Create app.py

app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+import torch
+from diffusers import FluxPipeline
+
+# Load model once
+pipe = FluxPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-dev",
+    torch_dtype=torch.bfloat16
+)
+pipe.enable_model_cpu_offload()   # optional, saves VRAM
+
+
+def generate_image(text):
+    if not text.strip():
+        return None
+
+    prompt = (
+        "High resolution A4 document page, clean printed text, "
+        "sharp readable black fonts, no distortions. Content:\n" + text
+    )
+
+    image = pipe(
+        prompt,
+        height=1024,
+        width=1024,
+        guidance_scale=3.0,
+        num_inference_steps=40,
+        max_sequence_length=512,
+        generator=torch.Generator('cpu').manual_seed(42)
+    ).images[0]
+
+    return image
+
+
+# Gradio UI
+demo = gr.Interface(
+    fn=generate_image,
+    inputs=gr.Textbox(lines=8, label="Enter Text Here"),
+    outputs=gr.Image(type="pil", label="Generated Image"),
+    title="Text ➝ Image Generator (FLUX.1-dev)"
+)
+
+demo.launch()