df_ai_int / classes /Seo_Backlinks.py
Ronio Jerico Roque
Update spinner messages to reflect file upload actions across multiple classes
c75d56b
import streamlit as st
import requests
from dotenv import load_dotenv
import os
import pandas as pd
import pandas._libs.tslibs.parsing
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 SeoBacklinks:
def __init__(self, model_url):
self.uploaded_files = []
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'''
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 **Current Footprint:** {current_footprint[i]}\n\n"
output += f"**Number of Backlinks:** {number_of_backlinks[i]}"
data = {
"": [str(category) for category in categories],
"Current Footprint": [str(footprint) for footprint in current_footprint],
"Best of Breed Solutions": [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']
def keyword_ranking(self, df_seo):
keyword_ranking = df_seo
st.session_state['keyword_ranking'] = keyword_ranking
keywords_ranking_sorted = keyword_ranking.sort_values("Position", ascending=True)
keywords_ranking_top_10 = keywords_ranking_sorted[keywords_ranking_sorted["Position"] <= 10].shape[0]
keywords_ranking_top_100 = keywords_ranking_sorted[keywords_ranking_sorted["Position"] <= 100].shape[0]
keyword_ranking = {
'Keyword_top_10': keywords_ranking_top_10,
'Keyword_top_100': keywords_ranking_top_100
}
st.session_state['keyword_ranking'] = keyword_ranking
def traffic_files(self, df_traffic):
traffic_channels = df_traffic
try:
traffic_channels.rename(columns={traffic_channels.columns[0]: 'date'}, inplace=True)
traffic_channels['date'] = pd.to_datetime(traffic_channels['date'], format='mixed')
except pandas._libs.tslibs.parsing.DateParseError:
pass
traffic_channels_sort = traffic_channels.sort_values("date", ascending=False)
organic_traffic = traffic_channels_sort['Organic Search'].values[0]
paid_traffic = traffic_channels_sort['Paid Search'].values[0]
direct_traffic = traffic_channels_sort['Direct'].values[0]
referral_traffic = traffic_channels_sort['Referral'].values[0]
st.session_state['organic_traffic'] = organic_traffic
st.session_state['paid_traffic'] = paid_traffic
st.session_state['direct_traffic'] = direct_traffic
st.session_state['referral_traffic'] = referral_traffic
def ga4_traffic(self, others):
st.session_state['others'] = others
ga4_paid_social = others['Sessions'].values[0]
ga4_organic_traffic = others['Sessions'].values[4]
ga4_direct_traffic = others['Sessions'].values[2]
ga4_referral_traffic = others['Sessions'].values[3]
st.session_state['ga4_paid_social'] = ga4_paid_social
st.session_state['ga4_organic_traffic'] = ga4_organic_traffic
st.session_state['ga4_direct_traffic'] = ga4_direct_traffic
st.session_state['ga4_referral_traffic'] = ga4_referral_traffic
def delete_sessions(self):
try:
del st.session_state['df_traffic']
del st.session_state['others']
del st.session_state['df_seo']
del st.session_state['keyword_ranking']
del st.session_state['ga4_paid_social']
del st.session_state['ga4_organic_traffic']
del st.session_state['ga4_direct_traffic']
del st.session_state['ga4_referral_traffic']
del st.session_state['organic_traffic']
del st.session_state['paid_traffic']
del st.session_state['direct_traffic']
del st.session_state['referral_traffic']
except KeyError:
pass
def row1(self):
'''
#st.write("") # FOR SPACINGs
file_src = st.radio(
"Traffic File Type",
["SemRush", "GA4"],
captions=[
"Limit 200MB CSV",
"Limit 200MB CSV",
],
)
self.page_index = st.text_input("Pages Indexed:", placeholder='Enter Pages Indexed')
self.bounce_rate = st.text_input("Bounce Rate:", placeholder='Enter Bounce Rate')
followers = {
'Pages Indexed': self.page_index if self.page_index else 'N/A',
'Bounce Rate': self.bounce_rate if self.bounce_rate else 'N/A'
}
st.write("") # FOR SPACINGs
'''
self.uploaded_files = st.file_uploader("Backlinks (SEO)", type=['pdf', 'csv'], accept_multiple_files=True, key="seo1")
