Update app.py

app.py

@@ -7,22 +7,33 @@ import numpy as np
 from scipy.spatial.distance import cosine
 import time
 
-# Set page title
-st.set_page_config(page_title="Resume Analyzer and Company Suitability Checker")
+# Set page title and hide sidebar
+st.set_page_config(
+    page_title="Resume Analyzer and Company Suitability Checker",
+    initial_sidebar_state="collapsed"
+)
+
+# Hide sidebar completely with custom CSS
+st.markdown("""
+<style>
+    [data-testid="collapsedControl"] {display: none;}
+    section[data-testid="stSidebar"] {display: none;}
+</style>
+""", unsafe_allow_html=True)
 
 #####################################
 # Preload Models
 #####################################
 @st.cache_resource(show_spinner=True)
-def load_models(summarization_model="google/pegasus-xsum", similarity_model="sentence-transformers/all-MiniLM-L6-v2"):
+def load_models():
     """Load models at startup"""
     with st.spinner("Loading AI models... This may take a minute on first run."):
         models = {}
         # Load summarization model
-        models['summarizer'] = pipeline("summarization", model=summarization_model)
+        models['summarizer'] = pipeline("summarization", model="google/pegasus-xsum")
         
         # Load feature extraction model for similarity
-        models['feature_extractor'] = pipeline("feature-extraction", model=similarity_model)
+        models['feature_extractor'] = pipeline("feature-extraction", model="bert-base-uncased")
         
         return models
 
@@ -139,31 +150,6 @@ company_prompt = st.text_area(
     help="Enter a detailed description of the company culture, role requirements, and desired skills.",
 )
 
-# Show model selection in sidebar
-st.sidebar.header("Model Settings")
-
-# Model dropdowns - we're now only allowing one model of each type to be selected
-summarization_model = st.sidebar.selectbox(
-    "Summarization Model",
-    ["google/pegasus-xsum", "facebook/bart-large-cnn", "t5-small", "sshleifer/distilbart-cnn-12-6"],
-    index=0,
-    help="Select the model to use for summarizing the resume text."
-)
-
-similarity_model = st.sidebar.selectbox(
-    "Similarity Model",
-    ["sentence-transformers/all-MiniLM-L6-v2", "sentence-transformers/all-mpnet-base-v2", 
-     "sentence-transformers/paraphrase-MiniLM-L3-v2", "sentence-transformers/multi-qa-mpnet-base-dot-v1"],
-    index=0,
-    help="Select the model to use for comparing candidate summary with company profile."
-)
-
-# Reload models if changed
-if st.sidebar.button("Reload Models"):
-    st.cache_resource.clear()
-    models = load_models(summarization_model, similarity_model)
-    st.sidebar.success("Models reloaded successfully!")
-
 # Process button
 if uploaded_file is not None and company_prompt and st.button("Analyze Resume"):
     with st.spinner("Processing..."):
@@ -173,10 +159,6 @@ if uploaded_file is not None and company_prompt and st.button("Analyze Resume"):
         if resume_text.startswith("Error") or resume_text == "Unsupported file type. Please upload a .docx or .txt file.":
             st.error(resume_text)
         else:
-            # Display extracted text
-            with st.expander("Extracted Text"):
-                st.text(resume_text)
-            
             # Generate summary
             summary, summarization_time = summarize_resume_text(resume_text, models)