Update app.py

app.py

@@ -3,13 +3,25 @@ from PIL import Image
 from main import ImageProcessor, PDFProcessor  # Replace 'your_module' with the actual module where your ImageProcessor and PDFProcessor classes are defined
 import google.generativeai as genai
 import os
+from dotenv import load_dotenv
+load_dotenv()
+
 
 genai.configure(api_key=os.getenv("API_KEY"))
 llm = genai.GenerativeModel("gemini-pro")
 
 
-# Streamlit title
-st.title("Q&A with Images & PDF")
+os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = 'application_default_credentials.json'
+
+# title
+st.markdown(
+    """
+    <div style="text-align:center">
+        <h1>Q&A with Images & PDF 🤖</h1>
+    </div>
+    """,
+    unsafe_allow_html=True
+)
 
 # File upload for image or PDF
 file_type = st.radio("Select File Type:", ["Image", "PDF"])
@@ -21,21 +33,35 @@ query = st.text_input("Enter your question:")
 # Display box for generated answer
 answer_display = st.empty()
 
-if uploaded_file is not None:
-    if file_type == "Image":
-        # Image processing
-        image_processor = ImageProcessor(uploaded_file)
-        captions = image_processor.get_caption(uploaded_file)
-        detections = image_processor.detect_objects(uploaded_file)
-        prompt = image_processor.make_prompt(query, captions, detections)
-        answer = image_processor.generate_answer(prompt)
-        answer_display.text(answer)
-
-    elif file_type == "PDF":
-        # PDF processing
-        pdf_processor = PDFProcessor(uploaded_file)
-        pdf_vector_stores = pdf_processor.create_embedding_df(uploaded_file)
-        relevant_passage = pdf_processor.find_best_passage(query, pdf_vector_stores)
-        prompt = pdf_processor.make_prompt(query, relevant_passage)
-        answer = pdf_processor.generate_answer(prompt)
-        answer_display.text(answer)
+# Creating instances outside the conditional check
+image_processor = ImageProcessor(uploaded_file) if uploaded_file and file_type == "Image" else None
+pdf_processor = PDFProcessor(uploaded_file) if uploaded_file and file_type == "PDF" else None
+
+
+if st.button("Generate answer"):
+    try:
+        if not query:
+            raise ValueError("Please provide the question. DO NOT KEEP IT EMPTY!")
+
+        if uploaded_file is not None:
+            if file_type == "Image":
+                # Image processing
+                
+                captions = image_processor.get_caption(uploaded_file)
+                detections = image_processor.detect_objects(uploaded_file)
+                prompt = image_processor.make_prompt(query, captions, detections)
+                answer = image_processor.generate_answer(prompt)
+                answer_display.markdown(answer)
+
+            elif file_type == "PDF":
+                # PDF processing
+            
+                pdf_vector_stores = pdf_processor.create_embedding_df(uploaded_file)
+                relevant_passage = pdf_processor.find_best_passage(query, pdf_vector_stores)
+                prompt = pdf_processor.make_prompt(query, relevant_passage)
+                answer = pdf_processor.generate_answer(prompt)
+                answer_display.markdown(answer)
+
+
+    except ValueError as e:
+        st.warning(str(e))