Spaces:
Sleeping
Sleeping
File size: 6,892 Bytes
97132db af5935b 567a60e 099f191 af5935b 73884d7 e634f6b 73884d7 af5935b 97132db 11d890f 97132db c676e89 1acf205 37ffd75 1acf205 d2b54c3 97132db d2b54c3 af5935b 97132db 135b203 97132db af5935b 97132db d2b54c3 97132db af5935b 97132db d2b54c3 97132db f8f385d d2b54c3 97132db d2b54c3 97132db af5935b b2d1824 97132db 2ed1d5c 97132db d2b54c3 2ed1d5c ab691f9 2ed1d5c 6c1d851 2ed1d5c 135b203 2ed1d5c 135b203 2ed1d5c 135b203 2ed1d5c 135b203 97132db 57952eb 230d404 57952eb 230d404 57952eb 230d404 57952eb 230d404 57952eb 824f4e9 230d404 57952eb 510a639 57952eb 510a639 57952eb 230d404 57952eb 230d404 57952eb 230d404 57952eb 230d404 57952eb 230d404 57952eb 230d404 57952eb 230d404 97132db d2b54c3 af5935b 97132db af5935b 97132db af5935b |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 |
# libraries
from flask import Flask, render_template, request, redirect, url_for, flash, session, send_from_directory
import os
import logging
from utility.utils import extract_text_from_images, Data_Extractor, json_to_llm_str, process_extracted_text, process_resume_data
from backup.backup import NER_Model
from paddleocr import PaddleOCR
# Configure logging
logging.basicConfig(
level=logging.INFO,
handlers=[
logging.StreamHandler() # Remove FileHandler and log only to the console
]
)
# Flask App
app = Flask(__name__)
app.secret_key = 'your_secret_key'
app.config['UPLOAD_FOLDER'] = 'uploads/'
app.config['RESULT_FOLDER'] = 'results/'
UPLOAD_FOLDER = 'static/uploads/'
RESULT_FOLDER = 'static/results/'
os.makedirs(UPLOAD_FOLDER, exist_ok=True)
os.makedirs(RESULT_FOLDER, exist_ok=True)
if not os.path.exists(app.config['UPLOAD_FOLDER']):
os.makedirs(app.config['UPLOAD_FOLDER'])
if not os.path.exists(app.config['RESULT_FOLDER']):
os.makedirs(app.config['RESULT_FOLDER'])
# Set the PaddleOCR home directory to a writable location
os.environ['PADDLEOCR_HOME'] = '/tmp/.paddleocr'
# Check if PaddleOCR home directory is writable
if not os.path.exists('/tmp/.paddleocr'):
os.makedirs('/tmp/.paddleocr', exist_ok=True)
logging.info("Created PaddleOCR home directory.")
else:
logging.info("PaddleOCR home directory exists.")
@app.route('/')
def index():
uploaded_files = session.get('uploaded_files', [])
logging.info(f"Accessed index page, uploaded files: {uploaded_files}")
return render_template('index.html', uploaded_files=uploaded_files)
@app.route('/upload', methods=['POST'])
def upload_file():
if 'files' not in request.files:
flash('No file part')
logging.warning("No file part found in the request")
return redirect(request.url)
files = request.files.getlist('files')
if not files or all(file.filename == '' for file in files):
flash('No selected files')
logging.warning("No files selected for upload")
return redirect(request.url)
uploaded_files = session.get('uploaded_files', [])
for file in files:
if file:
filename = file.filename
file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
file.save(file_path)
uploaded_files.append(filename)
logging.info(f"Uploaded file: {filename} at {file_path}")
session['uploaded_files'] = uploaded_files
flash('Files successfully uploaded')
logging.info(f"Files successfully uploaded: {uploaded_files}")
return process_file()
@app.route('/remove_file',methods=['POST'])
def remove_file():
uploaded_files = session.get('uploaded_files', [])
if uploaded_file:
for filename in uploaded_files:
file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
if os.path.exists(file_path):
os.remove(file_path)
logging.info(f"Removed file: {filename}")
else:
logging.warning(f"File not found for removal: {file_path}") # More specific log
session.pop('uploaded_files', None)
flash('Files successfully removed')
logging.info("All uploaded files removed")
else:
flash('No file to remove.')
logging.warning("File not found for removal")
return redirect(url_for('index'))
@app.route('/reset_upload')
def reset_upload():
"""Reset the uploaded file and the processed data."""
uploaded_files = session.get('uploaded_files', [])
if uploaded_file:
for filename in uploaded_files:
file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
if os.path.exists(file_path):
os.remove(file_path)
logging.info(f"Removed file: {filename}")
else:
logging.warning(f"File not found for removal: {file_path}") # More specific log
session.pop('uploaded_files', None)
flash('Files successfully removed')
logging.info("All uploaded files removed")
else:
flash('No file to remove.')
logging.warning("File not found for removal")
return redirect(url_for('index'))
@app.route('/process', methods=['GET','POST'])
def process_file():
uploaded_files = session.get('uploaded_files', [])
if not uploaded_files:
flash('No files selected for processing')
logging.warning("No files selected for processing")
return redirect(url_for('index'))
file_paths = [os.path.join(app.config['UPLOAD_FOLDER'], filename) for filename in uploaded_files]
logging.info(f"Processing files: {file_paths}")
extracted_text = {}
processed_Img = {}
try:
extracted_text, processed_Img = extract_text_from_images(file_paths)
logging.info(f"Extracted text: {extracted_text}")
logging.info(f"Processed images: {processed_Img}")
llmText = json_to_llm_str(extracted_text)
logging.info(f"LLM text: {llmText}")
LLMdata = Data_Extractor(llmText)
print("llm data--------->",llmText)
logging.info(f"LLM data: {LLMdata}")
except Exception as e:
logging.error(f"Error during LLM processing: {e}")
logging.info("Running backup model...")
LLMdata = {}
extracted_text, processed_Img = extract_text_from_images(file_paths)
logging.info(f"Extracted text(Backup): {extracted_text}")
logging.info(f"Processed images(Backup): {processed_Img}")
if extracted_text:
text = json_to_llm_str(extracted_text)
LLMdata = NER_Model(text)
logging.info(f"NER model data: {LLMdata}")
else:
logging.warning("No extracted text available for backup model")
cont_data = process_extracted_text(extracted_text)
logging.info(f"Contextual data: {cont_data}")
processed_data = process_resume_data(LLMdata, cont_data, extracted_text)
logging.info(f"Processed data: {processed_data}")
session['processed_data'] = processed_data
session['processed_Img'] = processed_Img
flash('Data processed and analyzed successfully')
logging.info("Data processed and analyzed successfully")
return redirect(url_for('result'))
@app.route('/result')
def result():
processed_data = session.get('processed_data', {})
processed_Img = session.get('processed_Img', {})
logging.info(f"Displaying results: Data - {processed_data}, Images - {processed_Img}")
return render_template('result.html', data=processed_data, Img=processed_Img)
@app.route('/uploads/<filename>')
def uploaded_file(filename):
logging.info(f"Serving file: {filename}")
return send_from_directory(app.config['UPLOAD_FOLDER'], filename)
if __name__ == '__main__':
logging.info("Starting Flask app")
app.run(debug=True)
|