Update app.py

app.py

@@ -1,51 +1,49 @@
-import streamlit as st
-import easyocr
-from langchain_google_genai import GoogleGenerativeAIEmbeddings
-import os
-from dotenv import load_dotenv
-from sklearn.metrics.pairwise import cosine_similarity
-import numpy as np
-import cv2
-import PyPDF2
-
-load_dotenv()
-
-st.title('Resume Shortlist Applications')
-
-file_input_resume = st.file_uploader('Enter your resume file', type=['png', 'jpg', 'jpeg', 'pdf'])
-text_file_input_resume = st.file_uploader('Enter your job descriptions', type=['txt'])
-
-def extract_text_easyocr(image_bytes):
-    nparr = np.frombuffer(image_bytes, np.uint8)
-    img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-    reader = easyocr.Reader(['en'])
-    result = reader.readtext(img, detail=0)
-    return "\n".join(result)
-
-def text_loader(file):
-    return file.read().decode('utf-8')
-
-if file_input_resume and text_file_input_resume:
-    if file_input_resume.type in ['image/png', 'image/jpeg', 'image/jpg']:
-        image_bytes = file_input_resume.read()
-        text = extract_text_easyocr(image_bytes)
-    elif file_input_resume.type == 'application/pdf':
-        pdf_reader = PyPDF2.PdfReader(file_input_resume)
-        text = "\n".join([page.extract_text() for page in pdf_reader.pages if page.extract_text()])
-    else:
-        st.error("Unsupported file format for resume.")
-        st.stop()
-    
-    text_job_descriptions = text_loader(text_file_input_resume)
-    GOOGLE_API_KEY = os.environ.get('GOOGLE_API_KEY')
-    os.environ['GOOGLE_API_KEY'] = GOOGLE_API_KEY
-    embeddings = GoogleGenerativeAIEmbeddings(model='models/embedding-001')
-    vector_resume_text = embeddings.embed_query(text)
-    vector_job_description = embeddings.embed_query(text_job_descriptions)
-    
-    def calculate_similarity(vector1, vector2):
-        return (cosine_similarity([vector1], [vector2])[0][0] * 100)
-    
-    if st.button('Check your Score'):
-        similarity = calculate_similarity(vector_resume_text, vector_job_description)
-        st.write(f'The similarity between your resume and job descriptions is {similarity:.2f}%')
+import streamlit as st
+import easyocr
+from langchain_google_genai import GoogleGenerativeAIEmbeddings
+import os
+from dotenv import load_dotenv
+from sklearn.metrics.pairwise import cosine_similarity
+import numpy as np
+import cv2
+import PyPDF2
+
+load_dotenv()
+
+st.title('Resume Shortlist Applications')
+
+file_input_resume = st.file_uploader('Enter your resume file', type=['png', 'jpg', 'jpeg', 'pdf'])
+text_file_input_resume = st.file_uploader('Enter your job descriptions', type=['txt'])
+def extract_text_easyocr(image_bytes):
+    nparr = np.frombuffer(image_bytes, np.uint8)
+    img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+    reader = easyocr.Reader(['en'])
+    result = reader.readtext(img, detail=0)
+    return "\n".join(result)
+
+def text_loader(file):
+    return file.read().decode('utf-8')
+
+GOOGLE_API_KEY = os.environ.get('GOOGLE_API_KEY')
+os.environ['GOOGLE_API_KEY'] = GOOGLE_API_KEY
+embeddings = GoogleGenerativeAIEmbeddings(model='models/embedding-001')
+    
+def calculate_similarity(vector1, vector2):
+    return (cosine_similarity([vector1], [vector2])[0][0] * 100)
+    
+if st.button('Check your Score'):
+    text_job_descriptions = text_loader(text_file_input_resume)
+    if file_input_resume and text_file_input_resume:
+        if file_input_resume.type in ['image/png', 'image/jpeg', 'image/jpg']:
+            image_bytes = file_input_resume.read()
+            text = extract_text_easyocr(image_bytes)
+        elif file_input_resume.type == 'application/pdf':
+            pdf_reader = PyPDF2.PdfReader(file_input_resume)
+            text = "\n".join([page.extract_text() for page in pdf_reader.pages if page.extract_text()])
+        else:
+            st.error("Unsupported file format for resume.")
+            st.stop()
+    vector_resume_text = embeddings.embed_query(text)
+    vector_job_description = embeddings.embed_query(text_job_descriptions)
+    similarity = calculate_similarity(vector_resume_text, vector_job_description)
+    st.write(f'The similarity between your resume and job descriptions is {similarity:.2f}%')