app.py

import gradio as gr
from transformers import pipeline

# Load the model
model = pipeline("text-generation", model="rish13/polymers")

def generate_response(prompt):
    # Generate text from the model
    response = model(prompt, max_length=150, num_return_sequences=1)
    generated_text = response[0]['generated_text']

    # Find the position of the first end-of-sentence punctuation
    end_punctuation = ['.', '!', '?']
    end_position = min((generated_text.find(punct) for punct in end_punctuation if punct in generated_text), default=-1)

    if end_position != -1:
        # Include the punctuation in the response
        generated_text = generated_text[:end_position + 1]

    return generated_text

# Define the Gradio interface
interface = gr.Interface(
    fn=generate_response,
    inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here...", label="Prompt"),
    outputs="text",
    title="Polymer Knowledge Model",
    description="A model fine-tuned for generating text related to polymers."
)

# Launch the interface
interface.launch()