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import gradio as gr
import pandas as pd
import datetime
from openai import OpenAI
import os
# 🔐 Setup API Key (store as HF_SECRET)
openai_api_key = os.getenv("OPENAI_API_KEY")
client = OpenAI(api_key=openai_api_key)
def generate_plan(subjects, exam_date, hours_per_day):
subjects = [s.strip() for s in subjects.split(",")]
exam_date = pd.to_datetime(exam_date)
today = pd.to_datetime("today").normalize()
total_days = (exam_date - today).days
if total_days <= 0 or not subjects:
return "Invalid input", None, None
total_hours = total_days * hours_per_day
hours_per_subject = total_hours // len(subjects)
# Simple schedule
schedule = []
for i in range(total_days):
date = today + pd.Timedelta(days=i)
subject = subjects[i % len(subjects)]
schedule.append({
"Date": date.date(),
"Subject": subject,
"Hours": round(hours_per_day / len(subjects), 2)
})
df = pd.DataFrame(schedule)
# Generate Tip from LLM
prompt = f"""Generate a short, motivating study tip for a student studying {', '.join(subjects)} with {hours_per_day} hours per day until {exam_date.date()}."""
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": prompt}]
)
tip = response.choices[0].message.content.strip()
return tip, df, df.to_csv(index=False)
# Gradio interface
with gr.Blocks() as demo:
gr.Markdown("## 📚 Personalized Study Plan Generator")
subjects = gr.Textbox(label="Enter subjects (comma-separated)")
exam_date = gr.Textbox(label="Enter exam date (YYYY-MM-DD)")
hours = gr.Slider(1, 12, step=1, label="Hours per day")
btn = gr.Button("Generate Plan")
output_tip = gr.Textbox(label="AI Study Tip")
output_table = gr.Dataframe(label="Study Plan")
download_csv = gr.File(label="Download CSV")
def generate_and_show(subjects, exam_date, hours):
tip, df, csv = generate_plan(subjects, exam_date, hours)
with open("study_plan.csv", "w") as f:
f.write(csv)
return tip, df, "study_plan.csv"
btn.click(fn=generate_and_show, inputs=[subjects, exam_date, hours],
outputs=[output_tip, output_table, download_csv])
demo.launch()
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