0.3 more inputs test

seed = random.randint(0, 2**32 - 1)
prompt = message.content[12:].strip()
number_of_images = 4
df.predict(prompt, "blur", seed,number_of_images,7.0, 'smart100',50, api_name="/generate64")

app.py

@@ -19,6 +19,8 @@ import time
 
 #todos
 #alert
+#stable diffusion upscale
+#buttons for deepfloydIF (1,2,3,4)
 
 # Get Gradio client
 jojogan = gradio_client.Client("akhaliq/JoJoGAN")
@@ -120,12 +122,16 @@ class MyClient(discord.Client):
             #(prompt, negative_prompt, seed, number_of_images, guidance_scale,custom_timesteps_1, number_of_inference_steps, api_name="/generate64") 
             #-> (stage_1_results, stage_1_param_path, stage_1_result_path)
 
+            # custom input
+            prompt = message.content[12:].strip()   
+            number_of_images = 4
+
             # random seed
             current_time = int(time.time())
             random.seed(current_time)
-            seed = random.randint(1, 10000)
+            seed = random.randint(0, 2**32 - 1)
             
-            stage_1_results, stage_1_param_path, stage_1_result_path = df.predict("llama", "blur", seed,1,7.0, 'smart100',50, api_name="/generate64")
+            stage_1_results, stage_1_param_path, stage_1_result_path = df.predict(prompt, "blur", seed,number_of_images,7.0, 'smart100',50, api_name="/generate64")
 
             #stage_1_results, stage_1_param_path, stage_1_result_path = df.predict("gradio written on a wall", "blur", 1,1,7.0, 'smart100',50, api_name="/generate64")