sync with remote

app.py

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+import streamlit as st
+import google.generativeai as genai
+import os
+import tempfile
+
+MODEL_ID = "gemini-2.0-flash-exp"
+genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
+model = genai.GenerativeModel(MODEL_ID)
+chat = model.start_chat()
+
+# Initialize session state variables
+if 'essay_question' not in st.session_state:
+    st.session_state.essay_question = ""
+if 'scoring_rubric' not in st.session_state:
+    st.session_state.scoring_rubric = ""
+if "subject" not in st.session_state:
+    st.session_state.subject = ""
+if "topic" not in st.session_state:
+    st.session_state.topic = ""
+
+def generate_essay_question(subject, topic, difficulty):
+    try:
+        prompt = f"Create an essay question on the topic '{topic}' in the context of {subject} with a {difficulty} difficulty level.  Output the essay question only. Do not provide any other information."
+        response = model.generate_content(prompt)
+        return response.text
+    except Exception as e:
+        st.error(f"An error occurred: {e}")
+        return None
+
+def generate_scoring_rubric(essay_question):
+    return f"Scoring Rubric for the essay question: {essay_question}\n\n1. Clarity: 10 points\n2. Argument Strength: 10 points\n3. Grammar: 10 points\n4. Creativity: 10 points\n5. Relevance to Topic: 10 points\n\nTotal: 50 points"
+
+def capture_exam_photo():
+    img_file_buffer = None
+    image_path = ""
+
+    # Use the camera to capture an image
+    img_file_buffer = st.camera_input("Take a picture")
+
+    if img_file_buffer is not None:
+            # Save the image to a temporary file
+            with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
+                temp_file.write(img_file_buffer.read())
+                image_path = temp_file.name
+            return image_path
+    else:
+        st.warning("Please capture an image of the exam paper.")
+        return None
+
+def main():
+
+    # Streamlit UI
+    st.title("Essay Grading System")
+    tabs = ["Essay Question", "Scoring Rubric", "Grading Outputs"]
+    selected_tab = st.sidebar.radio("Select a Tab", tabs)
+
+    if selected_tab == "Essay Question":
+        st.header("Generate Essay Question")
+        if st.session_state.subject != "":
+            subject = st.text_input("Enter Subject", st.session_state.subject)
+        else:
+            subject = st.text_input("Enter Subject")
+        if st.session_state.subject != "":
+            topic = st.text_input("Enter Topic", st.session_state.topic)
+        else:
+            topic = st.text_input("Enter Topic")
+            
+        difficulty = st.selectbox("Select Difficulty", ["Easy", "Moderate", "Difficult"])
+        
+        if st.button("Generate Question"):
+            if subject and topic and difficulty:
+                st.session_state.essay_question = generate_essay_question(subject, topic, difficulty)
+                st.success("Essay question generated successfully!")
+            else:
+                st.warning("Please provide the subject and topic.")        
+        if st.session_state.essay_question:
+            st.subheader("Generated Essay Question:")
+            st.write(st.session_state.essay_question)
+
+    elif selected_tab == "Scoring Rubric":
+        st.header("Scoring Rubric")
+        if not st.session_state.essay_question:
+            st.warning("Please generate an essay question first.")
+        else:
+            if not st.session_state.scoring_rubric:
+                st.session_state.scoring_rubric = generate_scoring_rubric(st.session_state.essay_question)
+            
+            st.subheader("Generated Scoring Rubric:")
+            st.session_state.scoring_rubric = st.text_area("Edit Rubric", st.session_state.scoring_rubric, height=200)
+
+    elif selected_tab == "Grading Outputs":
+        st.header("Grading Outputs")
+        if not st.session_state.essay_question or not st.session_state.scoring_rubric:
+            st.warning("Please generate both an essay question and a scoring rubric first.")
+        else:
+            exam_image_path = capture_exam_photo()
+            mime_type = "image/jpeg"
+            if exam_image_path is not None:
+
+                # Upload the file with the correct MIME type
+                file_data = genai.upload_file(exam_image_path, mime_type=mime_type)
+
+                multimodal_prompt = f"Extract all the text from the image. Score the essay exam response to the Essay Question: {st.session_state.essay_question}\nScoring Rubric: {st.session_state.scoring_rubric}.  Provide feednack on the essay response."
+                
+                # Send file and prompt to Gemini API
+                response = chat.send_message(
+                    [
+                        multimodal_prompt, 
+                        file_data
+                    ]
+                )                
+
+                st.subheader("AI Grading Response:")
+                # Display Gemini response
+                st.markdown(response.text)
+
+
+if __name__ == "__main__":
+    main()  

requirements.txt

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+streamlit
+google-generativeai