Update app.py

app.py

@@ -1,100 +1,118 @@
 import os
-import json
 import random
-import subprocess
 import gradio as gr
 
-from agents import AnalyzerAgent, CoachAgent, PredictiveAgent
-from ocr_agent import OcrAgent
+from demo_questions import QUESTIONS  # 60 demo questions
 
-# Paths
-DATA_DIR = "data"
-QUESTIONS_FILE = "questions.json"
-os.makedirs(DATA_DIR, exist_ok=True)
-
-# Load merged question bank
-def load_question_bank():
-    if not os.path.exists(QUESTIONS_FILE) or os.path.getsize(QUESTIONS_FILE) == 0:
-        return []
-    try:
-        with open(QUESTIONS_FILE, "r", encoding="utf-8") as f:
-            return json.load(f)
-    except:
+# ===============================
+# Utilities
+# ===============================
+def get_questions(subject):
+    """Return 10 random questions for the selected subject."""
+    if subject not in QUESTIONS or len(QUESTIONS[subject]) == 0:
         return []
+    return random.sample(QUESTIONS[subject], min(10, len(QUESTIONS)))
+
+
+def grade_exam(answers, questions):
+    """Grade answers, return score + analysis."""
+    correct = 0
+    analysis = []
+    for idx, (ans, q) in enumerate(zip(answers, questions), start=1):
+        if ans == q["answer"]:
+            correct += 1
+            analysis.append(f"✅ Q{idx}: Correct")
+        else:
+            analysis.append(
+                f"❌ Q{idx}: Your answer: {ans or 'No Answer'} | Correct: {q['answer']}"
+            )
+
+    score = f"🎯 Final Score: {correct} / {len(questions)}"
+    return score, "\n".join(analysis)
 
-QUESTION_BANK = load_question_bank()
-
-# Initialize agents
-analyzer = AnalyzerAgent()
-coach = CoachAgent()
-predictor = PredictiveAgent()
-ocr_agent = OcrAgent()
-
-# Functions
-def upload_pdf(pdf_file, subject, year, paper):
-    if pdf_file is None:
-        return "⚠️ No file uploaded."
-    questions = ocr_agent.extract_questions(pdf_file, subject, year, paper)
-    subprocess.run(["python", "merge_questions.py"])
-    return f"✅ Extracted {len(questions)} questions from {subject.upper()} Paper {paper} ({year})"
-
-def run_exam(subject, num_questions, include_predicted):
-    pool = [q for q in QUESTION_BANK if subject.lower() in q["source"]]
-    if include_predicted:
-        predicted = predictor.predict(subject)
-        pool.append({"id": 9999, "text": predicted, "choices": [], "topics": [], "source": "predicted"})
-    if not pool:
-        return "⚠️ No questions available.", [], []
-    selected = random.sample(pool, min(num_questions, len(pool)))
-    q_texts = [q["text"] for q in selected]
-    q_ids = [q["id"] for q in selected]
-    return "\n\n".join(q_texts), q_ids, [q.get("choices", []) for q in selected]
-
-def submit_answers(q_ids, answers):
-    correct_answers = ["A"] * len(q_ids)  # Placeholder until scheme data ready
-    score, analysis = analyzer.analyze(answers, correct_answers)
-    return f"Score: {score}/{len(q_ids)}", "\n".join(analysis)
-
-def essay_feedback(essay_text):
-    return coach.coach(essay_text)
 
