Duarte OC duarteocarmo

## streamlit_tool.py
import streamlit as st
from litellm import completion, stream_chunk_builder
from loguru import logger
import json
import plotly.express as px
from enum import Enum

MODEL = "gpt-4o-mini"


## exercise_1.py
import pandas


def remove_bad_cols(dataframe):
    return df.drop(
        labels=df.columns.difference(["passengerid", "price_paid"]), axis=1
    )


def add_inflation_to_price(dataframe):

## dba_scammer_whois.txt
delivery-85367.icu
% IANA WHOIS server
% for more information on IANA, visit http://www.iana.org
% This query returned 1 object

refer:        whois.nic.icu

domain:       ICU

organisation: Shortdot SA

## corona_widget.js
// Variables used by Scriptable.
// These must be at the very top of the file. Do not edit.
// icon-color: deep-green; icon-glyph: user-md;
// change "country" to a value from https://coronavirus-19-api.herokuapp.com/countries/
// teste
const country = "Portugal"
const url = `https://coronavirus-19-api.herokuapp.com/countries/${country}`
const req = new Request(url)
const res = await req.loadJSON()

## template_projector_config.json
{
  "embeddings": [
    {
      "tensorName": "My tensor",
      "tensorShape": [
        27378,
        128
      ],
      "tensorPath": "https://opera-nora-vos.dataverz.com/upload-json/upload/corona_128.tsv",
      "metadataPath": "https://opera-nora-vos.dataverz.com/upload-json/upload/corona_128_metadata.tsv"

## config.json
{
  "embeddings": [
    {
      "tensorName": "My tensor",
      "tensorShape": [
        1000,
        50
      ],
      "tensorPath": "https://gist.githubusercontent.com/duarteocarmo/d15f3d8a062640649e0dbd280eb62e0b/raw/9fbabadefaa7d6b2a1a9792f8c3dbe0e74828b53/corona_128.tsv"
    }

## corona_128.tsv

          
            0.265047
            0.402412
            0.04394
            0.232379
            -0.178385
            -0.251961
            0.033933
            0.004331000000000001
            0.269349
            0.276781
            0.62878
            0.038244
            0.018466
            0.277584
            0.291458
            0.226978
            -0.308167
            0.21948499999999999
            -0.21985100000000002
            -0.056057
            -0.211689
            0.141289
            0.465743
            -0.23253800000000002
            -0.380131
            0.171227
            0.410419
            0.256002
            -0.5630649999999999
            0.268669
            0.175975
            0.31272
            0.126661
            0.24339299999999997
            -0.068918
            0.518714
            0.3942
            0.013861000000000002
            -0.24618299999999999
            0.006409999999999999
            -0.347699
            0.708418
            0.16986099999999998
            0.181118
            0.30225
            0.41640900000000003
            0.15104700000000001
            0.227142
            0.083771
            -0.031074
            -0.435808
            -0.18545799999999998
            -0.132331
            0.30448600000000003
            0.121923
            -0.318643
            -0.02396
            0.045665
            -0.094992
            0.46035
            -0.35325700000000004
            0.138192
            0.28922
            -0.586064
            -0.11838699999999999
            -0.201355
            0.14893
            -0.661425
            0.757174
            0.35458
            0.102619
            -0.017088
            -0.057553999999999994
            -0.238733
            0.22670900000000002
            0.120297
            0.024797
            0.125356
            -0.131823
            -0.102591
            0.128919
            -0.331512
            0.396284
            -0.658933
            -0.017664
            0.464
            0.087157
            -0.170877
            -0.331757
            0.

## unfollow.py
import tweepy
import datetime

NO_ACTIVITY_FOR = 30
UNFOLLOW_COUNTER = 0
PROCESSED_USERS = 0

# get these at: https://developer.twitter.com/en/apps
access_token = ""
access_token_secret = ""

## updater.py
import subprocess
import sys
import papermill as papermill


REMOTE_FOLDER = "your cloud folder name"
LOCAL_FOLDER = "your local folder name"
TEMPLATE_NOTEBOOK = "template_notebook.ipynb"


## updater.py
import subprocess
import sys
import papermill as papermill
import os

ONEDRIVE_FOLDER = "shared folder"
LOCAL_FOLDER = "local-copy"
BASE_NOTEBOOK = ".ipynb"
	import streamlit as st
	from litellm import completion, stream_chunk_builder
	from loguru import logger
	import json
	import plotly.express as px
	from enum import Enum

	MODEL = "gpt-4o-mini"
	import pandas


	def remove_bad_cols(dataframe):
	return df.drop(
	labels=df.columns.difference(["passengerid", "price_paid"]), axis=1
	)


	def add_inflation_to_price(dataframe):
	delivery-85367.icu
	% IANA WHOIS server
	% for more information on IANA, visit http://www.iana.org
	% This query returned 1 object

	refer: whois.nic.icu

	domain: ICU

	organisation: Shortdot SA
	// Variables used by Scriptable.
	// These must be at the very top of the file. Do not edit.
	// icon-color: deep-green; icon-glyph: user-md;
	// change "country" to a value from https://coronavirus-19-api.herokuapp.com/countries/
	// teste
	const country = "Portugal"
	const url = `https://coronavirus-19-api.herokuapp.com/countries/${country}`
	const req = new Request(url)
	const res = await req.loadJSON()
	{
	"embeddings": [
	{
	"tensorName": "My tensor",
	"tensorShape": [
	27378,
	128
	],
	"tensorPath": "https://opera-nora-vos.dataverz.com/upload-json/upload/corona_128.tsv",
	"metadataPath": "https://opera-nora-vos.dataverz.com/upload-json/upload/corona_128_metadata.tsv"
	import tweepy
	import datetime

	NO_ACTIVITY_FOR = 30
	UNFOLLOW_COUNTER = 0
	PROCESSED_USERS = 0

	# get these at: https://developer.twitter.com/en/apps
	access_token = ""
	access_token_secret = ""
	import subprocess
	import sys
	import papermill as papermill


	REMOTE_FOLDER = "your cloud folder name"
	LOCAL_FOLDER = "your local folder name"
	TEMPLATE_NOTEBOOK = "template_notebook.ipynb"