app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

# Load the model from Hugging Face Hub
MODEL_NAME = "tacab/somali-agriculture"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)

# Create text generation pipeline
generator = pipeline("text-generation", model=model, tokenizer=tokenizer)

# Function to use in the Gradio interface
def generate_text(prompt):
    output = generator(
        prompt,
        do_sample=True,
        max_length=200,
        pad_token_id=tokenizer.eos_token_id
    )
    return output[0]["generated_text"]

# Build Gradio interface
gr.Interface(
    fn=generate_text,
    inputs=gr.Textbox(lines=3, label="Geli qoraalka/Prompt-ka"),
    outputs=gr.Textbox(label="Natiijada/Generated Text"),
    title="Tacab – Somali Agriculture Generator",
    description="App-kan wuxuu adeegsadaa model-ka 'tacab/somali-agriculture' si uu u abuuro qoraal cusub oo la xiriira beeraha Soomaaliyeed."
).launch()