0.5×← Perlahan · Cepat →
💬Tekan Play Demo untuk lihat Grade Book Analysis Agent menganalisis gred.
Demo Complete — All Stages Generated
01 WhatsApp Command
02 Requirement Analysis
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03 Python Script Generation
1
📥
Ambil data gredDatabase — kehadiran, tugasan, peperiksaan
2
🧮
Kira purata gredJumlah markah setiap kursus
3
🔍
Analisis prestasiBandingkan purata dan lulus
4
📊
Jana laporanGraf gred + cadangan penambahbaikan
import requests, json, pandas as pd
API_GRADES = "https://api.univ.edu/v1/grades"
def fetch_gradebook():
resp = requests.get(API_GRADES)
return resp.json().get("grades", [])
def analyze_grades(grades):
df = pd.DataFrame(grades)
df["avg"] = df[["attendance","assignment","exam"]].mean(axis=1)
result = {
"course_avg": df.groupby("course")["avg"].mean().to_dict(),
"pass_rate": (df["avg"] >= 50).mean() * 100,
"top_performers": df.nlargest(5, "avg").to_dict("records")
}
return result
report = analyze_grades(fetch_gradebook())
print(json.dumps(report))
04 Block Diagram
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05 System Schematic
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⚠️ Jangan kongsikan data gred pelajar tanpa kebenaran.
06 Simulasi Analisis Gred
Mula Analisis
CS10178.5Pass
MATH20182.3Pass
PHY10265.2Pass
CHEM10145.8Fail
ENG20188.1Pass
07 Grade Book Analysis Report
Terminal Log
[SISTEM] Grade Book Analysis Agent sedia
System Architecture
🤖 Agent Layer
Grade fetcher
Avg calculator
Performance analyzer
LLM insights
🎓 Education Layer
Grade DB
Attendance
Assignments
Reports
Safety Notes
- Student grades are confidential and protected.
- Human review required before sharing analytics.
- Verify grade calculations for accuracy.
- Browser demo does not access real student data.