Update app.py

app.py

@@ -1,23 +1,19 @@
 import torch
 import gradio as gr
-from diffusers import Flux2Pipeline
-
-pipe = Flux2Pipeline.from_pretrained(
-    "black-forest-labs/FLUX.2-klein-4B",
-    transformer=None,
-    vae=None,
-    scheduler=None,
-    safety_checker=None,
-    feature_extractor=None,
-)
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Le vrai encodeur texte FLUX (Mistral-3-Small)
+MODEL_ID = "black-forest-labs/FLUX.2-dev/text_encoder"
 
-tokenizer = pipe.tokenizer
-text_encoder = pipe.text_encoder
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+text_encoder = AutoModelForCausalLM.from_pretrained(MODEL_ID)
 
 def encode_text(prompt: str):
     inputs = tokenizer(
         prompt,
         return_tensors="pt",
+        padding=True,
+        truncation=True,
         max_length=512,
     )