app.py

import requests
import io
from PIL import Image
import gradio as gr
from transformers import MarianMTModel, MarianTokenizer
import os

model_name = "Helsinki-NLP/opus-mt-mul-en"
model = MarianMTModel.from_pretrained(model_name)
tokenizer = MarianTokenizer.from_pretrained(model_name)

def translate_text(tamil_text):
    inputs = tokenizer(tamil_text, return_tensors="pt")
    translated_tokens = model.generate(**inputs)
    translation = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
    return translation

def query_gemini_api(translated_text, gemini_api_key):
    url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent"
    headers = {"Content-Type": "application/json"}
    prompt = f"Based on the following sentence, continue the story: {translated_text}"
    payload = {
        "contents": [{"parts": [{"text": prompt}]}]
    }
    response = requests.post(f"{url}?key={gemini_api_key}", headers=headers, json=payload)

    if response.status_code == 200:
        result = response.json()
        creative_text = result['candidates'][0]['content']['parts'][0]['text']
        return creative_text
    else:
        return f"Error: {response.status_code} - {response.text}"

def query_image(payload):
    huggingface_api_key = os.getenv('HUGGINGFACE_API_KEY')
    API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
    headers = {"Authorization": f"Bearer {huggingface_api_key}"}
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.content

def process_input(tamil_input):
    gemini_api_key = os.getenv('GEMINI_API_KEY')  
    translated_output = translate_text(tamil_input)
    creative_output = query_gemini_api(translated_output, gemini_api_key)
    image_bytes = query_image({"inputs": translated_output})
    image = Image.open(io.BytesIO(image_bytes))
    return translated_output, creative_output, image


iface = gr.Interface(
    fn=process_input,
    inputs=[gr.Textbox(label="Input Tamil Text")],
    outputs=[
        gr.Textbox(label="Translated Text"),
        gr.Textbox(label="Creative Text"),
        gr.Image(label="Generated Image")
    ],
    title="TRANSART",
    description="Enter Tamil text to translate to English and generate an image based on the translated text."
)

interface.launch()