Update app.py

app.py

@@ -55,80 +55,17 @@ match_agent = Agent(
     llm=llm
 )
 
-# Streamlit UI
 st.title("🔍 AI-Powered ATS Scanner")
 
-# Sidebar navigation
-menu = st.sidebar.radio("Select Process", ["1️⃣ Extract Resume Keywords", "2️⃣ Analyze JD", "3️⃣ ATS Match Score"])
+st.subheader("⚙️ Resume & JD Match Analysis")
+resume_files = st.file_uploader("Upload Resumes (PDF/DOC)", type=["pdf", "docx"], accept_multiple_files=True, key="match_resume")
+job_description = st.text_area("Paste Job Description", key="match_jd")
 
-if menu == "1️⃣ Extract Resume Keywords":
-    st.subheader("📄 Resume Keyword Extractor")
-    resume_file = st.file_uploader("Upload Resume (PDF/DOC)", type=["pdf", "docx"])
-    if st.button("Extract Keywords"):
-        if resume_file:
-            resume_text = extract_text_from_file(resume_file)
-
-            task_resume = Task(
-                description=f"""Given the following resume text:\n\n{resume_text}\n\n
-                        Extract ONLY technical skills, programming languages, tools, domain-specific keywords, and certifications.
-                        DO NOT include soft skills, personality traits, or general qualities.
-                        Provide the output as a clean comma-separated list of keywords.""",
-                agent=resume_agent,
-                expected_output="List of keywords, technical skills, tools, programming languages, and certifications mentioned in the resume."
-            )
-
-            crew = Crew(
-                agents=[resume_agent],
-                tasks=[task_resume],
-                verbose=True
-            )
+if st.button("Analyze Match"):
+    if resume_files and job_description:
+        results = []
 
-            result = crew.kickoff(inputs={"resume_text": resume_text})
-            extracted_keywords = result.tasks_output[0].raw
-            st.write("### ✅ Extracted Resume Keywords and Skills:")
-            skills = extracted_keywords.split("\n")
-            for skill in skills:
-                if skill.strip():
-                    st.write(f"- {skill.strip()}")
-        else:
-            st.warning("Please upload a resume file.")
-
-elif menu == "2️⃣ Analyze JD":
-    st.subheader("📝 Job Description Analyzer")
-    job_description = st.text_area("Paste Job Description")
-    if st.button("Analyze JD"):
-        if job_description:
-            task_jd = Task(
-                description=f"""Given the following Job Description:\n\n{job_description}\n\n
-                    Extract ONLY technical skills, programming languages, tools, domain-specific keywords, and certifications mentioned.
-                    DO NOT include soft skills like 'communication skills', 'time management', or general traits.
-                    Provide the output as a clean, comma-separated list of technical and domain-specific skills.""",
-                agent=jd_agent,
-                expected_output="List of keywords, technical skills, tools, programming languages and domain-specific skills"
-            )
-
-            crew = Crew(
-                agents=[jd_agent],
-                tasks=[task_jd],
-                verbose=True
-            )
-
-            result = crew.kickoff(inputs={"job_description": job_description})
-            extracted_keywords = result.tasks_output[0].raw
-            st.write("### ✅ Extracted JD Keywords:")
-            skills = extracted_keywords.split("\n")
-            for skill in skills:
-                if skill.strip():
-                    st.write(f"- {skill.strip()}")
-        else:
-            st.warning("Please paste a job description.")
-
-elif menu == "3️⃣ ATS Match Score":
-    st.subheader("⚙️ Resume & JD Match Analysis")
-    resume_file = st.file_uploader("Upload Resume (PDF/DOC)", type=["pdf", "docx"], key="match_resume")
-    job_description = st.text_area("Paste Job Description", key="match_jd")
-    if st.button("Analyze Match"):
-        if resume_file and job_description:
+        for resume_file in resume_files:
             resume_text = extract_text_from_file(resume_file)
 
             task_match = Task(
@@ -149,20 +86,32 @@ elif menu == "3️⃣ ATS Match Score":
             crew = Crew(
                 agents=[match_agent],
                 tasks=[task_match],
-                verbose=True
+                verbose=False
             )
 
             result = crew.kickoff(inputs={"resume_text": resume_text, "job_description": job_description})
             extracted_keywords = result.tasks_output[0].raw
-                    
-            # Then parse extracted_keywords
-            match_score_line = next((line for line in extracted_keywords.split('\n') if "Match Score" in line), None)
-            missing_keywords_line = next((line for line in extracted_keywords.split('\n') if "Missing Keywords" in line), None)
-            st.success("✅ ATS Match Result:")
-            st.markdown(f"**{match_score_line.strip()}**")
-            st.markdown(f"**{missing_keywords_line.strip()}**")
-
-        else:
-            st.warning("Please upload resume and paste job description.")
-else:
-    st.warning("Invalid Input")
+
+            # Parse result
+            match_score_line = next((line for line in extracted_keywords.split('\n') if "Match Score" in line), "")
+            missing_keywords_line = next((line for line in extracted_keywords.split('\n') if "Missing Keywords" in line), "")
+
+            try:
+                score = int(match_score_line.split(":")[1].strip().replace("%", ""))
+            except:
+                score = 0
+
+            results.append({
+                "Resume": resume_file.name,
+                "Match Score (%)": score,
+                "Missing Keywords": missing_keywords_line.split(":", 1)[-1].strip()
+            })
+
+        # Sort by Match Score descending
+        results_sorted = sorted(results, key=lambda x: x["Match Score (%)"], reverse=True)
+
+        st.success("✅ ATS Match Results Table")
+        st.dataframe(results_sorted)
+
+    else:
+        st.warning("Please upload at least one resume and paste the job description.")