Update app.py

app.py

@@ -6,7 +6,6 @@ from llama_index.core import VectorStoreIndex
 from llama_index.embeddings.openai import OpenAIEmbedding
 from llama_index.llms.openai import OpenAI
 
-# Load OpenAI API Key
 openai.api_key = os.environ.get("OPENAI_API_KEY")
 
 def process_pdf(file, question):
@@ -26,27 +25,27 @@ def process_pdf(file, question):
     except Exception as e:
         return f"❌ Error: {e}"
 
-# Launch dark-themed UI with Gradio Blocks
-with gr.Blocks(theme=gr.themes.Soft(primary_hue="gray", secondary_hue="purple"), css="footer {display:none !important;}") as demo:
-    gr.HTML("""
-    <div style="text-align: center; padding: 2rem;">
-        <h1 style="font-size: 2.4rem; color: #ffffff;">🧠 Resume Insight AI</h1>
-        <p style="color: #cccccc;">Upload your resume and get instant AI insights powered by OpenAI + LlamaIndex</p>
-    </div>
+# Gradio Blocks UI
+with gr.Blocks(title="Resume Analyzer by Advaith") as demo:
+    gr.Markdown("""
+    # 📄 Resume Analyzer
+    Upload a resume and ask any question about the candidate!  
+    Powered by **LlamaIndex** + **OpenAI**
     """)
 
-    with gr.Box():
-        with gr.Row():
-            pdf_file = gr.File(label="📎 Upload PDF Resume", file_types=[".pdf"], type="file")
-            question = gr.Textbox(label="💬 Ask a Question", placeholder="e.g., What are my key skills?", lines=1)
+    with gr.Row():
+        pdf_file = gr.File(label="📁 Upload your resume (PDF)", file_types=[".pdf"])
+        question = gr.Textbox(lines=2, label="💬 Ask something", placeholder="e.g., What are the candidate's technical strengths?")
 
-        with gr.Row():
-            submit_btn = gr.Button("🔍 Analyze Resume", size="lg")
+    analyze_button = gr.Button("🔍 Analyze")
 
-        output = gr.Textbox(label="📘 AI Response", lines=10, interactive=False)
+    result = gr.Textbox(label="🧠 Answer", lines=10)
 
-    submit_btn.click(fn=process_pdf, inputs=[pdf_file, question], outputs=output)
+    def run_analysis(file, question):
+        return process_pdf(file, question)
 
-# Start the app
+    analyze_button.click(run_analysis, inputs=[pdf_file, question], outputs=result)
+
+# Launch app
 if __name__ == "__main__":
     demo.launch()