retry

app.py

@@ -5,14 +5,17 @@ from transformers import AutoTokenizer, AutoModelForQuestionAnswering
 # Replace with your Hugging Face API token
 hf_api_token = "HF_API_KEY"
 
-def generate_questions(file_content):
-    # Load MolMo model and tokenizer with API token
-    model_name = "allenai/Molmo-7B-D-0924"
-    tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=hf_api_token)
-    model = AutoModelForQuestionAnswering.from_pretrained(model_name, use_auth_token=hf_api_token)
+# Load the model and tokenizer globally, not inside the function
+model_name = "allenai/Molmo-7B-D-0924"
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=hf_api_token)
+model = AutoModelForQuestionAnswering.from_pretrained(model_name, use_auth_token=hf_api_token)
 
+def generate_questions(file_content):
     # Preprocess file content (assuming it's already text)
-    text = file_content.decode("utf-8")
+    try:
+        text = file_content.decode("utf-8")
+    except Exception as e:
+        return f"Error decoding file: {str(e)}", ""
 
     # Generate questions and answers
     inputs = tokenizer(text, return_tensors="pt")
@@ -31,7 +34,7 @@ def generate_questions(file_content):
     return questions, options
 
 # Create Gradio interface
-question_box = gr.Textbox(label="Question")
+question_box = gr.Textbox(label="Questions")
 option_box = gr.Textbox(label="Options")
 
 iface = gr.Interface(
@@ -41,4 +44,4 @@ iface = gr.Interface(
     title="Question and Option Generator"
 )
 
-iface.launch()
+iface.launch()