Added a very simple GUI using Kivy.

.gitignore

@@ -13,3 +13,5 @@
 *.pyc
 *.safetensors
 *.json
+
+request_history.db

requirements.txt

@@ -1,10 +1,32 @@
-mlx>=0.16.0
-numpy>=2.0.1
+certifi>=2024.8.30
+charset-normalizer>=3.3.2
+docutils>=0.21.2
+filelock>=3.15.4
+fsspec>=2024.9.0
+huggingface-hub>=0.24.6
+idna>=3.8
+Jinja2>=3.1.4
+Kivy>=2.3.0
+Kivy-Garden>=0.1.5
+MarkupSafe>=2.1.5
+mlx>=0.17.2
+mpmath>=1.3.0
+networkx>=3.3
+numpy>=2.1.1
+packaging>=24.1
+piexif>=1.1.3
 pillow>=10.4.0
-transformers>=4.44.0
+Pygments>=2.18.0
+PyYAML>=6.0.2
+regex>=2024.7.24
+requests>=2.32.3
+safetensors>=0.4.5
 sentencepiece>=0.2.0
-torch>=2.3.1
+setuptools>=74.1.2
+sympy>=1.13.2
+tokenizers==0.19.1
+torch>=2.4.1
 tqdm>=4.66.5
-huggingface-hub>=0.24.5
-safetensors>=0.4.4
-piexif>=1.1.3
+transformers>=4.44.2
+typing_extensions>=4.12.2
+urllib3>=2.2.2

src/mflux/flux/flux.py

@@ -70,7 +70,7 @@ def __init__(
         if weights.quantization_level is not None:
             self._set_model_weights(weights)
 
-    def generate_image(self, seed: int, prompt: str, config: Config = Config()) -> Image:
+    def generate_image(self, seed: int, prompt: str, config: Config = Config(), progress_callback=None) -> Image:
         # Create a new runtime config based on the model type and input parameters
         config = RuntimeConfig(config, self.model_config)
         time_steps = tqdm(range(config.num_inference_steps))
@@ -103,6 +103,9 @@ def generate_image(self, seed: int, prompt: str, config: Config = Config()) -> I
 
             # Evaluate to enable progress tracking
             mx.eval(latents)
+            # Call the progress callback if provided
+            if progress_callback:
+                progress_callback(t + 1, config.num_inference_steps)
 
         # 5. Decode the latent array and return the image
         latents = Flux1._unpack_latents(latents, config.height, config.width)

src/mflux/generate.py

@@ -2,6 +2,7 @@
 import os
 import sys
 import time
+from tqdm import tqdm
 
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 
@@ -49,12 +50,21 @@ def main():
             height=args.height,
             width=args.width,
             guidance=args.guidance,
-        )
+        ),
+        progress_callback=tqdm_progress(args.steps,args.output)
     )
 
     # Save the image
     image.save(path=args.output, export_json_metadata=args.metadata)
 
 
+def tqdm_progress(total_steps,output_filename):
+    pbar = tqdm(total=total_steps, desc=output_filename)
+    def update(step, _):
+        pbar.update(1)
+        if step == total_steps:
+            pbar.close()
+    return update
+
 if __name__ == '__main__':
     main()