remove config.py

.gitignore

@@ -356,8 +356,8 @@ fabric.properties
 
 #################### NotepadPP.gitignore ####################
 
-# Notepad++ backups #
-*.bak
+# Notepad++ backups #
+*.bak
 
 #################### PuTTY.gitignore ####################
 
@@ -485,7 +485,8 @@ $RECYCLE.BIN/
 .LSOverride
 
 # Icon must end with two \r
-Icon
+Icon
+
 
 # Thumbnails
 ._*
@@ -511,4 +512,6 @@ Temporary Items
 # add your custom gitignore here:
 !.gitignore
 !.gitsubmodules
-skills/config.py
+backend/skills/config.py
+tempdir*/
+tmpdir*/

README.md

@@ -0,0 +1,43 @@
+# A Siri like AI Assistant
+
+* Uses ChatGPT for general queries
+* Uses Wolfram Alpha for anything math related
+* Has built in NLP (using a NLI model) for determining if we can process query locally
+* Frontend/Backend architecture for ability to deploy lightweight clients
+
+
+## Skills
+
+- [ ] Translations
+- [ ] Alarms
+- [ ] Calendar
+- [ ] Gmail
+- [ ] ChatGPT
+- [ ] Reminders
+- [x] Timers - TODO: Adding in sound notifications.
+- [ ] Todos
+- [ ] Weather
+- [ ] Wolfram
+- [x] NLP
+- [x] Speech to Text (frontend for sure)
+- [ ] API
+	- [ ] Authentication
+	- [ ] General API
+- [ ] TTS  
+	- generate audio on backend or frontend?
+		- Perks of backend is fast generation
+		- Cons of backend is large file transfers between devices, lots of internet usage
+		- Perks of frontend is less data transfer between devices requiring less internet usage
+		- Cons of frontend is slower generation
+	- Current Solution: https://github.com/synesthesiam/opentts
+
+
+## API Specs
+
+Using websockets for communication allows for two way communication where the server can send the client info at any point
+Link for example: https://stackoverflow.com/questions/53331127/python-websockets-send-to-client-and-keep-connection-alive
+More examples (includes jwt authentication, though this is in node.js, still useful for figuring out how to do this stuff): https://www.linode.com/docs/guides/authenticating-over-websockets-with-jwt/
+
+## Ideas
+
+* Dashboard with api call counts

