Create app.py

app.py

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+import base64, io, random, torch, gradio as gr
+from diffusers import DiffusionPipeline
+from PIL import Image
+
+MODEL_ID = "JingyeChen22/textdiffuser2-full-ft"
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+dtype = torch.float16 if device == "cuda" else torch.float32
+
+pipe = DiffusionPipeline.from_pretrained(MODEL_ID, torch_dtype=dtype).to(device)
+
+def gen_image(prompt, main_text, sub_text, negative_prompt, width, height, steps, guidance, seed):
+    # seed
+    if seed is None or str(seed).strip() == "":
+        seed = random.randint(1, 2**31 - 1)
+    g = torch.Generator(device=device).manual_seed(int(seed))
+
+    # prompt structuré pour TextDiffuser-2
+    full_prompt = f"{prompt}\ntext: '{main_text}'\nsubtext: '{sub_text}'"
+
+    img = pipe(
+        prompt=full_prompt,
+        negative_prompt=negative_prompt if negative_prompt else None,
+        num_inference_steps=int(steps),
+        guidance_scale=float(guidance),
+        width=int(width),
+        height=int(height),
+        generator=g
+    ).images[0]
+
+    # retour base64 pour un usage direct via API
+    buf = io.BytesIO()
+    img.save(buf, format="PNG")
+    b64 = base64.b64encode(buf.getvalue()).decode("utf-8")
+    return img, str(seed), b64
+
+with gr.Blocks() as demo:
+    gr.Markdown("### TextDiffuser-2 — API pour visuels LinkedIn (HF Space)")
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="Background prompt", value="Professional LinkedIn poster background, deep blue gradient, Quebec map in connected nodes, innovation & cybersecurity icons, clean corporate layout, high contrast")
+            main_text = gr.Textbox(label="Main title", value="SOUVERAINETÉ NUMÉRIQUE AU QUÉBEC")
+            sub_text = gr.Textbox(label="Subtitle", value="Un avantage compétitif réel ?")
+            negative_prompt = gr.Textbox(label="Negative prompt (optional)", value="blurry, misspelled text, distorted letters, artifacts, cluttered layout")
+            width  = gr.Number(label="Width", value=1200, precision=0)
+            height = gr.Number(label="Height", value=627,  precision=0)
+            steps = gr.Slider(10, 60, value=40, step=1, label="Steps")
+            guidance = gr.Slider(3.0, 12.0, value=7.5, step=0.5, label="Guidance")
+            seed = gr.Textbox(label="Seed (optional)")
+            btn = gr.Button("Generate")
+        with gr.Column():
+            out_img = gr.Image(label="Result", type="pil")
+            out_seed = gr.Textbox(label="Used seed")
+            out_b64 = gr.Textbox(label="Base64 PNG (for API)")
+    btn.click(gen_image, inputs=[prompt, main_text, sub_text, negative_prompt, width, height, steps, guidance, seed],
+              outputs=[out_img, out_seed, out_b64])
+
+demo.launch()