Delete qgen_server.py

qgen_server.py

@@ -1,38 +0,0 @@
-
-import os
-from flask import request, jsonify
-from transformers import pipeline
-
-# Define a writable directory for the model cache
-cache_dir = os.path.join(os.getenv("XDG_CACHE_HOME", "/tmp/.cache"), "huggingface_models")
-os.makedirs(cache_dir, exist_ok=True)
-
-print("Loading Question Generation model (iarfmoose/t5-base-question-generator)...")
-# Initialize the pipeline for text2text-generation with the specified model
-qg_model = pipeline("text2text-generation", model="iarfmoose/t5-base-question-generator", model_kwargs={"cache_dir": cache_dir})
-print("Question Generation model loaded.")
-
-def handle_generate_questions():
-    data = request.get_json()
-    if not data or 'text' not in data:
-        return jsonify({'error': 'Invalid request. "text" field is required.'}), 400
-    
-    text = data['text']
-    
-    # Prepend the text with "generate questions: " as required by this model
-    input_text = f"generate questions: {text}"
-    
-    try:
-        # Generate questions
-        results = qg_model(input_text, max_length=64, num_beams=4, early_stopping=True)
-        
-        # The result is a single string with questions separated by '<sep>'
-        generated_text = results[0]['generated_text']
-        questions = [q.strip() for q in generated_text.split('<sep>') if q.strip()]
-        
-        print(f"Generated questions for text: '{text[:50]}...' -> {questions}")
-        
-        return jsonify({'questions': questions})
-    except Exception as e:
-        print(f"Error during question generation: {e}")
-        return jsonify({'error': str(e)}), 500