backend/NLP.py

@@ -0,0 +1,133 @@
+# Natural Language Processing using something like https://spacy.io
+
+# THIS WORKS REALLY WELL FOR WHAT WE NEED: https://huggingface.co/facebook/bart-large-mnli
+# Zero Shot Classification - Natrual Language Inference
+# basically this means we can list all the different skill names and the model will give us a 
+# percentage probability that we are talking about each of them. We should be able to take the top
+# value and pass valid information from the query into the skill class after extracting information
+# using another model for tokenization. This took me an entire week of research to figure out -_-
+
+# this will allow us to figure out what the query means 
+# i.e we might not have to add the word "wolfram" into a query to send it to wolfram...
+
+# import spacy
+
+
+# nlp = spacy.load("en_core_web_sm")
+
+# doc = nlp("What is the weather in toronto")
+
+# for token in doc.ents:
+# 	print(token)
+# 	# if token.like_num:
+# 		# print(tokenx)
+
+
+# from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+# tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-mnli")
+
+# model = AutoModelForSequenceClassification.from_pretrained("facebook/bart-large-mnli")
+
+from transformers import pipeline
+import spacy
+
+from datetime import datetime
+import time
+
+# text = "When Sebastian Thrun started working on self-driving cars at Google in 2007, few people outside of the company took him seriously."
+
+# doc = nlp(text)
+
+
+
+
+class NLP:
+    def __init__(self, candidate_labels=[]):
+        self.candidate_labels = candidate_labels
+
+        self.classifier = pipeline("zero-shot-classification",
+                      model="facebook/bart-large-mnli")
+
+        self.tokenclass = spacy.load("en_core_web_sm")
+
+
+
+    def get_skill(self, sentence):
+        return self.classifier(sentence, self.candidate_labels)
+
+    def get_named_entities(self, sentence):
+        return [[ent.text, ent.start_char, ent.end_char, ent.label_] for ent in self.tokenclass(sentence).ents]
+
+        # for ent in doc.ents:
+            # print(ent.text, ent.start_char, ent.end_char, ent.label_)
+
+        # return self.tokenclass(sentence)
+
+
+
+if __name__ == "__main__":
+    starttime = time.time()
+    nlp = NLP(['weather', 'timer', 'physics', 'mathematics'])
+    print(f"Init: {time.time()-starttime}")
+    starttime = time.time()
+    print('==')
+    print(nlp.get_skill("one day I will see the world"))
+    print(f"Took: {time.time()-starttime}")
+    starttime = time.time()
+    print("yay!")
+    print(nlp.get_skill("What is the weather today?"))
+    print(f"Took: {time.time()-starttime}")
+    starttime = time.time()
+    print('==')
+
+
+    print(nlp.get_skill("What is air resistance of a spaceship with a mass of 1000kg"))
+    print(f"Took: {time.time()-starttime}")
+    starttime = time.time()
+
+    print(nlp.get_skill("What is five plus five"))
+    print(f"Took: {time.time()-starttime}")
+    starttime = time.time()
+
+    print('====')
+    print(nlp.get_named_entities("one day I will see the world"))
+    print(f"Took: {time.time()-starttime}")
+    starttime = time.time()
+    print("yay!")
+    print(nlp.get_named_entities("What is the weather today in london?"))
+    print(f"Took: {time.time()-starttime}")
+    starttime = time.time()
+    print('====')
+
+    print('======')
+    print(nlp.get_named_entities("set a timer for 1 minute and 15 seconds"))
+    print(f"Took: {time.time()-starttime}")
+    starttime = time.time()
+    print(nlp.get_named_entities("remind me at May 5th at 2:30 in the afternoon to wash the dog"))
+    print(f"Took: {time.time()-starttime}")
+    starttime = time.time()
+    print(nlp.get_skill("remind me at May 5th at 2:30 in the afternoon to wash the dog"))
+    print(f"Took: {time.time()-starttime}")
+    starttime = time.time()
+    print('======')
+# sequence_to_classify = "one day I will see the world"
+# candidate_labels = ['travel', 'cooking', 'dancing']
+# print(classifier(sequence_to_classify, candidate_labels))
+
+
+# import spacy
+# from spacy.matcher import Matcher
+
+# nlp = spacy.load("en_core_web_sm")
+# matcher = Matcher(nlp.vocab)
+# # Add match ID "HelloWorld" with no callback and one pattern
+# pattern = [{"LOWER": "hello"}, {"IS_PUNCT": True}, {"LOWER": "world"}]
+# matcher.add("HelloWorld", [pattern])
+
+# doc = nlp("Hello, world! Hello world!")
+# matches = matcher(doc)
+# for match_id, start, end in matches:
+#     string_id = nlp.vocab.strings[match_id]  # Get string representation
+#     span = doc[start:end]  # The matched span
+#     print(match_id, string_id, start, end, span.text)

backend/api.py

@@ -0,0 +1 @@
+#using FastAPI because I used that for ThermalTodos with auth0 auth and dont want to relearn auth0

backend/auth.py

@@ -0,0 +1,8 @@
+# TODO: Handle all authentication stuff for verifying client is who we think it is in here.
+
+# Example: https://github.com/miguelgrinberg/REST-auth
+
+# User/Pass for initial token and refresh token generation, this should 
+# OAuth2 style authentication
+# Flask-RESTFul with 
+# 

