Update app.py

app.py

@@ -1,37 +1,56 @@
 import os
-import gradio as gr
+
+import streamlit as st
+
 from rag_utility import process_document_to_chromadb, answer_question
 
-def process_and_store_file(file):
-    if file is not None:
-        working_dir = os.getcwd()
-        save_path = os.path.join(working_dir, os.path.basename(file))
-        with open(save_path, "wb") as f:
-            f.write(file.read())
-        process_document_to_chromadb(save_path)
-        return "Document Processed Successfully"
-    return "No file uploaded."
-
-def get_answers(question):
-    if not question.strip():
-        return "Please enter a question.", "Please enter a question."
-    answer = answer_question(question)
-    return answer["answer_deepseek"], answer["answer_llama3"]
-
-with gr.Blocks() as demo:
-    gr.Markdown("# 🐋 DeepSeek-R1 vs 🦙 Llama-3")
-    with gr.Row():
-        file_input = gr.File(label="Upload a PDF file", file_types=[".pdf"], type="filepath")
-        process_button = gr.Button("Process Document")
-    status_output = gr.Textbox(label="Status", interactive=False)
-    process_button.click(process_and_store_file, inputs=file_input, outputs=status_output)
-    
-    question_input = gr.Textbox(label="Ask your question from the document")
-    answer_button = gr.Button("Answer")
-    with gr.Row():
-        deepseek_output = gr.Markdown("### DeepSeek-r1 Response")
-        llama3_output = gr.Markdown("### Llama-3 Response")
-    
-    answer_button.click(get_answers, inputs=question_input, outputs=[deepseek_output, llama3_output])
-
-demo.launch()
+
+# Set working directory (optional, ensures saving in project dir)
+working_dir = os.getcwd()
+
+st.title("🐋 DeepSeek-R1 vs 🦙 Llama-3")
+
+# File uploader
+uploaded_file = st.file_uploader("Upload a PDF file", type=["pdf"])
+
+if uploaded_file is not None:
+    # Define save path
+    save_path = os.path.join(working_dir, uploaded_file.name)
+    # Save file
+    with open(save_path, "wb") as f:
+        f.write(uploaded_file.getbuffer())
+
+    process_documents = process_document_to_chromadb(uploaded_file.name)
+    st.info("Document Processed Successfully")
+
+
+user_question = st.text_area("Ask your question from the document")
+
+if st.button("Answer"):
+    answer = answer_question(user_question)
+    answer_deepseek = answer["answer_deepseek"]
+    answer_llama3 = answer["answer_llama3"]
+
+    col1, col2 = st.columns(2)
+
+    with col1:
+        st.markdown("### DeepSeek-r1 Response")
+        st.markdown(
+            f"""
+            <div style="border: 1px solid #ccc; padding: 10px; border-radius: 5px; background-color: #f9f9f9;">
+                {answer_deepseek}
+            </div>
+            """,
+            unsafe_allow_html=True
+        )
+
+    with col2:
+        st.markdown("### Llama-3 Response")
+        st.markdown(
+            f"""
+            <div style="border: 1px solid #ccc; padding: 10px; border-radius: 5px; background-color: #f9f9f9;">
+                {answer_llama3}
+            </div>
+            """,
+            unsafe_allow_html=True
+        )