Update app.py

app.py

@@ -1,13 +1,9 @@
-# app.py
-
-import os
 import gradio as gr
 from text_extractor import extract_text_from_file
 from embedder import get_embeddings
 from vector_store import create_faiss_index, search_similar_cvs
 from groq_api import summarize_match
 
-# Global state
 cv_texts = []
 cv_names = []
 cv_vectors = []
@@ -15,86 +11,63 @@ faiss_index = None
 
 def upload_cvs(files):
     global cv_texts, cv_names, cv_vectors, faiss_index
+
     try:
-        cv_texts = [extract_text_from_file(f.name) for f in files]
+        cv_texts = [extract_text_from_file(f) for f in files]
         cv_names = [f.name for f in files]
         cv_vectors = get_embeddings(cv_texts)
 
-        import numpy as np
-        if cv_vectors is None or np.array(cv_vectors).size == 0:
-            return "❌ No valid CVs extracted or embedded."
+        if not cv_vectors:
+            return "❌ No valid CVs."
 
         faiss_index = create_faiss_index(cv_vectors)
         return f"✅ Uploaded and indexed {len(files)} CVs."
+
     except Exception as e:
         return f"❌ Error during upload: {e}"
 
 def match_jd(jd_text):
-    global faiss_index
-    try:
-        if not faiss_index:
-            return "❌ Please upload CVs first."
-        if not jd_text.strip():
-            return "❌ Job description is empty."
-
-        jd_vector = get_embeddings([jd_text])[0]
-        top_k_indices = search_similar_cvs(jd_vector, faiss_index, k=3)
-
-        import os
-        matched_names = [os.path.basename(cv_names[i]) for i in top_k_indices]
-        matched_texts = [
-            cv_texts[i][:500] if cv_texts[i].strip() else "[No CV content]"
-            for i in top_k_indices
-        ]
-
-        summary = summarize_match(jd_text, matched_names, matched_texts)
-        return f"""
-✅ <span style='color:#16a34a; font-weight:bold;'>Top Matches:</span><br>{matched_names}<br><br>
-📝 <span style='color:#3b82f6; font-weight:bold;'>Summary:</span><br>{summary}
-"""
-    except Exception as e:
-        return f"<span style='color:red;'>❌ Error during matching: {e}</span>"
+    if not faiss_index:
+        return "❌ Please upload CVs first."
+    if not jd_text.strip():
+        return "⚠️ Job description is empty."
+
+    jd_vector = get_embeddings([jd_text])[0]
+    indices = search_similar_cvs(jd_vector, faiss_index, k=3)
+
+    matched = [cv_names[i] for i in indices]
+    texts = [cv_texts[i][:400] for i in indices]
+
+    summary = summarize_match(jd_text, matched, texts)
+
+    return f"✅ Top Matches:\n{matched}\n\n📝 Summary:\n{summary}"
 
 def clear_data():
     global cv_texts, cv_names, cv_vectors, faiss_index
     cv_texts, cv_names, cv_vectors, faiss_index = [], [], [], None
-    return "🧹 All data cleared. You can now start fresh."
-
-# ======================
-# TABBED PROFESSIONAL UI
-# ======================
-with gr.Blocks(css="""
-    .gr-button { background-color: #2563eb; color: white; font-weight: bold; }
-    .gr-button:hover { background-color: #1d4ed8; }
-    textarea, input[type='file'] { border: 2px solid #3b82f6 !important; }
-    .gr-textbox label { color: #111827; font-weight: 600; }
-""") as upload_tab:
-    gr.Markdown("## 📤 Upload CVs")
-    gr.Markdown("Upload candidate CVs in PDF or DOCX format.")
-    cv_upload = gr.File(label="Upload CVs", file_types=[".pdf", ".docx"], file_count="multiple")
-    upload_button = gr.Button("📁 Upload & Index CVs")
-    upload_status = gr.Textbox(label="Status", interactive=False)
-    upload_button.click(upload_cvs, inputs=[cv_upload], outputs=[upload_status])
-
-with gr.Blocks() as match_tab:
-    gr.Markdown("## 📋 Match Job Description to CVs")
-    jd_input = gr.Textbox(label="Paste Job Description", lines=8, placeholder="e.g. Looking for a Python Data Analyst...")
-    match_button = gr.Button("🔍 Match CVs")
-    match_result = gr.HTML()
-    match_button.click(match_jd, inputs=[jd_input], outputs=[match_result])
-
-with gr.Blocks() as reset_tab:
-    gr.Markdown("## 🧹 Clear All Data")
-    gr.Markdown("Click below to reset the app and upload new CVs.")
-    clear_button = gr.Button("Reset App")
-    clear_output = gr.Textbox(label="Reset Status", interactive=False)
-    clear_button.click(clear_data, inputs=[], outputs=[clear_output])
-
-# Menu Bar Style Tabs
-app = gr.TabbedInterface(
-    interface_list=[upload_tab, match_tab, reset_tab],
-    tab_names=["📤 Upload CVs", "📋 Match JD", "🧹 Reset"]
-)
-
-if __name__ == "__main__":
-    app.launch()
+    return "🧹 Cleared."
+
+with gr.Blocks(css=".gr-box {max-width: none !important;}") as app:
+    gr.Markdown("# 📄 CV Matcher with Groq API")
+
+    with gr.Box():
+        gr.Markdown("## 📤 Upload CVs")
+        file_input = gr.File(file_types=[".pdf", ".docx"], file_count="multiple", label="Select CVs")
+        upload_btn = gr.Button("📁 Upload & Index")
+        upload_output = gr.Textbox(label="Status")
+
+    with gr.Box():
+        gr.Markdown("## 📋 Match Job Description")
+        jd_input = gr.Textbox(label="Paste Job Description", lines=8, max_lines=12)
+        match_btn = gr.Button("🔍 Match CVs")
+        result_output = gr.Textbox(label="Results", lines=12, interactive=False)
+
+    with gr.Row():
+        clear_btn = gr.Button("🧹 Clear All")
+        clear_output = gr.Textbox(label="Status")
+
+    upload_btn.click(upload_cvs, inputs=[file_input], outputs=[upload_output])
+    match_btn.click(match_jd, inputs=[jd_input], outputs=[result_output])
+    clear_btn.click(clear_data, inputs=[], outputs=[clear_output])
+
+app.launch()