app.py

import os
import requests
import gradio as gr

# Define the function to query Hugging Face API for image generation
def generate_image(prompt):
    API_URL = "https://api-inference.huggingface.co/models/KingNish/flux-me"
    API_TOKEN = os.getenv("HF_READ_TOKEN")  # Ensure the token is set in your environment
    headers = {"Authorization": f"Bearer {API_TOKEN}"}

    payload = {
        "inputs": prompt
    }

    # Call the Hugging Face API to generate the image
    response = requests.post(API_URL, headers=headers, json=payload)

    # Check if the request was successful
    if response.status_code != 200:
        return f"Error: {response.status_code}, {response.text}"

    # Save the generated image
    image_path = "generated_image.png"
    with open(image_path, "wb") as f:
        f.write(response.content)

    return image_path

# Define the chatbot function to return the generated image
def chatbot(prompt):
    image = generate_image(prompt)
    return image

# Create the Gradio interface with the same UI/UX
interface = gr.Interface(
    fn=chatbot,
    inputs="text",
    outputs="image",
    title="prompthero/openjourney",
    description="Enter a text prompt and get an AI-generated image."
)

# Launch the interface
interface.launch()