if self.uploaded_files:
self.delete_sessions()
upload.upload_file_seo(self.uploaded_files)
self.file_dict = upload.file_dict
'''
st.write("") # FOR THE HIDE BUTTON
self.uploaded_file_seo = st.file_uploader("Upload SEO Keywords CSV (SEMRush)", type='csv', key="seo2")
if self.uploaded_file_seo:
self.delete_sessions()
try:
encoding_seo = self.detect_encoding(self.uploaded_file_seo)
st.session_state['df_seo'] = pd.read_csv(self.uploaded_file_seo, encoding=encoding_seo, low_memory=False, key="seo3")
except Exception:
pass
if file_src == "SemRush":
st.write("") # FOR THE HIDE BUTTON
self.uploaded_file = st.file_uploader("Upload a Traffic File CSV", type='csv')
if self.uploaded_file:
self.delete_sessions()
try:
encoding = self.detect_encoding(self.uploaded_file)
st.session_state['df_traffic'] = pd.read_csv(self.uploaded_file, encoding=encoding, low_memory=False, key="seo4")
except Exception:
pass
elif file_src == "GA4":
st.write("") # FOR THE HIDE BUTTON
self.others = st.file_uploader("Upload a Traffic File CSV", type='csv', key="seo5")
if self.others:
self.delete_sessions()
try:
st.session_state['others'] = pd.read_csv(self.others, skiprows=9)
except Exception:
pass
'''
'''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())
start_time = time.time()
if st.session_state['analyze'] == 'clicked':
hide_button()
if self.uploaded_files:
combined_text = ""
with st.spinner('Uploading Backlinks...', show_time=True):
st.write('')
'''
# INITIALIZING SESSIONS
combined_text += f"Pages Indexed: {self.page_index}\n"
combined_text += f"Bounce Rate: {self.bounce_rate}\n"
'''
try:
backlink_files = self.file_dict
combined_text += f"Number of backlinks {backlink_files}\n\n"
except KeyError:
pass
'''
try:
df_traffic = st.session_state['df_traffic']
self.traffic_files(df_traffic)
organic_traffic = st.session_state['organic_traffic']
paid_traffic = st.session_state['paid_traffic']
direct_traffic = st.session_state['direct_traffic']
referral_traffic = st.session_state['referral_traffic']
combined_text += df_traffic.to_csv(index=True)
combined_text += f"\nOrganic Traffic: {organic_traffic}"
combined_text += f"\nPaid Traffic: {paid_traffic}"
combined_text += f"\nDirect Traffic: {direct_traffic}"
combined_text += f"\nReferral Traffic: {referral_traffic}"
except KeyError:
pass
try:
df_seo = st.session_state['df_seo']
self.keyword_ranking(df_seo)
keyword_ranking = st.session_state['keyword_ranking']
combined_text += f"\nKeyword Ranking Top 10: {keyword_ranking['Keyword_top_10']}"
combined_text += f"\nKeyword Ranking Top 100: {keyword_ranking['Keyword_top_100']}\n\n"
combined_text += df_seo.to_csv(index=True)
except KeyError:
pass
try:
others = st.session_state['others']
self.ga4_traffic(others)
ga4_paid_social = st.session_state['ga4_paid_social']
ga4_organic_traffic = st.session_state['ga4_organic_traffic']
ga4_direct_traffic = st.session_state['ga4_direct_traffic']
ga4_referral_traffic = st.session_state['ga4_referral_traffic']
traffics = ga4_direct_traffic + ga4_organic_traffic + ga4_paid_social + ga4_referral_traffic
combined_text += f"Traffics: {traffics}"
combined_text += f"Paid Traffic: {ga4_paid_social}\nOrganic Traffic: {ga4_organic_traffic}\nDirect Traffic: {ga4_direct_traffic}\nReferral Traffic: {ga4_referral_traffic}"
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 = {
#'analyst': self.analyst_name,
'url_uuid': self.model_url.split("-")[-1],
'time_lapsed': time_lapsed,
#'backlink_files': [*st.session_state['uploaded_files']],
'seo_file': [self.uploaded_file_seo.name] if self.uploaded_file_seo else ['Not available'],
'payload': payload_txt,
'result': result,
}
collect_telemetry(debug_info)
#with st.expander("Debug information", icon="⚙"):
# st.write(debug_info)
st.session_state['analyzing'] = False
if __name__ == "__main__":
st.set_page_config(layout="wide")
upload = uploadFile()