Update app.py

app.py

@@ -8,10 +8,10 @@ from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.chains import RetrievalQA
 from tempfile import NamedTemporaryFile
 
-# Load Groq API Key securely (for Hugging Face secrets)
+# Load Groq API Key securely
 os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY")
 
-# Helper to process uploaded PDFs and build vectorstore
+# Function to process PDFs
 def process_pdfs(files):
     all_docs = []
     for file in files:
@@ -31,32 +31,34 @@ def process_pdfs(files):
     qa_chain = RetrievalQA.from_chain_type(llm=llm, retriever=retriever)
     return qa_chain
 
-# Global chain (reset with new uploads)
+# Global variable
 qa_chain = None
 
-# Upload + Process PDFs
+# Upload handler
 def upload_pdfs(files):
     global qa_chain
     qa_chain = process_pdfs(files)
     return "✅ PDFs uploaded and processed. Now ask your questions."
 
-# Ask a question
+# Question handler
 def ask_question(query):
     if qa_chain is None:
         return "❌ Please upload Kaggle notebooks/competition PDFs first."
-    result = qa_chain.run(query)
-    return result
-
-# Gradio UI
-upload = gr.File(file_types=[".pdf"], file_count="multiple", label="Upload Kaggle PDFs")
-btn_upload = gr.Button("Process PDFs")
-question = gr.Textbox(label="Ask a question about uploaded notebooks")
-answer = gr.Textbox(label="Assistant Answer")
+    return qa_chain.run(query)
 
+# ✅ Gradio UI (fixed)
 with gr.Blocks() as app:
     gr.Markdown("## 🤖 Kaggle Study Assistant\nUpload PDFs from Kaggle and ask intelligent questions.")
-    upload_output = gr.Textbox(visible=True)
+
+    with gr.Row():
+        upload = gr.File(file_types=[".pdf"], file_count="multiple", label="Upload Kaggle PDFs")
+        btn_upload = gr.Button("📥 Process PDFs")
+
+    upload_output = gr.Textbox(label="Upload Status")
     btn_upload.click(fn=upload_pdfs, inputs=upload, outputs=upload_output)
+
+    question = gr.Textbox(label="Ask a question about uploaded notebooks")
+    answer = gr.Textbox(label="Assistant Answer", interactive=False)
     question.submit(fn=ask_question, inputs=question, outputs=answer)
 
 app.launch()