backend/main.py

@@ -0,0 +1,31 @@
+from skills.alarms import Alarms
+from skills.cal import Cal
+from skills.gmail import Gmail
+from skills.gpt import GPT
+from skills.reminders import Reminders
+from skills.timers import Timers
+from skills.todos import Todos
+from skills.weather import Weather
+from skills.wolfram import Wolfram
+
+from NLP import NLP
+
+import sys
+print(sys.version)
+
+skills = [GPT(), Alarms(), Cal(), Gmail(), Reminders(), Timers(), Todos(), Weather(), Wolfram()]
+skill_names = [skill.trigger_phrase for skill in skills]
+
+print("test")
+
+if __name__ == "__main__":
+	# print("Skill Trigger Phrases: ")
+
+	print(f"Active Skills: {skill_names}")
+
+
+	nlp = NLP()
+
+
+	# for skill in skills:
+		# print(skill.trigger_phrase)

backend/requirements.txt

@@ -0,0 +1,4 @@
+transformers
+spacy
+schedule
+ctparse

backend/skills/alarms.py

@@ -0,0 +1,11 @@
+
+"""
+Basically going to be the same as timers.py
+
+Maybe we just call timers.py from here?
+
+"""
+
+class Alarms:
+	def __init__(self):
+		self.trigger_phrase = "alarms"

backend/skills/auth.py

@@ -0,0 +1,12 @@
+# TODO: Handle all authentication stuff for verifying client is who we think it is in here.
+
+"""
+Reading material for this:
+
+https://auth0.com/blog/using-m2m-authorization/
+https://git.imsam.ca/sam/ThermalTodos/src/branch/main/application/main.py (FastAPI + Auth0)
+(previous link is based on this) https://auth0.com/blog/build-and-secure-fastapi-server-with-auth0/
+
+THIS IS GOING TO BE AN ABSOLUTE PAIN TO WORK ON, I SPENT LITERALLY ABOUT 8 HOURS JUST ON THERMALTODOS AUTH
+I HOPE THIS ISNT AS PAINFUL
+"""

backend/skills/cal.py

@@ -0,0 +1,11 @@
+
+"""
+Reading Material:
+
+https://developers.google.com/calendar/api/quickstart/python
+https://git.imsam.ca/sam/ThermalTodos/src/branch/main/application/sync_calendar.py (readonly application of previous link)
+"""
+
+class Cal:
+	def __init__(self):
+		self.trigger_phrase = "calendar"

backend/skills/config.py.example

@@ -0,0 +1,4 @@
+# Copy & Rename this file to config.py and fill in data
+ntfy_url="" # Obtained from ntfy.sh app (choose a random string of numbers/letters for better security)
+deepl_api_key="" # Obtained from https://www.deepl.com/en/docs-api
+google_api_key="" #Obtained from https://cloud.google.com/translate/pricing

backend/skills/gmail.py

@@ -0,0 +1,11 @@
+
+"""
+Reading Material:
+
+https://developers.google.com/gmail/api/quickstart/python
+https://git.imsam.ca/sam/ThermalTodos/src/branch/main/application/sync_calendar.py (for autherizing user)
+"""
+
+class Gmail:
+	def __init__(self):
+		self.trigger_phrase = "gmail"

backend/skills/gpt.py

@@ -0,0 +1,5 @@
+
+
+class GPT:
+	def __init__(self):
+		self.trigger_phrase = "gpt"

backend/skills/reminders.py

@@ -0,0 +1,12 @@
+
+
+"""
+Using notification logic from timers.py to notify at specified time
+have web app to access list of reminders? (notion api?)
+
+look into location based reminders and see if thats possible (maybe ntfy.sh supports this?)
+"""
+
+class Reminders: # ntfy.sh notification?
+	def __init__(self):
+		self.trigger_phrase = "reminders"

