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13e4835 211a2f2 13e4835 986cd95 13e4835 986cd95 13e4835 986cd95 d14f99d 185161c d14f99d 986cd95 d14f99d 986cd95 d14f99d 986cd95 d14f99d 211a2f2 d14f99d 986cd95 13e4835 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 | import streamlit as st
import requests
from dotenv import load_dotenv
import os
import pandas as pd
import time
import chardet
from helper.telemetry import collect_telemetry
from helper.upload_File import uploadFile
from helper.button_behaviour import hide_button
from helper.initialize_analyze_session import initialize_analyze_session
class Twitter:
def __init__(self, model_url):
self.file_dict = {}
self.model_url = model_url
#self.analyst_name = analyst_name
#self.data_src = data_src
#self.analyst_description = analyst_description
self.initialize()
self.row1()
def initialize(self):
# FOR ENV
load_dotenv()
'''
# AGENT NAME
st.header(self.analyst_name)
# EVALUATION FORM LINK
url = os.getenv('Link')
st.write('Evaluation Form: [Link](%s)' % url)
# RETURN BUTTON
try:
if st.button("Return", type='primary'):
st.switch_page("./pages/home.py")
except Exception:
pass
'''
if 'twitter_upload' not in st.session_state:
st.session_state['twitter_upload'] = ''
def request_model(self, payload_txt):
response = requests.post(self.model_url, json=payload_txt)
response.raise_for_status()
output = response.json()
categories = []
current_footprint = []
number_of_backlinks = []
for key, value in output.items():
if key == 'json':
for item in value:
categories.append(item.get('category', 'N/A').replace('_', ' ').title())
current_footprint.append(item.get('current_footprint', 'N/A'))
number_of_backlinks.append(item.get('best_of_breed_solution', 'N/A'))
output = ""
for i in range(len(categories)):
output += f"\n\n---\n **Category:** {categories[i]}"
output += f"\n\n **Count:** {current_footprint[i]}\n\n"
output += f"**Best of Breed Solution:** {number_of_backlinks[i]}"
data = {
"": [str(category) for category in categories],
"Current Footprint": [str(footprint) for footprint in current_footprint],
"Best of Breed Solution": [str(backlink) for backlink in number_of_backlinks]
}
'''
df_output = pd.DataFrame(data)
with st.expander("AI Analysis", expanded=True, icon="🤖"):
st.table(df_output.style.set_table_styles(
[{'selector': 'th:first-child, td:first-child', 'props': [('width', '20px')]},
{'selector': 'th, td', 'props': [('width', '150px'), ('text-align', 'center')]}]
).set_properties(**{'text-align': 'center'}))
'''
return output
def detect_encoding(self, uploaded_file):
result = chardet.detect(uploaded_file.read(100000))
uploaded_file.seek(0) # Reset file pointer to the beginning
return result['encoding']
try:
linkedin_post_frequency = linkedin_content_post[~linkedin_content_post['Post title'].isna()].shape[0]
except Exception:
new_header = linkedin_content_post.iloc[0]
linkedin_content_post = linkedin_content_post[1:]
linkedin_content_post.columns = new_header
linkedin_post_frequency = linkedin_content_post[~linkedin_content_post['Post title'].isna()].shape[0]
st.write(linkedin_content_post)
st.session_state['linkedin_post_frequency'] = linkedin_post_frequency
return linkedin_post_frequency
def terminate_session(self, session):
try:
del st.session_state[session]
except KeyError:
pass
def file_upload(self, file_name, file_desc, session):
st.write("") # FOR THE HIDE BUTTON
file_name = st.file_uploader(f"{file_desc}", type='csv')
if file_name:
try:
self.terminate_session(session)
except UnboundLocalError:
pass
try:
encoding = self.detect_encoding(file_name)
st.session_state[f'{session}'] = pd.read_csv(file_name, encoding=encoding, low_memory=False)
except Exception:
pass
return file_name
def process(self):
session = st.session_state.analyze
if (self.twitter or self.twitter_er or self.twitter_pf) and session == 'clicked':
try:
combined_text = ""
with st.spinner('Uploading Twitter Files...', show_time=True):
st.write('')
# INITIALIZING SESSIONS
combined_text += f"Client Summary: {st.session_state.nature}\n"
try:
combined_text += f"\nTwitter Followers: {self.twitter}"
combined_text += f"\nTwitter Audience Engagement Rate: {self.twitter_er}%"
combined_text += f"\nTwitter Post Frequency: {self.twitter_pf}"
except KeyError:
pass
# OUTPUT FOR SEO ANALYST
payload_txt = {"question": combined_text}
#result = self.request_model(payload_txt)
#end_time = time.time()
#time_lapsed = end_time - start_time
debug_info = {'data_field' : 'Twitter', 'result': combined_text}
'''
debug_info = {
#'analyst': self.analyst_name,
'url_uuid': self.model_url.split("-")[-1],
'time_lapsed': time_lapsed,
'payload': payload_txt,
'result': result,
}
'''
collect_telemetry(debug_info)
st.session_state['twitter_upload'] = 'uploaded'
st.session_state['analyzing'] = False
except AttributeError:
st.info("Please upload CSV or PDF files first.")
hide_button()
def row1(self):
self.twitter = st.text_input("Followers:", placeholder='Enter Twitter Followers')
self.twitter_er = st.text_input("Audience Engagement Rate:", placeholder='Enter Twitter Audience Engagement Rate')
self.twitter_pf = st.text_input("Post Frequency:", placeholder='Enter Post Frequency')
followers = {
'Twitter Followers': self.twitter if self.twitter else 'N/A',
}
'''
st.write("") # FOR THE HIDE BUTTON
st.write("") # FOR THE HIDE BUTTON
st.write("AI Analyst Output: ")
st.session_state['analyzing'] = False
st.write("") # FOR THE HIDE BUTTON'
'''
#analyze_button = st.button("Analyze", disabled=initialize_analyze_session())
self.process()
if __name__ == "__main__":
st.set_page_config(layout="wide")
upload = uploadFile()
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