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feifeilib/feifeifluxapi.py

@@ -7,10 +7,10 @@ from feifeilib.feifeisharpened import feifeisharpened
 
 client = InferenceClient("black-forest-labs/FLUX.1-dev", token=os.getenv('HF_TOKEN'))
 client.headers["x-use-cache"] = "0"
-MAX_SEED = np.iinfo(np.int32).maxv
+MAX_SEED = np.iinfo(np.int32).max
 
-def feifeifluxapi(randomize_seed=False,seed=random.randint(0, MAX_SEED),prompt,quality_select=False,sharpened_select=False, styles_Radio=["(None)"],FooocusExpansion_select=False,height=1152,width=896,guidance_scale=3.5,num_strength=0.35):
-    prompt,generator = feifeiprompt(randomize_seed,seed,prompt,quality_select,styles_Radio,FooocusExpansion_select)
+def feifeifluxapi(prompt, randomize_seed=False, seed=random.randint(0, MAX_SEED), quality_select=False, sharpened_select=False, styles_Radio=["(None)"], FooocusExpansion_select=False, height=1152, width=896, guidance_scale=3.5, num_strength=0.35):
+    prompt, generator = feifeiprompt(randomize_seed, seed, prompt, quality_select, styles_Radio, FooocusExpansion_select)
     image = client.text_to_image(
         prompt=prompt,
         height=height,
@@ -18,5 +18,5 @@ def feifeifluxapi(randomize_seed=False,seed=random.randint(0, MAX_SEED),prompt,q
         guidance_scale=guidance_scale
     )
     if sharpened_select:
-        feifeisharpened(image,num_strength)
-    return image
+        feifeisharpened(image, num_strength)
+    return image