backend/skills/timers.py

@@ -0,0 +1,116 @@
+import requests
+
+if __name__ == "__main__": # Handle running this script directly vs as a project
+	from config import ntfy_url
+	from utility import parsetime2
+else:
+	from skills.config import ntfy_url
+	from skills.utility import parsetime2
+
+
+import threading
+import schedule
+import time
+
+# def job_that_executes_once():
+    # Do some work that only needs to happen once...
+    # return schedule.CancelJob
+
+
+def run_continuously(schedule, interval=1): 
+	# Borrowed from schedule documentation, why reinvent the wheel when its been created.
+    """Continuously run, while executing pending jobs at each
+    elapsed time interval.
+    @return cease_continuous_run: threading. Event which can
+    be set to cease continuous run. Please note that it is
+    *intended behavior that run_continuously() does not run
+    missed jobs*. For example, if you've registered a job that
+    should run every minute and you set a continuous run
+    interval of one hour then your job won't be run 60 times
+    at each interval but only once.
+    """
+    cease_continuous_run = threading.Event()
+
+    class ScheduleThread(threading.Thread):
+        @classmethod
+        def run(cls):
+            while not cease_continuous_run.is_set():
+                schedule.run_pending()
+                time.sleep(interval)
+
+    continuous_thread = ScheduleThread()
+    continuous_thread.start()
+    return cease_continuous_run
+
+
+# while True:
+#     schedule.run_pending()
+#     time.sleep(1)
+
+
+class Timers:
+	def __init__(self):
+		self.trigger_phrase = "timer"
+		self.timers = {}
+		self.schedule = schedule.Scheduler()
+
+
+	def _notify(self, device_id, timer_name):
+		r = requests.post(f"https://ntfy.sh/{device_id}",
+				data=f"{timer_name}",
+				headers={
+					"Title": "Your timer is going off!",
+					"Priority": "default",
+					"Tags": "bell"
+				})
+		return r
+
+	def _add_timer(self, duration, name):
+		if len(self.timers) == 0:
+			self.stop_run_continuously = run_continuously(self.schedule)
+		self.timers[name] = time.mktime(duration.timetuple())
+		self.schedule.every().day.at(time.strftime("%H:%M:%S", duration.timetuple())).do(self._trigger_timer, name).tag(name)
+		# use https://schedule.readthedocs.io/en/stable/examples.html#run-a-job-once to trigger self._trigger_timer()
+
+	def _remove_timer(self, name):
+		del self.timers[name]
+		if len(self.timers) == 0:
+			self.stop_run_continuously.set()
+
+	def _trigger_timer(self, name):
+		if name in self.timers:
+			res = self._notify(ntfy_url, name).text
+			print(res)
+
+			self._remove_timer(name)
+
+		# TODO: play timer done sound, send response on api saying to listen to ntfy.sh for signal to trigger sound.
+		# Better option for two way communication: WEBSOCKETS!
+		return schedule.CancelJob
+
+	def get_remaining_time(self, name=""): #TODO: test this function
+		"""Returns time remaining for timer as seconds remaining"""
+		return self.timers[name]-time.mktime(datetime.now().timetuple())
+		# if name == "":
+
+
+	def run(self, query="", duration_string="", name=""):
+		if "add" in query:
+			# duration = time.mktime(parsetime2(duration_string).timetuple())
+			duration = parsetime2(duration_string)
+			self._add_timer(duration, name)
+			return True # Return true to indicate success
+		if "remove" in query:
+			self._remove_timer(name)
+			return True
+		return False # Return false to indicate failure
+
+	def _disable_timer_check_thread(self):
+		self.stop_run_continuously.set()
+
+
+if __name__ == "__main__":
+	dur = Timers()
+	dur.run("add", "15 seconds", "test timer")
+	# dur._add_timer(123, "123")
+	# dur._trigger_timer("123")

backend/skills/todos.py

@@ -0,0 +1,5 @@
+
+
+class Todos: # Notion api?
+	def __init__(self):
+		self.trigger_phrase = "todos"

