updated app.py

app.py

@@ -15,6 +15,7 @@ import pandas as pd
 from reportlab.lib.pagesizes import letter
 from reportlab.pdfgen import canvas
 import io
+from textwrap import wrap
 
 import yake
 import tempfile
@@ -108,29 +109,41 @@ def ocr_image(image: Image.Image) -> dict:
 def generate_pdf(results: dict) -> str:
     buffer = io.BytesIO()
     c = canvas.Canvas(buffer, pagesize=letter)
+    width, height = letter
     c.setFont("Helvetica", 12)
-    c.drawString(50, 750, "AI Multi-Modal Assistant Report")
+    
+    c.drawString(50, height - 50, "AI Multi-Modal Assistant Report")
 
-    y = 720
+    y = height -80      # Starting y position
+     
     for key, value in results.items():
-        c.drawString(50, y, f"{key}: {value}")
-        y -= 20
-        if y < 60:
-            c.showPage()
-            y = 750
+        # Convert any complex types to string
+        if isinstance(value, (list, dict)):
+            value = str(value)
+
+        # Wrap long lines (max 90 chars per line)
+        wrapped_lines = wrap(f"{key}: {value}", width=90)
+        for line in wrapped_lines:
+            c.drawString(50, y, line)
+            y -= 18
+            if y < 60:  # New page if needed
+                c.showPage()
+                c.setFont("Helvetica", 12)
+                y = height - 50
+
+        y -= 10  # Space between entries
 
     c.save()
     buffer.seek(0)
 
-    # ✅ Save to a temp file and return path instead of buffer
     with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp:
         tmp.write(buffer.getvalue())
         tmp_path = tmp.name
 
     return tmp_path
-    return tmp_path  # ✅ returns file path (Gradio-friendly)
 
 
+    
 # ------------------------------
 # 3. Multi‑Modal Analysis Function
 # ------------------------------