app.py

from flask import Flask, request, jsonify, send_file
from diffusers import StableDiffusionPipeline
import torch
from io import BytesIO
from PIL import Image

app = Flask(__name__)

# Load the model
model_id = "sairajg/Text_To_Image"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")  # Ensure you're using a GPU for inference

@app.route("/generate", methods=["POST"])
def generate_image():
    data = request.json
    prompt = data.get("prompt")
    if not prompt:
        return jsonify({"error": "Prompt is required"}), 400

    # Generate image
    with torch.autocast("cuda"):
        image = pipe(prompt).images[0]

    # Save image to a BytesIO object
    img_io = BytesIO()
    image.save(img_io, format="PNG")
    img_io.seek(0)

    return send_file(img_io, mimetype="image/png")

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=5000)