Update app.py

app.py

@@ -82,13 +82,19 @@ def extract_basic_resume_info(text):
 
     # Extract Job Experience using the "experience" section.
     # Capture everything after the word "experience" until a new section or the end.
-    experience_match = re.search(r"experience\s*(.*?)(?:\n\s*\n|additional information|skills|education|$)", text, re.IGNORECASE | re.DOTALL)
+    experience_match = re.search(
+        r"experience\s*(.*?)(?:\n\s*\n|additional information|skills|education|$)",
+        text,
+        re.IGNORECASE | re.DOTALL,
+    )
     if experience_match:
         job_experience = experience_match.group(1).strip()
         info["Job Experience"] = " ".join(job_experience.split())
     else:
         # Fallback if not a labeled section.
-        exp_match = re.search(r"(\d+)\s+(years|yrs)\s+(?:of\s+)?experience", text, re.IGNORECASE)
+        exp_match = re.search(
+            r"(\d+)\s+(years|yrs)\s+(?:of\s+)?experience", text, re.IGNORECASE
+        )
         if exp_match:
             info["Job Experience"] = f"{exp_match.group(1)} {exp_match.group(2)}"
 
@@ -99,7 +105,9 @@ def extract_basic_resume_info(text):
         info["Skills"] = skills_str.rstrip(".")
 
     # Extract Education (e.g., "Education: ...")
-    edu_match = re.search(r"education\s*(.*?)(?:\n\s*\n|experience|$)", text, re.IGNORECASE | re.DOTALL)
+    edu_match = re.search(
+        r"education\s*(.*?)(?:\n\s*\n|experience|$)", text, re.IGNORECASE | re.DOTALL
+    )
     if edu_match:
         education_block = edu_match.group(1).strip()
         info["Education"] = " ".join(education_block.split())
@@ -158,8 +166,6 @@ def compute_suitability(candidate_summary, company_prompt, model):
 # Main Resume Processing Logic
 #####################################
 def process_resume(file_obj):
-    if file_obj is None:
-        return None
     resume_text = extract_text_from_file(file_obj)
     basic_info = extract_basic_resume_info(resume_text)
     summary_paragraph = summarize_basic_info(basic_info)
@@ -178,39 +184,56 @@ model = load_model()
 # Streamlit Interface
 #####################################
 st.title("Resume Analyzer and Company Suitability Checker")
-st.markdown("""
-Upload your resume file in **.doc** or **.docx** format. The app extracts key details (such as name, age, job experience, skills, 
-and education) and summarizes them into a single paragraph. It then compares the candidate summary with the company profile
+st.markdown(
+    """
+Upload your resume file in **.doc** or **.docx** format. The app extracts key details such as name, age, job experience, skills, 
+and education, and summarizes them into a single paragraph. Then, it compares the candidate summary with a company profile
 (using a pre-defined prompt for Google LLC) to produce a suitability score.
-""")
+"""
+)
 
+# File uploader for resume
 uploaded_file = st.file_uploader("Upload Resume", type=["doc", "docx"])
 
+# Button to process the resume and store the summary in session state.
 if st.button("Process Resume"):
     if uploaded_file is None:
-        st.error("Please upload a file first.")
+        st.error("Please upload a resume file first.")
     else:
         with st.spinner("Processing resume..."):
-            summary_paragraph = process_resume(uploaded_file)
-
+            candidate_summary = process_resume(uploaded_file)
+            st.session_state["candidate_summary"] = candidate_summary
         st.subheader("Candidate Summary")
-        st.markdown(summary_paragraph)
-
-        st.subheader("Company Information (Prompt)")
-        default_company_prompt = (
-            "Google LLC, a global leader in technology and innovation, specializes in internet services, cloud computing, "
-            "artificial intelligence, and software development. As part of Alphabet Inc., Google seeks candidates with strong "
-            "problem-solving skills, adaptability, and collaboration abilities. Technical roles require proficiency in programming "
-            "languages such as Python, Java, C++, Go, or JavaScript, with expertise in data structures, algorithms, and system design. "
-            "Additionally, skills in AI, cybersecurity, UX/UI design, and digital marketing are highly valued. Google fosters a culture "
-            "of innovation, expecting candidates to demonstrate creativity, analytical thinking, and a passion for cutting-edge technology."
-        )
-        company_prompt = st.text_area("Enter company details:", value=default_company_prompt, height=150)
-
-        if st.button("Compute Suitability Score"):
-            if not company_prompt.strip():
-                st.error("Please enter the company information.")
-            else:
-                with st.spinner("Computing suitability score..."):
-                    score = compute_suitability(summary_paragraph, company_prompt, model)
-                st.success(f"Suitability Score: {score:.2f} (range 0 to 1)")
+        st.markdown(candidate_summary)
+
+# Pre-define the company prompt for Google LLC.
+default_company_prompt = (
+    "Google LLC, a global leader in technology and innovation, specializes in internet services, cloud computing, "
+    "artificial intelligence, and software development. As part of Alphabet Inc., Google seeks candidates with strong "
+    "problem-solving skills, adaptability, and collaboration abilities. Technical roles require proficiency in programming "
+    "languages such as Python, Java, C++, Go, or JavaScript, with expertise in data structures, algorithms, and system design. "
+    "Additionally, skills in AI, cybersecurity, UX/UI design, and digital marketing are highly valued. Google fosters a culture "
+    "of innovation, expecting candidates to demonstrate creativity, analytical thinking, and a passion for cutting-edge technology."
+)
+
+# Company prompt text area.
+company_prompt = st.text_area(
+    "Enter company details:",
+    value=default_company_prompt,
+    height=150,
+)
+
+# Button to compute the suitability score.
+if st.button("Compute Suitability Score"):
+    if "candidate_summary" not in st.session_state:
+        st.error("Please process the resume first!")
+    else:
+        candidate_summary = st.session_state["candidate_summary"]
+        if candidate_summary.strip() == "":
+            st.error("Candidate summary is empty; please check your resume file.")
+        elif company_prompt.strip() == "":
+            st.error("Please enter the company information.")
+        else:
+            with st.spinner("Computing suitability score..."):
+                score = compute_suitability(candidate_summary, company_prompt, model)
+            st.success(f"Suitability Score: {score:.2f} (range 0 to 1)")