import gradio as gr
from transformers import AutoTokenizer, AutoModelForSequenceClassification

# Load the Hugging Face model and tokenizer
model_name = 'AIRI-Institute/gena-lm-bert-base-lastln-t2t'  # Replace with the actual model name
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

# Define a function to process the DNA sequence
def analyze_dna(sequence):
    # Preprocess the input sequence
    inputs = tokenizer(sequence, return_tensors='pt')
    # Get model predictions
    outputs = model(**inputs)

    predictions = outputs.logits.argmax(dim=-1).item()
    return f"Prediction: {predictions}"

# Create a Gradio interface
demo = gr.Interface(fn=analyze_dna, inputs="text", outputs="text")

# Launch the interface
demo.launch()