Upload app.py

app.py

@@ -20,7 +20,7 @@ from io import BytesIO
 from reportlab.lib.pagesizes import letter
 from reportlab.pdfgen import canvas
 from reportlab.lib.utils import ImageReader
-
+from PIL import Image
 # ===============================
 # 3️⃣ Groq Client
 # ===============================
@@ -116,66 +116,79 @@ def add_daily_entry(user_id, stress, mood, sleep_hours):
 def generate_weekly_report(user_id):
     global df
     df['date'] = pd.to_datetime(df['date'])
-    user_df = df[df['user_id']==user_id]
+    user_df = df[df['user_id'] == user_id]
+
     if user_df.empty:
         return "No data available yet.", None, None
+
     user_df['week'] = user_df['date'].dt.isocalendar().week
 
     weekly_summary = user_df.groupby('week').agg({
-        "stress":["mean","max"],
-        "mood":["mean","min"],
-        "sleep_hours":["mean","min"]
+        "stress": ["mean", "max"],
+        "mood": ["mean", "min"],
+        "sleep_hours": ["mean", "min"]
     })
+
     weekly_summary['stress_change'] = weekly_summary['stress']['mean'].diff()
     weekly_summary['mood_change'] = weekly_summary['mood']['mean'].diff()
     weekly_summary['sleep_change'] = weekly_summary['sleep_hours']['mean'].diff()
 
-    # Charts
-    fig, ax = plt.subplots(3,1,figsize=(8,10))
-    weekly_summary['stress']['mean'].plot(ax=ax[0],title="Weekly Avg Stress",color='red',marker='o')
-    weekly_summary['mood']['mean'].plot(ax=ax[1],title="Weekly Avg Mood",color='blue',marker='o')
-    weekly_summary['sleep_hours']['mean'].plot(ax=ax[2],title="Weekly Avg Sleep Hours",color='green',marker='o')
+    # ---- Create chart ----
+    fig, ax = plt.subplots(3, 1, figsize=(8, 10))
+
+    weekly_summary['stress']['mean'].plot(ax=ax[0], title="Weekly Avg Stress", marker="o")
+    weekly_summary['mood']['mean'].plot(ax=ax[1], title="Weekly Avg Mood", marker="o")
+    weekly_summary['sleep_hours']['mean'].plot(ax=ax[2], title="Weekly Avg Sleep Hours", marker="o")
+
     plt.tight_layout()
+
     chart_buf = BytesIO()
     plt.savefig(chart_buf, format="png")
+    plt.close()
     chart_buf.seek(0)
 
-    # LLaMA explanation
+    chart_image = Image.open(chart_buf)
+
+    # ---- LLaMA explanation ----
     trend_prompt = f"""
 You are a wellness data analyst AI.
-Here is the weekly summary for user {user_id}:
+
+Here is the weekly summary:
 {weekly_summary.tail(4)}
 
-Explain in plain language the trends in stress, mood, and sleep over the past 4 weeks.
+Explain the trends in stress, mood, and sleep in simple, policymaker-friendly language.
 """
+
     response = client.chat.completions.create(
         model="llama-3.3-70b-versatile",
-        messages=[{"role":"user","content":trend_prompt}]
+        messages=[{"role": "user", "content": trend_prompt}]
     )
+
     explanation = response.choices[0].message.content
 
-    # Generate PDF
+    # ---- PDF generation ----
     pdf_buf = BytesIO()
     c = canvas.Canvas(pdf_buf, pagesize=letter)
     width, height = letter
-    c.setFont("Helvetica",12)
-    y = height - 40
-    c.drawString(30,y,f"Weekly Trend Report for User {user_id}")
-    y -= 30
+
+    c.setFont("Helvetica-Bold", 14)
+    c.drawString(40, height - 40, "Weekly Mental Health Trend Report")
+
+    c.setFont("Helvetica", 11)
+    y = height - 80
     for line in explanation.split("\n"):
-        c.drawString(30,y,line)
-        y -= 15
+        c.drawString(40, y, line)
+        y -= 14
         if y < 100:
             c.showPage()
             y = height - 40
-    # Add chart
-    img = ImageReader(chart_buf)
+
     c.showPage()
-    c.drawImage(img,50,150,width=500,height=400)
+    c.drawImage(ImageReader(chart_buf), 50, 200, width=500, height=400)
     c.save()
     pdf_buf.seek(0)
 
-    return explanation, chart_buf, pdf_buf
+    return explanation, chart_image, pdf_buf
 
 # ===============================
 # 🔟 Gradio interface