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.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+#api keys
+api_keys.json

README.md

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+[![Review Assignment Due Date](https://classroom.github.com/assets/deadline-readme-button-24ddc0f5d75046c5622901739e7c5dd533143b0c8e959d652212380cedb1ea36.svg)](https://classroom.github.com/a/fSA_TVih)
+[![Review Assignment Due Date](https://classroom.github.com/assets/deadline-readme-button-8d59dc4de5201274e310e4c54b9627a8934c3b88527886e3b421487c677d23eb.svg)](https://classroom.github.com/a/fSA_TVih)
 [![Open in Visual Studio Code](https://classroom.github.com/assets/open-in-vscode-c66648af7eb3fe8bc4f294546bfd86ef473780cde1dea487d3c4ff354943c9ae.svg)](https://classroom.github.com/online_ide?assignment_repo_id=10680461&assignment_repo_type=AssignmentRepo)
 ## Final Project Repo
 

api_filter.py

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+from telethon.sync import TelegramClient
+from datetime import datetime, timedelta
+from telethon.tl.functions.channels import GetParticipantsRequest
+from telethon.tl.types import ChannelParticipantsSearch
+import json
+import pytz
+import statistics
+from urllib.request import urlopen
+
+class TelegramAPI:
+    def __init__(self):
+        with open('api_keys.json') as f:
+            keys = json.load(f)
+
+            self.api_id = keys['api_id']
+            self.api_hash = keys['api_hash']
+            self.bot_token = keys['bot_token']
+
+    def get_all_messages(self,username):
+        einelist = []
+        with TelegramClient('test', self.api_id, self.api_hash) as client:
+
+            #offset_date=lastweekcutoff
+            for message in client.iter_messages(username,reverse=False):
+                #finds all reaction types and converts it to likes
+                einelist.append(message)
+                #print(type(message.date))
+            #print(len(einelist))
+        return einelist
+
+    def filter_timeframe(self,einelist, timeframe):
+        now = datetime.now(pytz.timezone('US/Eastern'))
+
+        timeframes = {
+            'hour': timedelta(hours=1),
+            'day': timedelta(days=1),
+            'week': timedelta(weeks=1),
+            'month': timedelta(days=30),  # Approximate one month
+            'year': timedelta(days=365),
+            'recent': timedelta.max
+        }
+
+        if timeframe not in timeframes:
+            raise ValueError(f"Invalid timeframe '{timeframe}', should be one of {list(timeframes.keys())}")
+
+        if timeframe == 'recent':
+            most_recent_item = max(einelist, key=lambda item: getattr(item, "date"))
+            return [most_recent_item]
+
+        start_time = now - timeframes[timeframe]
+
+        return [item for item in einelist if getattr(item, "date") >= start_time]
+
+    def filter_metric(self,einelist,metric,username=""):
+        timeframes = {
+            'reactions': [],
+            'comments': [],
+            'forwards': [],
+            'views': [],
+        }
+        for message in einelist:
+            reactions,comments,forwards,views = 0,0,0,0
+            if message.reactions != None:
+                messagereactions = message.reactions.results
+                for reacttype in messagereactions:
+                    # print(reacttype.reaction)
+                    # print(reacttype.count)
+                    reactions += int(reacttype.count)
+
+            try:
+                if message.views != None:
+                    views += int(message.views)
+            except:print("L")
+            try:
+                if message.forwards != None:
+                    forwards += int(message.forwards)
+            except:print("L")
+
+            if message.replies != None:
+                comments += int(message.replies.replies)
+
+            timeframes['reactions'].append(reactions)
+            timeframes['comments'].append(comments)
+            timeframes['forwards'].append(forwards)
+            timeframes['views'].append(views)
+
+        return timeframes[metric]
+
+    def filter_stat(self,metriclist,stat):
+        if stat=="top":
+            return max(metriclist)
+        elif stat=="bottom":
+            return min(metriclist)
+        elif stat=="average":
+            return statistics.mean(metriclist)
+        elif stat=="median":
+            statistics.median(metriclist)
+        else:
+            return -1
+
+    def response_from_labels(self,timeframe,stat,metric,user):
+        fullacountlist = self.get_all_messages(user)
+        timefilteredlist = self.filter_timeframe(fullacountlist,timeframe)
+        metricfilteredlist = self.filter_metric(timefilteredlist,metric)
+        wantedstat = self.filter_stat(metricfilteredlist,stat)
+        return wantedstat
+
+    def get_follower_count(self,username):
+        url =f"https://api.telegram.org/bot{self.bot_token}/getChatMembersCount?chat_id=@{username}"
+        with urlopen(url) as f:
+            resp = json.load(f)
+
+        return int(resp['result'])
+
+
+
+
+
+
+if __name__ == "__main__":
+    pass
+    # t = TelegramAPI()
+    # einelist = t.get_all_messages("")
+    # filteredlist = filter_timeframe(einelist,"day")
+    # print(filteredlist)
+    # print(len(filteredlist))
+
+
+    # print(filter_metric(filteredlist,"comments"))
+    # print(response_from_labels("recent","top","comments","disclosetv"))

chatgptprompts.py

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+import requests
+import json
+import openai
+import os
+
+
+class ChatBot:
+    def __init__(self) -> None:
+        openai.api_key = os.environ.get("OPENAI_API_KEY")
+
+        self.messages = [
+            {"role": "system", "content": "You are a kind helpful social media assistant."},
+        ]
+
+
+    def querychatgpt(self, initmessage,stat):
+        message = f"You are a helpful social media assistant for an account using Telegram. A user asks '{initmessage}'. The answer to this question is '{str(stat)}'. Please write a response to that and don't worry about missing context, and do not mention that you lack any context. Also try to keep the response in two sentences or under."
+        # print(message)
+
+        self.messages.append(  {"role": "user", "content": message},)
+
+        chat = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=self.messages)
+
+        reply = chat.choices[0].message.content
+        self.messages.append({"role": "assistant", "content": reply})
+        return reply
+
+# c = ChatBot()
+
+# print(c.querychatgpt( "what was the average amount of likes i got in the last month?",12))