Update app.py

app.py

@@ -629,7 +629,7 @@ Grading JSON:
     try:
         contents = [prompt] + images
         response = client.models.generate_content(
-            model="gemini-2.0-flash-exp",
+            model="gemini-2.5-flash",
             contents=contents
         )
         raw_text = response.text
@@ -794,7 +794,7 @@ def align_and_grade_pipeline(qp_path, ms_path, ans_path, subject="Maths", imprin
 
         print("1.i) Transcribing QP+MS (questions first, then full markscheme, with graph detection)...")
         qpms_prompt = QP_MS_TRANSCRIPTION_PROMPT["content"] + "\nAt the end, also list all questions in the markscheme where a graph is expected, in the format:\nGraph expected in:\n- Question <number> → Page <number>\n(One per line, after ==== MARKSCHEME END ====)"
-        qpms_text = gemini_generate_content(qpms_prompt, file_upload_obj=merged_uploaded)
+        qpms_text = gemini_generate_content(qpms_prompt, file_upload_obj=merged_uploaded, model_name="gemini-2.5-flash")
         print("📄 QP+MS transcription received. Saving debug file: debug_qpms_transcript.txt")
         with open("debug_qpms_transcript.txt", "w", encoding="utf-8") as f:
             f.write(qpms_text)
@@ -812,7 +812,7 @@ def align_and_grade_pipeline(qp_path, ms_path, ans_path, subject="Maths", imprin
 
         print("1.ii) Building AS transcription prompt with expected question IDs and graph detection, sending to Gemini...")
         as_prompt = build_as_cot_prompt_with_expected_ids(extracted_ids, qpms_text) + "\nAt the end, also list all answers where a graph is found, in the format:\nGraph found in:\n- Answer <number> → Page <number>\n(One per line, after all answers)"
-        as_text = gemini_generate_content(as_prompt, file_upload_obj=ans_uploaded)
+        as_text = gemini_generate_content(as_prompt, file_upload_obj=ans_uploaded, model_name="gemini-2.5-flash")
         print("📝 AS transcription received. Saving debug file: debug_as_transcript.txt")
         with open("debug_as_transcript.txt", "w", encoding="utf-8") as f:
             f.write(as_text)
@@ -839,7 +839,7 @@ def align_and_grade_pipeline(qp_path, ms_path, ans_path, subject="Maths", imprin
         grading_prompt_obj = get_grading_prompt(subject.lower())
         grading_prompt_system = grading_prompt_obj["content"]
         grading_images = ms_graph_images + as_graph_images
-        grading_text = gemini_generate_content(grading_prompt_system + "\n\nPlease grade the following transcripts:\n" + grading_input, image_obj=grading_images if grading_images else None)
+        grading_text = gemini_generate_content(grading_prompt_system + "\n\nPlease grade the following transcripts:\n" + grading_input, image_obj=grading_images if grading_images else None, model_name="gemini-2.5-pro")
         print("🧾 Grading output received. Saving debug file: debug_grading.md")
         with open("debug_grading.md", "w", encoding="utf-8") as f:
             f.write(grading_text)