Update app.py

app.py

@@ -1,27 +1,18 @@
 import gradio as gr
 import numpy as np
 import random
+import os
+from huggingface_hub import InferenceClient
 
-# import spaces #[uncomment to use ZeroGPU]
-from diffusers import DiffusionPipeline
-import torch
-
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
-
-if torch.cuda.is_available():
-    torch_dtype = torch.float16
-else:
-    torch_dtype = torch.float32
-
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = pipe.to(device)
+# 初始化 InferenceClient
+client = InferenceClient(
+    provider="fal-ai",
+    api_key=os.environ["HF_TOKEN"],
+)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
-
-# @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
     prompt,
     negative_prompt,
@@ -35,22 +26,24 @@ def infer(
 ):
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
-
-    generator = torch.Generator().manual_seed(seed)
-
-    image = pipe(
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-        width=width,
-        height=height,
-        generator=generator,
-    ).images[0]
-
+    # 拼接 prompt 和 negative_prompt
+    full_prompt = prompt
+    if negative_prompt:
+        full_prompt += f". Negative prompt: {negative_prompt}"
+
+    # 发送推理请求
+    image = client.text_to_image(
+        full_prompt,
+        model="black-forest-labs/FLUX.1-Krea-dev",
+        # 下面参数部分模型可能不支持，可根据实际情况调整
+        # width=width,
+        # height=height,
+        # guidance_scale=guidance_scale,
+        # num_inference_steps=num_inference_steps,
+        seed=seed,
+    )
     return image, seed
 
-
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
     "An astronaut riding a green horse",
@@ -66,7 +59,7 @@ css = """
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
+        gr.Markdown(" # FLUX.1-Krea Text-to-Image Demo")
 
         with gr.Row():
             prompt = gr.Text(
@@ -105,7 +98,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=1024,
                 )
 
                 height = gr.Slider(
@@ -113,7 +106,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=1024,
                 )
 
             with gr.Row():
@@ -122,7 +115,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
+                    value=4.5,
                 )
 
                 num_inference_steps = gr.Slider(
@@ -130,7 +123,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=2,  # Replace with defaults that work for your model
+                    value=30,
                 )
 
         gr.Examples(examples=examples, inputs=[prompt])