feat: switch to fal.ai API — fal-client + Multiple Angles LoRA

app.py

@@ -1,8 +1,9 @@
 import random
-import torch
+import base64
+import io
+import os
+import fal_client
 import gradio as gr
-import spaces
-from diffusers import QwenImageEditPlusPipeline
 from PIL import Image
 
 # ── Constantes poses ──────────────────────────────────────────────────────────
@@ -21,22 +22,6 @@ ELEVATION_NAMES = {
 }
 DISTANCE_NAMES = {0.6: "close-up", 1.0: "medium shot", 1.8: "wide shot"}
 
-# ── Chargement modèle (lazy — nécessite GPU pour la quantization 4-bit) ───────
-
-dtype = torch.bfloat16
-pipe = None
-
-
-def get_pipe():
-    global pipe
-    if pipe is None:
-        pipe = QwenImageEditPlusPipeline.from_pretrained(
-            "ovedrive/Qwen-Image-Edit-2511-4bit",
-            torch_dtype=dtype,
-            device_map="auto",
-        )
-    return pipe
-
 # ── Helpers ───────────────────────────────────────────────────────────────────
 
 def snap_to_nearest(value, options):
@@ -47,15 +32,21 @@ def build_camera_prompt(azimuth: float, elevation: float, distance: float) -> st
     az = snap_to_nearest(azimuth, AZIMUTHS)
     el = snap_to_nearest(elevation, ELEVATIONS)
     di = snap_to_nearest(distance, DISTANCES)
-    return f"Show this from {AZIMUTH_NAMES[az]}, {ELEVATION_NAMES[el]}, {DISTANCE_NAMES[di]}"
+    return f"<sks> {AZIMUTH_NAMES[az]}, {ELEVATION_NAMES[el]}, {DISTANCE_NAMES[di]}"
 
 
 def update_prompt_preview(azimuth, elevation, distance):
     return build_camera_prompt(azimuth, elevation, distance)
 
-# ── Inférence ZeroGPU ─────────────────────────────────────────────────────────
 
-@spaces.GPU(duration=120)
+def pil_to_data_uri(img: Image.Image) -> str:
+    buf = io.BytesIO()
+    img.save(buf, format="PNG")
+    b64 = base64.b64encode(buf.getvalue()).decode()
+    return f"data:image/png;base64,{b64}"
+
+# ── Inférence fal.ai ──────────────────────────────────────────────────────────
+
 def infer(
     image: Image.Image,
     azimuth: float,
@@ -64,24 +55,41 @@ def infer(
     seed: int,
     randomize_seed: bool,
 ):
+    if image is None:
+        raise gr.Error("Veuillez uploader une image source / Please upload a source image")
+
     if randomize_seed:
         seed = random.randint(0, 2**31 - 1)
 
     prompt = build_camera_prompt(azimuth, elevation, distance)
-    generator = torch.Generator(device="cpu").manual_seed(seed)
+    image_url = pil_to_data_uri(image)
+
+    os.environ["FAL_KEY"] = os.environ.get("FAL_KEY", "e5f4d316-d436-4b83-a427-bea6e535ebef:ab20bb07b0da7c4bcc1b96cec55f0d2e")
+
+    result = fal_client.run(
+        "fal-ai/qwen-image-edit",
+        arguments={
+            "image_url": image_url,
+            "prompt": prompt,
+            "seed": seed,
+            "image_size": {"width": 1024, "height": 1024},
+            "num_inference_steps": 4,
+            "guidance_scale": 1.0,
+            "loras": [
+                {
+                    "path": "fal/Qwen-Image-Edit-2511-Multiple-Angles-LoRA",
+                    "scale": 1.0,
+                }
+            ],
+        },
+    )
 
-    result = get_pipe()(
-        image=[image],
-        prompt=prompt,
-        height=1024,
-        width=1024,
-        num_inference_steps=20,
-        guidance_scale=3.5,
-        generator=generator,
-        num_images_per_prompt=1,
-    ).images[0]
+    image_url_out = result["images"][0]["url"]
+    import urllib.request
+    with urllib.request.urlopen(image_url_out) as resp:
+        out_img = Image.open(io.BytesIO(resp.read())).convert("RGB")
 
-    return result, seed, prompt
+    return out_img, seed, prompt
 
 # ── UI Gradio ─────────────────────────────────────────────────────────────────
 
@@ -116,7 +124,7 @@ with gr.Blocks(title="Angle Studio") as demo:
 
             prompt_preview = gr.Textbox(
                 label="Prompt généré / Generated prompt",
-                value="Show this from front view, eye-level shot, medium shot",
+                value="<sks> front view, eye-level shot, medium shot",
                 interactive=False,
             )
 
@@ -154,4 +162,4 @@ with gr.Blocks(title="Angle Studio") as demo:
         outputs=[output_image, output_seed, session_images, gallery],
     )
 
-demo.launch(theme=gr.themes.Base())
+demo.launch()