Create app.py

app.py

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+import streamlit as st
+from ocr_processing import OCRProcessor
+from grading_logic import GradingSystem
+import os
+
+# Initialize components
+ocr_handler = OCRProcessor()
+grading_handler = GradingSystem(ocr_handler)
+
+
+def main():
+    st.set_page_config(page_title="Grading Assistant", page_icon=":pencil:", layout="wide")
+
+    st.sidebar.title("Upload Student Files")
+    st.sidebar.info("Upload student answer sheets and marking schemes.")
+
+    student_files = st.sidebar.file_uploader("Upload Answer Sheets", type=["pdf", "jpeg", "jpg", "png"], accept_multiple_files=True)
+    marking_scheme_file = st.sidebar.file_uploader("Upload Marking Scheme (DOCX)", type=["docx"])
+
+    st.title("📖 Automated Grading Assistant")
+    st.subheader("An AI-powered tool for grading student responses.")
+
+    if st.button("Start Grading"):
+        if not student_files or not marking_scheme_file:
+            st.error("Both student answers and a marking scheme are required!")
+            return
+
+        student_image_paths = []
+        for student_file in student_files:
+            file_path = f"./uploads/{student_file.name}"
+            with open(file_path, "wb") as f:
+                f.write(student_file.getvalue())
+
+            if student_file.name.lower().endswith(".pdf"):
+                try:
+                    extracted_images = ocr_handler.convert_pdf_to_images(file_path)
+                    student_image_paths.extend(extracted_images)
+                except Exception as err:
+                    st.error(f"Error processing {student_file.name}: {err}")
+            else:
+                student_image_paths.append(file_path)
+
+        # Save marking scheme
+        marking_scheme_path = f"./uploads/{marking_scheme_file.name}"
+        with open(marking_scheme_path, "wb") as f:
+            f.write(marking_scheme_file.getvalue())
+
+        st.info("Extracting student responses...")
+        extracted_answers = grading_handler.extract_answers(student_image_paths)
+        st.success("Responses extracted successfully.")
+        st.text_area("Extracted Responses", extracted_answers, height=200)
+
+        st.info("Extracting marking scheme...")
+        marking_criteria = grading_handler.extract_marking_criteria(marking_scheme_path)
+        st.success("Marking scheme extracted.")
+        st.text_area("Marking Scheme", marking_criteria, height=200)
+
+        st.info("Evaluating responses...")
+        assessment_results = grading_handler.grade_answers(extracted_answers, marking_criteria)
+        st.success("Assessment complete.")
+        st.text_area("Assessment Results", assessment_results, height=200)
+
+
+if __name__ == "__main__":
+    main()