change login with gradio agent

app.py

@@ -6,34 +6,36 @@ from huggingface_hub import login, InferenceClient
 
 pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
 pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power
+
 token = os.getenv("HF_TOKEN")
 login(token=token)
 
 
 client = InferenceClient(
 	provider="together",
-	api_key="token"
+	api_key=token,
+    model="black-forest-labs/FLUX.1-dev",
+    token=token
 )
 
-prompt = "A cat holding a sign that says hello world"
-image = pipe(
-    prompt,
-    height=1024,
-    width=1024,
-    guidance_scale=3.5,
-    num_inference_steps=50,
-    max_sequence_length=512,
-    generator=torch.Generator("cpu").manual_seed(0),
-    use_auth_token=token
-).images[0]
-
-image.save("flux-dev.png")
+def generate_image(prompt):
+    image = pipe(
+        prompt,
+        height=1024,
+        width=1024,
+        guidance_scale=3.5,
+        num_inference_steps=50,
+        max_sequence_length=512,
+        generator=torch.Generator("cpu").manual_seed(0)
+    ).images[0]
+    return image
 
 gradio_app = gr.Interface(
-    image,
-    inputs=gr.Image(label="Select hot dog candidate", sources=['upload', 'webcam'], type="pil"),
-    outputs=[gr.Image(label="Processed Image"), gr.Label(label="Result", num_top_classes=2)],
-    title="Hot Dog? Or Not?",
+    fn=generate_image,
+    inputs=gr.inputs.Textbox(label="Entrez une description"),
+    outputs=gr.outputs.Image(label="Image générée"),
+    title="Générateur d'images IA",
+    description="Entrez une description et générez une image correspondante."
 )
 
 if __name__ == "__main__":