Update app.py

app.py

@@ -5,16 +5,13 @@ from reportlab.platypus import SimpleDocTemplate, Paragraph
 from reportlab.lib.styles import getSampleStyleSheet
 from reportlab.lib.pagesizes import A4
 
-# Configure Gemini API
+# -------------------- CONFIG --------------------
 genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
 
 # ---------- PROMPTS ----------
 TRANSCRIPTION_PROMPT = """ Transcribe the PDF into a clean, question-wise format. While doing so, ensure the following:
-
 Exclude any text that has been cut, striked, or crossed out (since these may represent student mistakes).
-
 Clearly distinguish between a "step cut" and when variables cancel out during a step.
-
 Present the transcription neatly without including unnecessary markings. """
 GRADING_PROMPT = """ Instructions to Examiners:
 Abbreviations:
@@ -23,7 +20,6 @@ Abbreviations:
 - R: Marks for clear Reasoning.
 - AG: Answer given in the question; no marks awarded.
 - FT: Follow Through; award marks for correct method/answer using incorrect earlier results.
-
 Marking Rules:
 1. Always follow the markscheme annotations (M1, A2, etc.).
 2. M marks must be earned before dependent A marks are awarded (no M0 followed by A1 unless explicitly allowed).
@@ -33,12 +29,12 @@ Marking Rules:
 6. "Show that" responses do not need to restate the AG line unless noted.
 7. Once a correct answer is seen, ignore further incorrect working unless it affects a later part (then apply FT as appropriate).
 8. Do not award the final A mark if an incorrect approximation is used in the same part.
-
 Error Avoidance:
 - **No incorrect mark allocation:** Do not award marks unless they are explicitly justified by the markscheme.
 - **No misclassification of errors:** Distinguish correctly between "Conceptual Errors" and "Silly Mistakes."
 - **Follow markscheme logic exactly:** Especially regarding when to withhold accuracy marks if method marks are not earned."""
 
+
 # ---------- HELPER: Save to PDF ----------
 def save_as_pdf(text, filename="output.pdf"):
     styles = getSampleStyleSheet()
@@ -47,35 +43,44 @@ def save_as_pdf(text, filename="output.pdf"):
     doc.build(story)
     return filename
 
+
 # ---------- STEP 1: TRANSCRIPTION ----------
 def transcribe(ans_file):
     try:
-        ans_uploaded = genai.upload_file(path=ans_file.name, display_name="Answer Sheet")
+        ans_uploaded = genai.upload_file(path=ans_file, display_name="Answer Sheet")
         model = genai.GenerativeModel("gemini-2.5-pro", generation_config={"temperature": 0})
 
         resp = model.generate_content([TRANSCRIPTION_PROMPT, ans_uploaded])
 
-        transcription = getattr(resp, "text", None) or resp.candidates[0].content.parts[0].text
+        transcription = getattr(resp, "text", None)
+        if not transcription and resp.candidates:
+            transcription = resp.candidates[0].content.parts[0].text
+
         pdf_path = save_as_pdf(transcription, "transcription.pdf")
         return transcription, pdf_path
     except Exception as e:
         return f"❌ Error during transcription: {e}", None
 
+
 # ---------- STEP 2: GRADING ----------
 def grade(qp_file, ms_file, transcription):
     try:
-        qp_uploaded = genai.upload_file(path=qp_file.name, display_name="Question Paper")
-        ms_uploaded = genai.upload_file(path=ms_file.name, display_name="Marking Scheme")
+        qp_uploaded = genai.upload_file(path=qp_file, display_name="Question Paper")
+        ms_uploaded = genai.upload_file(path=ms_file, display_name="Marking Scheme")
         model = genai.GenerativeModel("gemini-2.5-pro", generation_config={"temperature": 0})
 
         resp = model.generate_content([GRADING_PROMPT, qp_uploaded, ms_uploaded, transcription])
 
-        grading = getattr(resp, "text", None) or resp.candidates[0].content.parts[0].text
+        grading = getattr(resp, "text", None)
+        if not grading and resp.candidates:
+            grading = resp.candidates[0].content.parts[0].text
+
         pdf_path = save_as_pdf(grading, "grading.pdf")
         return grading, pdf_path
     except Exception as e:
         return f"❌ Error during grading: {e}", None
 
+
 # ---------- GRADIO APP ----------
 with gr.Blocks(title="📘 AI Teacher Assistant") as demo:
     gr.Markdown("## 📘 AI Teacher Assistant\nUpload exam documents to transcribe and grade student answers step by step.")
@@ -88,7 +93,7 @@ with gr.Blocks(title="📘 AI Teacher Assistant") as demo:
     # Step 1: Transcription
     transcribe_btn = gr.Button("Step 1: Transcribe Answer Sheet")
     with gr.Row():
-        transcription_out = gr.Markdown(label="📄 Student Transcription")
+        transcription_out = gr.Textbox(label="📄 Student Transcription", lines=20)
         transcription_pdf = gr.File(label="⬇️ Download Transcription (PDF)")
 
     # Step 2: Grading
@@ -97,7 +102,7 @@ with gr.Blocks(title="📘 AI Teacher Assistant") as demo:
         grading_out = gr.Textbox(label="✅ Grading Report (Step-by-Step)", lines=20)
         grading_pdf = gr.File(label="⬇️ Download Grading (PDF)")
 
-    # Button Logic with loading indicators
+    # Button Logic
     transcribe_btn.click(
         fn=transcribe,
         inputs=[ans_file],