis=1)
324
  df["datetime"] = df.apply(lambda row: ProcessDateTime(row["datetime"]), axis=1)
325
+ df["theme"] = df.apply(lambda row: ProcessMessageWrapper(row["datetime"], row["message"], row["replies"], row["person"], row["id"]), axis=1)
 
326
  else:
327
  df = pd.read_json(OUTPUT_THEME_PATH)
328
  return df[["person", "theme", "message"]]