import streamlit as st import requests from dotenv import load_dotenv import os import time from helper.telemetry import collect_telemetry from helper.upload_File import uploadFile from helper.button_behaviour import hide_button, unhide_button from helper.initialize_analyze_session import initialize_analyze_session import pandas as pd class SeoOnCrawl: def __init__(self, model_url): self.uploaded_files = [] self.file_dict = {} self.file_gt = {} 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 = [] remarks = [] for key, value in output.items(): if key == 'json': for item in value: categories.append(item.get('elements', 'N/A').replace('_', ' ').title()) remarks.append(item.get('remarks', 'N/A')) output = "" for i in range(len(categories)): output += f"\n\n---\n **Category:** {categories[i]}" output += f"\n\n **Remarks:** {remarks[i]}\n\n" data = { "Category": [str(category) for category in categories], "Remarks": [str(footprint) for footprint in remarks], } 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 process(self): session = st.session_state.analyze if self.uploaded_files and session == 'clicked': combined_text = "" with st.spinner('Uploading Crawl File...', show_time=True): st.write('') try: for file_info in st.session_state['uploaded_files'].values(): if file_info['type'] == 'pdf': combined_text += file_info['content'] + "\n" elif file_info['type'] == 'csv': try: combined_text += "CrawlFile CSV: {"+ file_info['content'].to_csv(index=True) + "\n" except AttributeError: pass except KeyError: pass ''' try: for f in st.session_state['uploaded_gt'].values(): if f['type'] == 'pdf': combined_text += "GTmetrix: {"+ f['content'] + "}\n" elif f['type'] == 'csv': combined_text += f['content'].to_csv(index=True) + "\n" 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' : 'Crawl', 'result': combined_text} ''' debug_info = {#'analyst': self.analyst_name, 'url_uuid': self.model_url.split("-")[-1], 'time_lapsed' : time_lapsed, 'crawl_file': [file.name for file in self.uploaded_files] if self.uploaded_files else ['Not available'], #'gt_metrix': [file.name for file in self.gtmetrix] if self.gtmetrix 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 try: self.file_dict.popitem() except KeyError: pass def row1(self): #st.write(self.data_src) self.uploaded_files = st.file_uploader("Crawl File - ScreamingFrog:", type=['pdf', 'csv'], accept_multiple_files=True, key="seo_on_backlink") #self.gtmetrix = st.file_uploader("GTmetrix", type=['pdf', 'csv'], accept_multiple_files=True, key="seo_on_gt") if self.uploaded_files: upload.multiple_upload_file(self.uploaded_files) self.file_dict = upload.file_dict #if self.gtmetrix: # upload.upload_gt(self.gtmetrix) #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 self.process() if __name__ == "__main__": st.set_page_config(layout="wide") upload = uploadFile()