app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

# Load your model
model_checkpoint = "AnasHXH/Ros_model"
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)

def generate_command(input_text):
    # Tokenize text and convert to model input format
    inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True)
    # Generate output from the model
    outputs = model.generate(inputs["input_ids"])
    # Decode the generated tokens to text
    command = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return command

# Define your Gradio interface
iface = gr.Interface(
    fn=generate_command,  # the function to wrap
    inputs="text",        # the input data type
    outputs="text",       # the output data type
    title="Robot Command Generator",
    description="Type in English to get the robot command"
)

# Run the Gradio app
iface.launch()