backend/skills/translations.py

@@ -0,0 +1,70 @@
+import requests
+from skills.config import deepl_api_key
+from skills.config import google_api_key
+
+
+"""
+Reading material for this:
+
+https://www.deepl.com/en/docs-api
+https://cloud.google.com/translate/docs/overview
+"""
+
+class Translations:
+	def __init__(self):
+		self.trigger_phrase = "translate"
+
+		# These vars would be good canidates for a future monitoring dashboard
+		self.total_chars_translated = 0
+		self.deepl_chars_translated = 0
+		self.googl_chars_translated = 0 #only increment if api charged for the characters (read docs to figure this out)
+		self.free_monthly_char_limit_googl = 500000
+		self.free_monthly_char_limit_deepl = 500000
+		self.supported_deepl_langs = ["list of supported languages"]
+
+
+	def _get_language_code(self, query):
+		return "FR" #TODO: Convert parse language from query and convert possibly into lang code depending on api requirements
+		# Return None if language not recognized
+
+	def _clean_up_text(self, query):
+		return "cleaned up text" #TODO: remove characters that are not needed to translate text (apis charge per char sent, not per char translated)
+
+
+	def translate_deepl(self, text, language):
+
+		self.deepl_chars_translated += len(text)
+
+		headers = {
+			'Authorization': 'DeepL-Auth-Key ' + deepl_api_key,
+			'Content-Type': 'application/json',
+		}
+
+		json_data = {
+			'text': [text],
+			'target_lang': language,
+		}
+
+		response = requests.post('https://api-free.deepl.com/v2/translate', headers=headers, json=json_data)
+
+		return response
+
+	def translate_google(self, text, language):
+		self.google_chars_translated += len(text)
+
+
+		return "" #TODO: add in google translate api, probably using python client library for google api
+
+
+	def translate(self, text):
+		parsed_text = self._clean_up_text(text) #TODO: Parse text and extract language and query from it,
+		target_language = self._get_language_code(text)
+
+		if target_language in self.supported_deepl_langs:
+			return self.translate_deepl(parsed_text, target_language)
+
+		if target_language is not None:
+			return self.translate_google(text, target_language)
+
+		return self.translate_google(text, "auto")
+

backend/skills/utility.py

@@ -0,0 +1,51 @@
+from ctparse import ctparse #Used for parsing time (parsetime), https://github.com/comtravo/ctparse
+import parsedatetime #Used for parsing time (parsetime2), https://github.com/bear/parsedatetime
+
+from datetime import datetime
+import time
+
+def parsetime(phrase):
+	"""
+	Takes in natrual language time phrase, outputs datetime object
+	"""
+
+	ts = datetime.now()
+	p = ctparse(phrase, ts=ts)
+	if p is not None:
+		return p.resolution.dt
+	return p
+
+	# return ctparse(phrase, ts=ts)
+
+
+def parsetime2(phrase):
+	"""
+	Takes in natrual language time phrase, outputs datetime object 
+	Handles seconds better
+	Doesnt handle 'in the afternoon'
+	Does handle 'this afternoon'
+	"""
+
+	time_struct, parse_status = parsedatetime.Calendar().parse(phrase)
+	return datetime(*time_struct[:6])
+
+if __name__ == "__main__":
+	t = parsetime('May 5th 2:30 in the afternoon')
+	print(t)
+
+	# t2 = parsetime('15 seconds')
+	# # print(t2)
+	# # print(t2)
+	# if t2 is not None:
+	# 	print(t2.resolution)
+
+
+	t2 = parsetime2('now')
+	print(time.mktime(t2.timetuple()))
+
+	t3 = parsetime2('in 5 minutes 30 seconds')
+	print(time.mktime(t3.timetuple()))
+
+	print(time.strftime("%H:%M:%S", t3.timetuple()))
+	# for x in t:
+		# print(x)

backend/skills/weather.py

@@ -0,0 +1,5 @@
+
+
+class Weather: #open weather map api
+	def __init__(self):
+		self.trigger_phrase = "weather"

backend/skills/wolfram.py

@@ -0,0 +1,5 @@
+
+
+class Wolfram: #wolfram alpha api
+	def __init__(self):
+		self.trigger_phrase = "wolfram"

frontend/auth.py

@@ -0,0 +1 @@
+# TODO: Handle all authentication stuff for verifying server is who we think it is in here.

