Update app.py

app.py

@@ -13,20 +13,6 @@ genai.configure(api_key=GEMINI_API_KEY)
 # Initialize model
 model = genai.GenerativeModel("gemini-2.5-pro", generation_config={"temperature": 0})
 
-# ---------- Helper: Safe Extraction ----------
-def safe_extract(response):
-    """Safely get text from Gemini response"""
-    try:
-        if hasattr(response, "text") and response.text:
-            return response.text
-        elif response.candidates:
-            for cand in response.candidates:
-                if cand.content and cand.content.parts:
-                    return cand.content.parts[0].text
-        return "⚠️ No response generated from Gemini."
-    except Exception as e:
-        return f"⚠️ Error extracting response: {str(e)}"
-
 
 # ---------- STEP 1: TRANSCRIPTION ----------
 def transcribe_files(qp_file, ms_file, ans_file):
@@ -39,7 +25,7 @@ def transcribe_files(qp_file, ms_file, ans_file):
     Persona:
     You are an expert transcriptionist specializing in scientific and mathematical documents.
     Your task is to transcribe the provided handwritten student solutions into Markdown with LaTeX.
-    
+
     Rules:
     - Use LaTeX for all math ($ ... $ inline, $$ ... $$ for display).
     - Do NOT correct mistakes. Just transcribe faithfully.
@@ -47,13 +33,16 @@ def transcribe_files(qp_file, ms_file, ans_file):
     - Use **bold** for question numbering (e.g., **1.**, **2a.**).
     - Preserve step-by-step structure (use align* for multi-line equations).
     - If a symbol is illegible, mark it as [unclear].
-    
-    Output:
-    - A single clean Markdown string with LaTeX equations.
     """
 
     response = model.generate_content([transcription_instructions, uploaded_as])
-    return safe_extract(response)
+
+    # Direct extraction (like in your notebook)
+    transcription = getattr(response, "text", None)
+    if not transcription:
+        transcription = response.candidates[0].content.parts[0].text
+
+    return transcription
 
 
 # ---------- STEP 2: GRADING ----------
@@ -77,7 +66,7 @@ def grade_files(qp_file, ms_file, ans_file, transcription):
         * Conceptual Error
         * Silly Mistake
         * None
-    
+
     Output:
     - For each part: show awarded marks + justification.
     - Explain reasoning step by step.
@@ -90,7 +79,13 @@ def grade_files(qp_file, ms_file, ans_file, transcription):
         uploaded_ms,
         transcription
     ])
-    return safe_extract(response)
+
+    # Direct extraction (like in your notebook)
+    grading = getattr(response, "text", None)
+    if not grading:
+        grading = response.candidates[0].content.parts[0].text
+
+    return grading
 
 
 # ---------- GRADIO UI ----------
@@ -111,5 +106,4 @@ with gr.Blocks() as demo:
     transcribe_btn.click(fn=transcribe_files, inputs=[qp, ms, ans], outputs=transcription_output)
     grade_btn.click(fn=grade_files, inputs=[qp, ms, ans, transcription_output], outputs=grading_output)
 
-# Launch for Hugging Face
 demo.launch()