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| import streamlit as st | |
| from src.main import process_essays | |
| from PIL import Image | |
| import os | |
| from openpyxl import load_workbook, Workbook | |
| from io import BytesIO | |
| import openai | |
| import base64 | |
| from src.utils import save_workbook_to_bytes, serve_excel_for_download, image_to_base64, download_image | |
| openai_api_key = os.getenv("OPENAI_API_KEY") | |
| # Set the OpenAI API key | |
| openai.api_key = openai_api_key | |
| st.title("AutoAssess: Student Essay Transcription and Assessment") | |
| st.subheader("Upload Student Essays") | |
| # Upload folder of images | |
| uploaded_files = st.file_uploader("Upload a folder of student essays (images). Please make sure that the images are in order i.e. first image is the first page of the first student, the second image is the second page of the first student (if it exists) untill all images of the first student are uploaded which should be followed by the ordererd pages of the second student, etc.", type=['jpg', 'jpeg', 'png'], accept_multiple_files=True) | |
| # Path to your example images (you need to place them in your project directory or provide a URL) | |
| # image_1_path = "example_essay_1.png" # Example file path | |
| # image_2_path = "example_essay_2.png" # Example file path | |
| # # Example images section | |
| # st.text("If you don't have any images to upload, you can download (and reupload) the example images below.") | |
| # # Download buttons for the two example essays (images) | |
| # download_image(image_1_path, "example_essay_1.png") | |
| # download_image(image_2_path, "example_essay_2.png") | |
| # replace uploaded files with files loading from directory | |
| # image_dir = "data/images" | |
| # uploaded_files = [] | |
| # for file in os.listdir(image_dir): | |
| # with open(image_dir + '/' + file, "rb") as image_file: | |
| # uploaded_files.append(image_file.read()) | |
| # Text inputs for question and criteria | |
| # essay_question = st.text_input("Enter the essay question:") | |
| # grading_criteria = st.text_area("Enter grading criteria or relevant marking information:") | |
| st.subheader("Specify Essay Question") | |
| st.text("For example: What is beauty?") | |
| essay_question = st.text_input("Enter the essay question:") | |
| st.subheader("Specify Grading Criteria") | |
| st.text("For example: Please follow the german grading system where 1 is the best grade and 6 is the worst grade. An essay with a grade of 1 should be well structured, have a clear introduction, body and conclusion, be free of grammatical errors, spelling mistakes and punctuation errors, be original and creative.") | |
| grading_criteria = st.text_area("Enter grading criteria or relevant marking information:") | |
| # essay_question = "What is beauty?" | |
| # grading_criteria = "1. Introduction\n2. Body\n3. Conclusion\n4. Grammar\n5. Spelling\n6. Punctuation\n7. Originality\n8. Creativity" | |
| # Path to the example Excel file in the repository | |
| st.subheader("Specify student IDs and page count") | |
| example_file_path ="example.xlsx" | |
| serve_excel_for_download(example_file_path) | |
| st.text("Please download the example Excel file to see the expected format. You will need to adjust the student IDs and page counts. Note that if you provide a grade and reason for a student, the system will not reassess that student's essay. Further, this will help te system make better assessments by calibrating it to your style of grading. Note that grade and reason must both be specified.") | |
| # Upload Excel file with student IDs and page count | |
| excel_file = st.file_uploader("Upload Excel file with student IDs and page count", type=["xlsx"]) | |
| # excel_file = "data/essays.xlsx" | |
| if st.button("Process Essays"): | |
| if not uploaded_files or not essay_question or not grading_criteria or not excel_file: | |
| st.warning("Please upload all required files and enter necessary information.") | |
| else: | |
| uploaded_files = sorted(uploaded_files, key=lambda x: x.name) | |
| # Process student info file | |
| workbook = load_workbook(excel_file) | |
| new_workbook = process_essays(uploaded_files,essay_question,grading_criteria,workbook) | |
| # Optional: Save results to the output folder | |
| # output_file = "output/results.xlsx" | |
| # new_workbook.save(output_file) | |
| # st.success(f"All essays processed. Results saved to {output_file}") | |
| # Convert the workbook to bytes | |
| excel_file = save_workbook_to_bytes(new_workbook) | |
| # Display the download button | |
| st.download_button( | |
| label="Download the assessed Excel file", | |
| data=excel_file, | |
| file_name="assessments.xlsx", | |
| mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" | |
| ) |