Update app.py

app.py

@@ -2,7 +2,6 @@ import streamlit as st
 from docx import Document
 import PyPDF2
 import google.generativeai as genai  # Correct package for Gemini
-import re  # For output validation
 
 # Title of the app
 st.title("JD-Resume Fit Check App")
@@ -21,18 +20,22 @@ with col1:
     st.subheader('Upload your Resume')
     uploaded_file = st.file_uploader('Upload your Resume (PDF or DOCX)', type=['pdf', 'docx'])
     resume_text = ""
-    if uploaded_file is not None:
-        if uploaded_file.type == 'application/pdf':
-            # Extract text from PDF
-            pdf_reader = PyPDF2.PdfReader(uploaded_file)
-            for page in pdf_reader.pages:
-                resume_text += page.extract_text()
-            st.success("Resume uploaded and processed!")
-        elif uploaded_file.type == 'application/vnd.openxmlformats-officedocument.wordprocessingml.document':
-            # Extract text from DOCX
-            doc = Document(uploaded_file)
-            resume_text = '\n'.join([paragraph.text for paragraph in doc.paragraphs])
-            st.success("Resume uploaded and processed!")
+
+    try:
+        if uploaded_file:
+            if uploaded_file.type == 'application/pdf':
+                pdf_reader = PyPDF2.PdfReader(uploaded_file)
+                for page in pdf_reader.pages:
+                    text = page.extract_text()
+                    if text:
+                        resume_text += text
+                st.success("Resume uploaded and processed!")
+            elif uploaded_file.type == 'application/vnd.openxmlformats-officedocument.wordprocessingml.document':
+                doc = Document(uploaded_file)
+                resume_text = '\n'.join([paragraph.text for paragraph in doc.paragraphs if paragraph.text])
+                st.success("Resume uploaded and processed!")
+    except Exception as e:
+        st.error(f"Error processing file: {e}")
 
 # Right column: JD input
 with col2:
@@ -54,8 +57,9 @@ if resume_text and job_description:
     # Truncate input if too large
     max_input_tokens = 4000  # Example limit
     combined_input = f"{resume_text}\n{job_description}"
-    if len(combined_input.split()) > max_input_tokens:
-        combined_input = ' '.join(combined_input.split()[:max_input_tokens])
+    words = combined_input.split()
+    if len(words) > max_input_tokens:
+        combined_input = ' '.join(words[:max_input_tokens])
         st.warning("Input text truncated to fit the model's token limit.")
 
     # Display a "Generate" button
@@ -64,13 +68,14 @@ if resume_text and job_description:
 
         # Construct the prompt for analysis
         prompt = f"""
-        You are an expert recruiter and hiring manager assistant. Analyze the following details and strictly provide the response in the specified format:
+        You are an expert recruiter and hiring manager assistant. Analyze the following details and provide a structured response in the specified format:
 
-        ### Input:
         1. Resume: {resume_text}
+
         2. Job Description: {job_description}
 
         ### Tasks:
+
         1. Identify the key skills, experiences, and qualifications mentioned in the Job Description.
         2. Compare the above with the details provided in the Resume.
         3. Provide a match score (out of 10) based on how well the Resume aligns with the Job Description.
@@ -79,23 +84,17 @@ if resume_text and job_description:
         6. Recommend relevant topics for interview preparation based on the Job Description.
 
         ### Response Format:
-        1. **Match Score:** [Provide a score out of 10]
-        2. **Justification:** [Detailed analysis of how well the resume matches the job description]
-        3. **Resume Suggestions:** [Actionable changes to align the resume with the job description]
-        4. **Interview Preparation Topics:** [Relevant topics for interview preparation]
-
-        Example:
-        1. **Match Score:** 8/10
-        2. **Justification:** The resume covers 80% of the key skills but lacks specific cloud experience.
-        3. **Resume Suggestions:** Add certifications in cloud platforms and mention specific cloud-related projects.
-        4. **Interview Preparation Topics:** Cloud computing, project management, and teamwork.
+        1. Match Score: [Provide a score out of 10]
+        2. Justification: [Provide a detailed analysis of how well the resume matches the job description]
+        3. Resume Suggestions: [List actionable changes to align the resume with the job description]
+        4. Interview Preparation Topics: [List relevant topics for interview preparation]
         """
 
         try:
-            # Initialize the Generative Model
-            #model = genai.GenerativeModel(model='gemini-pro')
+            # Initialize the generative model
             model = genai.GenerativeModel("gemini-pro")
-            
+
+            # Generate content using the Gemini API
             response = model.generate_content(
                         prompt,
                         generation_config=genai.types.GenerationConfig(
@@ -106,14 +105,9 @@ if resume_text and job_description:
                     )
 
 
-            # Validate and enforce format consistency
-            expected_format = r"(1\. \*\*Match Score:\*\* .+\n2\. \*\*Justification:\*\* .+\n3\. \*\*Resume Suggestions:\*\* .+\n4\. \*\*Interview Preparation Topics:\*\* .+)"
+            # Ensure response contains text
             if response and hasattr(response, "text"):
-                output_text = response.text
-                if re.match(expected_format, output_text):
-                    st.write(output_text)  # Display the generated response
-                else:
-                    st.error("The response does not match the expected format. Please try again.")
+                st.write(response.text)  # Display the generated response
             else:
                 st.error("No response received from the API.")