+# ===============================
 # Gradio UI
-with gr.Blocks() as demo:
-    gr.Markdown("## 📝 SPM Exam Simulator (Form 5)")
-
-    with gr.Tab("Upload Past Papers"):
-        pdf_file = gr.File(label="Upload PDF", type="filepath")
-        subject = gr.Dropdown(["BM", "English", "Math", "History", "Science", "MoralStudies"], label="Subject")
-        year = gr.Number(label="Year", value=2018, precision=0)
-        paper = gr.Dropdown([1, 2], label="Paper")
-        upload_btn = gr.Button("Process PDF")
-        upload_out = gr.Textbox(label="Upload Status")
-        upload_btn.click(fn=upload_pdf, inputs=[pdf_file, subject, year, paper], outputs=upload_out)
-
-    with gr.Tab("Paper 2 Simulator"):
-        subject_sim = gr.Dropdown(["BM", "English", "Math", "History", "Science", "MoralStudies"], label="Subject")
-        num_q = gr.Slider(1, 50, step=1, value=10, label="Number of Questions")
-        include_pred = gr.Checkbox(label="Include AI-Predicted")
-        run_btn = gr.Button("Start Simulation")
-        q_out = gr.Textbox(label="Questions")
-        ids_out = gr.State()
-        choices_out = gr.State()
-        run_btn.click(fn=run_exam, inputs=[subject_sim, num_q, include_pred], outputs=[q_out, ids_out, choices_out])
-
-        ans_in = gr.Textbox(label="Your Answers (comma-separated, e.g. A,B,C)")
-        submit_btn = gr.Button("Submit")
-        score_out = gr.Textbox(label="Score")
-        analysis_out = gr.Textbox(label="Analysis")
-        submit_btn.click(fn=lambda ids, ans: submit_answers(ids, ans.split(",")),
-                         inputs=[ids_out, ans_in], outputs=[score_out, analysis_out])
-
-    with gr.Tab("Paper 1 (Essay Practice)"):
-        essay_in = gr.Textbox(label="Write your essay here", lines=10)
-        essay_btn = gr.Button("Get Feedback")
-        essay_out = gr.Textbox(label="Feedback")
-        essay_btn.click(fn=essay_feedback, inputs=essay_in, outputs=essay_out)
-
-demo.launch(server_name="0.0.0.0", server_port=7860)
+# ===============================
+with gr.Blocks(title="SPM Exam Simulator") as demo:
+    gr.Markdown(
+        """
+        # 📘 SPM Exam Simulator (Demo Version)
+
+        Welcome! This platform allows Form 5 students to practice **real-world SPM-style exam papers**.  
+        👉 Select a subject, click **Start Exam**, and answer **10 questions** just like in the actual exam.
+        """
+    )
+
+    with gr.Row():
+        subject_dd = gr.Dropdown(
+            choices=list(QUESTIONS.keys()),
+            label="Select Subject",
+            value="BM",
+        )
+        start_btn = gr.Button("🚀 Start Exam", variant="primary")
+
+    with gr.Column() as exam_area:
+        gr.Markdown("### 📝 Exam Section")
+        gr.Markdown("Answer all questions below:")
+
+        question_boxes = []
+        answer_boxes = []
+
+        for i in range(10):
+            q_text = gr.Markdown(f"Q{i+1}: (Will load after Start)")
+            q_opts = gr.Radio(choices=[], label=f"Answer Q{i+1}", type="value")
+            question_boxes.append(q_text)
+            answer_boxes.append(q_opts)
+
+        submit_btn = gr.Button("✅ Submit Answers", visible=False, variant="primary")
+
+    with gr.Column():
+        gr.Markdown("### 📊 Results Section")
+        score_out = gr.Textbox(label="Score", interactive=False)
+        analysis_out = gr.Textbox(label="Answer Analysis", lines=15, interactive=False)
+
+    # ===========================
+    # Handlers
+    # ===========================
+    def load_exam(subject):
+        qs = get_questions(subject)
+        updates = []
+        for i, q in enumerate(qs):
+            updates.append(gr.update(value=f"**Q{i+1}:** {q['text']}"))
+            updates.append(gr.update(choices=q["choices"], value=None))
+        # Fill remaining slots if less than 10
+        for j in range(len(qs), 10):
+            updates.append(gr.update(value=f"Q{j+1}: (No Question)"))
+            updates.append(gr.update(choices=[], value=None))
+        return updates + [gr.update(visible=True)], qs
+
+    def submit_exam(*answers, subject, questions):
+        score, analysis = grade_exam(list(answers), questions)
+        return score, analysis
+
+    # ===========================
+    # Events
+    # ===========================
+    exam_state = gr.State([])
+
+    start_btn.click(
+        fn=load_exam,
+        inputs=subject_dd,
+        outputs=[*question_boxes, *answer_boxes, submit_btn, exam_state],
+    )
+
+    submit_btn.click(
+        fn=submit_exam,
+        inputs=[*answer_boxes, subject_dd, exam_state],
+        outputs=[score_out, analysis_out],
+    )
+
+# ===============================
+# Launch
+# ===============================
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)