test pre integrate mistral

app.py

@@ -4,6 +4,10 @@ import random
 import spaces
 import torch
 from diffusers import DiffusionPipeline
+from huggingface_hub import InferenceClient
+
+client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
+
 
 dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -44,9 +48,8 @@ css="""
 with gr.Blocks(css=css) as demo:
     
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""# FLUX.1 [schnell]
-12B param rectified flow transformer distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/) for 4 step generation
-[[blog](https://blackforestlabs.ai/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-schnell)]
+        gr.Markdown(f"""# Text to Product
+        Using Mistral + Flux + Trellis
         """)
         
         with gr.Row():
@@ -61,9 +64,55 @@ with gr.Blocks(css=css) as demo:
             
             run_button = gr.Button("Run", scale=0)
         
+        refined_prompt = gr.Text(
+            label="Refined Prompt", 
+            show_label=False,
+            max_lines=10, 
+            placeholder="Prompt refined by Mistral", 
+            container=False
+            )
+
         result = gr.Image(label="Result", show_label=False)
         
-        with gr.Accordion("Advanced Settings", open=False):
+        with gr.Accordion("Advanced Settings istral", open=False):
+            gr.Slider(
+                label="Temperature",
+                value=0.9,
+                minimum=0.0,
+                maximum=1.0,
+                step=0.05,
+                interactive=True,
+                info="Higher values produce more diverse outputs",
+            ),
+            gr.Slider(
+                label="Max new tokens",
+                value=256,
+                minimum=0,
+                maximum=1048,
+                step=64,
+                interactive=True,
+                info="The maximum numbers of new tokens",
+            ),
+            gr.Slider(
+                label="Top-p (nucleus sampling)",
+                value=0.90,
+                minimum=0.0,
+                maximum=1,
+                step=0.05,
+                interactive=True,
+                info="Higher values sample more low-probability tokens",
+            ),
+            gr.Slider(
+                label="Repetition penalty",
+                value=1.2,
+                minimum=1.0,
+                maximum=2.0,
+                step=0.05,
+                interactive=True,
+                info="Penalize repeated tokens",
+            )
+        
+        with gr.Accordion("Advanced Settings Flux", open=False):
             
             seed = gr.Slider(
                 label="Seed",

requirements.txt

@@ -1,5 +1,7 @@
 --extra-index-url https://download.pytorch.org/whl/cu121
 
+huggingface_hub
+mistral_inference
 torch==2.4.0
 torchvision==0.19.0
 pillow==10.4.0