Update app.py

app.py

@@ -7,8 +7,7 @@ import numpy as np
 import torch
 from PIL import Image
 from diffusers import DiffusionPipeline, StableDiffusionXLPipeline, EDMEulerScheduler, StableDiffusionXLInstructPix2PixPipeline, AutoencoderKL
-from huggingface_hub import hf_hub_download
-from huggingface_hub import InferenceClient
+from huggingface_hub import hf_hub_download, InferenceClient
 
 vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
 pipe = StableDiffusionXLPipeline.from_pretrained("fluently/Fluently-XL-Final", torch_dtype=torch.float16, vae=vae)
@@ -75,7 +74,11 @@ def king(type ,
         inputs = processor(raw_image, return_tensors="pt").to("cuda", torch.float16)
         out = model.generate(**inputs, min_length=10, max_length=20)
         caption = processor.decode(out[0], skip_special_tokens=True)
-        instructions = f"{instruction} {caption} {instruction}"
+        client1 = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
+        system_instructions1 = "<s>[SYSTEM] Your task is to modify prompt by USER with edit text, and create new prompt for image generation, reply with prompt only, Your task is to reply with final prompt only. [USER]"
+        formatted_prompt = f"{system_instructions1} {caption} [EDIT] {instruction} [FINAL_PROMPT]"
+        stream = client1.text_generation(formatted_prompt, max_new_tokens=50, stream=True, details=True, return_full_text=False)
+        instructions = "".join([response.token.text for response in stream if response.token.text != "</s>"])
         print(instructions)
         if randomize_seed:
             seed = random.randint(0, 99999)