Update app.py

app.py

@@ -24,9 +24,10 @@ job_description_series = pd.Series([txt], name="Text")
 st.dataframe(job_description_series)
 
 uploaded_files = st.file_uploader(
-    "Choose a PDF file(s) for candidate profiles", accept_multiple_files=True, type="pdf"
+    "Choose a PDF file(s) for candidate profiles",  type="pdf", key = "candidate 1"
 )
 
+
 all_resumes_text = []  # Store the text content of each PDF
 
 if uploaded_files:
@@ -62,9 +63,44 @@ if uploaded_files:
 
 
        
-        
+uploaded_files = st.file_uploader(
+    "Choose a PDF file(s) for candidate profiles",  type="pdf", key = "candidate 2"
+) 
         
 
             
 
+all_resumes_text = []  # Store the text content of each PDF
+
+if uploaded_files:
+    for uploaded_file in uploaded_files:
+        try:
+            pdf_reader = PdfReader(uploaded_file)
+            text_data = ""
+            for page in pdf_reader.pages:
+                text_data += page.extract_text()
+            all_resumes_text.append(text_data)
+        except Exception as e:
+            st.error(f"Error processing file {uploaded_file.name}: {e}")
+
+    if all_resumes_text:
+        all_documents = [job_description_series.iloc[0]] + all_resumes_text
+
+        vectorizer = TfidfVectorizer()
+        tfidf_matrix = vectorizer.fit_transform(all_documents)
+
+        tfidf_df = pd.DataFrame(tfidf_matrix.toarray(), columns=vectorizer.get_feature_names_out())
+        st.subheader("TF-IDF Values:")
+        st.dataframe(tfidf_df)
+
+        cosine_sim_matrix = cosine_similarity(tfidf_matrix)
+        cosine_sim_df = pd.DataFrame(cosine_sim_matrix)
+        st.subheader("Cosine Similarity Matrix:")
+        st.dataframe(cosine_sim_df)
+
+        # Display similarity scores between the job description and each resume
+        st.subheader("Cosine Similarity Scores (Job Description vs. Resumes):")
+        for i, similarity_score in enumerate(cosine_sim_matrix[0][1:]):
+            st.write(f"Similarity with Candidate Profile {i + 1}: {similarity_score:.4f}")
+