frontend/main.py

@@ -22,3 +22,9 @@ stop_listening = r.listen_in_background(m, callback)
 print("Listening...")
 while True:
     time.sleep(0.1)
+
+
+# TODO: Make api request to backend with resulting text in callback function.
+
+# Use to connect to backend with bi-directional communication, allows for alarms/timers/etc to work: 
+# https://pypi.org/project/websocket-client/

frontend/tts.py

@@ -0,0 +1 @@
+# make requests to https://github.com/synesthesiam/opentts and play resulting wav file

skills/config.py.example

@@ -1,2 +0,0 @@
-# Copy & Rename this file to config.py and fill in data
-ntfy_url="" # Obtained from ntfy.sh app (choose a random string of numbers/letters for better security)

skills/timers.py

@@ -1,47 +0,0 @@
-from config import ntfy_url
-import requests
-
-class Timers:
-	def __init__(self):
-		self.trigger_phrase = "timer"
-		self.timers = {}
-
-	def _add_timer(self, time, name):
-		self.timers[name] = time
-		# use https://schedule.readthedocs.io/en/stable/examples.html#run-a-job-once to trigger self._trigger_timer()
-
-	def _remove_timer(self, name):
-		del self.timers[name]
-
-	def _trigger_timer(self, name):
-		if name in self.timers:
-			r = requests.post(f"https://ntfy.sh/{ntfy_url}",
-				data=f"{name}",
-				headers={
-					"Title": "Your timer is going off!",
-					"Priority": "default",
-					"Tags": "bell"
-				})
-			print(r.text)
-			#TODO: send ntfy.sh to device
-			#TODO: play timer done sound
-
-
-	def run(self, query):
-		if "add" in query:
-			time = 0 #TODO: Natural Language parse time out of phrase
-			self._add_timer(time)
-			return True # Return true to indicate success
-		if "remove" in query:
-			time = 0 #TODO: Natural Language parse time out of phrase
-			self._remove_timer(time)
-			return True
-		return False # Return false to indicate failure
-
-
-
-
-if __name__ == "__main__":
-	time = Timers()
-	time._add_timer(123, "123")
-	time._trigger_timer("123")

tmpdir_tts/hyperparams.yaml

@@ -1 +0,0 @@
-/Users/sam/.cache/huggingface/hub/models--speechbrain--tts-tacotron2-ljspeech/snapshots/f0c9855a337493070f576ef94dacd0ed407e04f2/hyperparams.yaml

tmpdir_tts/model.ckpt

@@ -1 +0,0 @@
-/Users/sam/.cache/huggingface/hub/models--speechbrain--tts-tacotron2-ljspeech/snapshots/f0c9855a337493070f576ef94dacd0ed407e04f2/model.ckpt

tmpdir_vocoder/generator.ckpt

@@ -1 +0,0 @@
-/Users/sam/.cache/huggingface/hub/models--speechbrain--tts-hifigan-ljspeech/snapshots/e0cc1f9be5b65d4612013f26867ca600e98bc1b6/generator.ckpt

tmpdir_vocoder/hyperparams.yaml

@@ -1 +0,0 @@
-/Users/sam/.cache/huggingface/hub/models--speechbrain--tts-hifigan-ljspeech/snapshots/e0cc1f9be5b65d4612013f26867ca600e98bc1b6/hyperparams.yaml