Update app.py

app.py

@@ -1,7 +1,103 @@
+import json
+import random
 import gradio as gr
+from agents import AnalyzerAgent, ForecastAgent, CoachAgent
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load questions
+with open("questions.json", "r", encoding="utf-8") as f:
+    QUESTION_BANK = json.load(f)
+
+# Agents
+analyzer = AnalyzerAgent()
+forecast_agent = ForecastAgent()
+coach_agent = CoachAgent()
+
+# State
+def start_exam(level, subject, num_questions=5):
+    # Filter questions
+    questions = [q for q in QUESTION_BANK if q["subject"] == f"{level}_{subject}"]
+    selected = random.sample(questions, min(num_questions, len(questions)))
+
+    # Keep only necessary fields for UI
+    exam_data = [
+        {"id": q["id"], "text": q["text"], "choices": q.get("choices", [])}
+        for q in selected
+    ]
+    return exam_data, gr.update(visible=True), gr.update(visible=False)
+
+def submit_exam(answers, exam_data, level, subject):
+    # Score
+    correct = 0
+    per_question = {}
+    for q in exam_data:
+        qid = str(q["id"])
+        user_ans = answers.get(qid, None)
+        correct_ans = next(item for item in QUESTION_BANK if item["id"] == q["id"])["correct_answer"]
+        per_question[qid] = {"user": user_ans, "correct": correct_ans}
+        if user_ans == correct_ans:
+            correct += 1
+
+    score = round(100 * correct / len(exam_data), 2)
+
+    # Run Analyzer
+    analysis = analyzer.analyze(per_question, QUESTION_BANK)
+
+    # Call Forecast Agent (GLM-4.5)
+    forecast = forecast_agent.forecast(level, subject)
+
+    # Call Coach Agent (GLM-4.5)
+    coach = coach_agent.coach(analysis, level, subject)
+
+    return (
+        f"Your Score: {score}%",
+        analysis,
+        forecast,
+        coach,
+        gr.update(visible=False),
+        gr.update(visible=True)
+    )
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("## 📘 Pay Fong Exam Simulator (AI-Powered)")
+    
+    with gr.Row():
+        level = gr.Dropdown(["Form2", "Form3", "Higher1", "Higher2", "Higher3"], label="Select Level")
+        subject = gr.Dropdown(["Math", "Science", "Physics", "Chemistry", "Biology"], label="Select Subject")
+        start_btn = gr.Button("Start Exam")
+    
+    exam_output = gr.State()
+    answers_state = gr.State()
+
+    exam_area = gr.Column(visible=False)
+    with exam_area:
+        gr.Markdown("### Exam Questions")
+        exam_display = gr.JSON(label="Questions")
+        answers_box = gr.JSON(label="Your Answers (edit as JSON: {id: 'answer'})")
+        submit_btn = gr.Button("Submit Exam")
+
+    results_area = gr.Column(visible=False)
+    with results_area:
+        score_text = gr.Textbox(label="Score")
+        analysis_json = gr.JSON(label="Weakness Analysis")
+        forecast_json = gr.JSON(label="Forecast (AI)")
+        coach_json = gr.JSON(label="Study Coach")
+
+    # Button actions
+    start_btn.click(
+        start_exam,
+        inputs=[level, subject],
+        outputs=[exam_display, exam_area, results_area]
+    ).then(
+        lambda exam: exam, outputs=exam_output
+    )
+
+    submit_btn.click(
+        submit_exam,
+        inputs=[answers_box, exam_output, level, subject],
+        outputs=[score_text, analysis_json, forecast_json, coach_json, exam_area, results_area]
+    )
+
+if __name__ == "__main__":
+    demo.launch()
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()