app.py

import gradio as gr
import requests
import os
import json

# Define the function that queries the Hugging Face API
def generate_image_from_model(prompt):
    API_URL = "https://api-inference.huggingface.co/models/prompthero/openjourney"
    API_TOKEN = os.getenv("HF_READ_TOKEN")
    headers = {"Authorization": f"Bearer {API_TOKEN}"}

    payload = {
        "inputs": prompt,
    }

    response = requests.post(API_URL, headers=headers, json=payload)

    # Handle errors
    if response.status_code != 200:
        return f"Error: {response.status_code}, {response.text}"

    # Assuming the response is an image, save it temporarily and return the path
    image_data = response.content
    image_path = "generated_image.png"
    with open(image_path, "wb") as img_file:
        img_file.write(image_data)

    return image_path  # Return the path to the image

# Create the Gradio interface
interface = gr.Interface(
    fn=generate_image_from_model,
    inputs="text",
    outputs="image",
    title="OpenJourney Text-to-Image",
    description="Enter a prompt to generate an image using OpenJourney model."
)

# Launch the interface
interface.launch()