sss

app.py

@@ -2,7 +2,6 @@ import streamlit as st
 import pdfplumber
 import io
 import spacy
-from docx import Document
 from transformers import pipeline
 
 st.set_page_config(
@@ -47,13 +46,6 @@ def extract_text_from_pdf(pdf_file):
             text += page.extract_text() or ""
     return text
 
-def extract_text_from_docx(docx_file):
-    doc = Document(docx_file)
-    text = ""
-    for paragraph in doc.paragraphs:
-        text += paragraph.text + "\n"
-    return text
-
 def analyze_resume(text, job_title):
     # Extract relevant skills
     doc = nlp(text.lower())
@@ -89,7 +81,7 @@ col1, col2 = st.columns([2, 1])
 
 with col1:
     # File upload
-    uploaded_file = st.file_uploader("Upload Resume (PDF or DOCX)", type=["pdf", "docx"])
+    uploaded_file = st.file_uploader("Upload Resume (PDF)", type=["pdf"])
 
 with col2:
     # Job selection
@@ -104,11 +96,8 @@ if uploaded_file and job_title:
     try:
         # Show spinner while processing
         with st.spinner("Analyzing resume..."):
-            # Extract text based on file type
-            if uploaded_file.type == "application/pdf":
-                text = extract_text_from_pdf(uploaded_file)
-            else:
-                text = extract_text_from_docx(uploaded_file)
+            # Extract text from PDF
+            text = extract_text_from_pdf(uploaded_file)
             
             # Analyze resume
             found_skills, summary = analyze_resume(text, job_title)

requirements.txt

@@ -1,6 +1,5 @@
 streamlit>=1.31.0
 pdfplumber>=0.10.3
-python-docx>=1.1.0
 transformers>=4.37.2
 spacy>=3.7.2
 https://huggingface.co/spacy/en_core_web_sm/resolve/main/en_core_web_sm-any-py3-none-any.whl