Update app.py

app.py

@@ -41,7 +41,7 @@ def load_models():
         # Load T5-small model for evaluation
         models['evaluator'] = pipeline(
             "text2text-generation", 
-            model="google-t5/t5-small",
+            model="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
             max_length=200
         )
         
@@ -398,10 +398,10 @@ Score: {score_percent}/100
 st.title("Google Resume Match Analyzer")
 st.markdown(
     """
-Upload your resume file in **.docx**, **.doc**, or **.txt** format to see how well you match with Google's hiring requirements. The app performs the following tasks:
-1. Extracts text from your resume.
+Upload your resume file in **.docx**, **.doc**, or **.txt** format to see how well the candidate matchs with Google's hiring requirements. The app performs the following tasks:
+1. Extracts text from candidate's resume.
 2. Uses AI to generate a structured candidate summary.
-3. Evaluates your fit for Google, providing a match score and specific feedback.
+3. Evaluates whether candidates fit for Google or not, providing a match score and specific feedback.
 """
 )
 
@@ -413,7 +413,7 @@ with st.expander("Google's Requirements", expanded=False):
 uploaded_file = st.file_uploader("Upload your resume (.docx, .doc, or .txt)", type=["docx", "doc", "txt"])
 
 # Process button with optimized flow
-if uploaded_file is not None and st.button("Analyze My Google Fit"):
+if uploaded_file is not None and st.button("Analyze Google Fit"):
     # Create a placeholder for the progress bar
     progress_bar = st.progress(0)
     status_text = st.empty()
@@ -432,7 +432,7 @@ if uploaded_file is not None and st.button("Analyze My Google Fit"):
         progress_bar.progress(75)
         
         # Display summary
-        st.subheader("Your Resume Summary")
+        st.subheader("Candidate Resume Summary")
         st.markdown(summary)
         st.info(f"Summary generated in {summarization_time:.2f} seconds")