add --index-url for installing pre-built wheels

README.md

@@ -24,7 +24,7 @@ Detailed API documentation is available [here](docs/index.html).
 
 ## Installation
 
-**GPU version(optional)** 
+**GPU version(optional)**
 
 check if you have GPU acceleration (torch required)
 <details>
@@ -40,16 +40,24 @@ check if you have GPU acceleration (torch required)
   ```
   CMAKE_ARGS="-DGGML_CUDA=on -DSD_CUBLAS=ON" pip install nexaai-gpu
   ```
+  Or you prefer to install our pre-built wheel:
+  ```bash
+  pip install nexaai-cuda --index-url https://nexaai.github.io/nexa-sdk/whl/cu124 --extra-index-url https://pypi.org/simple
+  ```
 </details>
 <details>
   <summary>Apple M Chip:</summary>
   Apple icon -> about this mac -> Graphics
-  
+
   if True:
 
   ```
   CMAKE_ARGS="-DGGML_METAL=on -DSD_METAL=ON" pip install nexaai-gpu
   ```
+  Or you prefer to install our pre-built wheel:
+  ```bash
+  pip install nexaai-metal --index-url https://nexaai.github.io/nexa-sdk/whl/metal --extra-index-url https://pypi.org/simple
+  ```
 </details>
 
 <details>
@@ -77,7 +85,12 @@ check if you have GPU acceleration (torch required)
   ```
   pip install nexaai
   ```
-<details>
+</details>
+
+Or you prefer to install the pre-built wheel:
+```bash
+pip install nexaai --index-url https://nexaai.github.io/nexa-sdk/whl/cpu --extra-index-url https://pypi.org/simple
+```
 
 ## Nexa CLI commands
 

nexa/gguf/nexa_inference_image.py

@@ -43,7 +43,7 @@ class NexaImageInference:
         streamlit (bool): Run the inference in Streamlit UI.
 
     """
-    
+
 
     def __init__(self, model_path, **kwargs):
         self.model_path = None
@@ -81,7 +81,7 @@ def __init__(self, model_path, **kwargs):
                 logging.error("Failed to load the model or pipeline.")
                 exit(1)
 
-    # @SpinningCursorAnimation()
+    @SpinningCursorAnimation()
     def _load_model(self, model_path: str):
         with suppress_stdout_stderr():
             from nexa.gguf.sd.stable_diffusion import StableDiffusion
@@ -108,9 +108,9 @@ def _save_images(self, images):
             file_path = os.path.join(output_dir, file_name)
             image.save(file_path)
             logging.info(f"\nImage {i+1} saved to: {file_path}")
-    
-    def txt2img(self, 
-                prompt, 
+
+    def txt2img(self,
+                prompt,
                 negative_prompt="",
                 cfg_scale=7.5,
                 width=512,
@@ -151,7 +151,7 @@ def run_txt2img(self):
                 )
                 try:
                     images = self.txt2img(
-                        prompt, 
+                        prompt,
                         negative_prompt,
                         cfg_scale=self.params["guidance_scale"],
                         width=self.params["width"],
@@ -169,9 +169,9 @@ def run_txt2img(self):
             except Exception as e:
                 logging.error(f"Error during generation: {e}", exc_info=True)
 
-    def img2img(self, 
-                image_path, 
-                prompt, 
+    def img2img(self,
+                image_path,
+                prompt,
                 negative_prompt="",
                 cfg_scale=7.5,
                 width=512,
@@ -213,8 +213,8 @@ def run_img2img(self):
                 negative_prompt = nexa_prompt(
                     "Enter your negative prompt (press Enter to skip): "
                 )
-                images = self.img2img(image_path, 
-                                      prompt, 
+                images = self.img2img(image_path,
+                                      prompt,
                                       negative_prompt,
                                       cfg_scale=self.params["guidance_scale"],
                                       width=self.params["width"],
@@ -224,7 +224,7 @@ def run_img2img(self):
                                       control_cond=self.params.get("control_image_path", ""),
                                         control_strength=self.params.get("control_strength", 0.9),
                                     )
-                
+
                 self._save_images(images)
             except KeyboardInterrupt:
                 print(EXIT_REMINDER)

nexa/gguf/nexa_inference_text.py

@@ -40,7 +40,7 @@ class NexaTextInference:
         top_k (int): Top-k sampling parameter.
         top_p (float): Top-p sampling parameter
     """
-    
+
     def __init__(self, model_path, stop_words=None, **kwargs):
         self.params = DEFAULT_TEXT_GEN_PARAMS
         self.params.update(kwargs)
@@ -98,7 +98,7 @@ def create_embedding(
         """
         return self.model.create_embedding(input)
 
-    # @SpinningCursorAnimation()
+    @SpinningCursorAnimation()
     def _load_model(self):
         logging.debug(f"Loading model from {self.downloaded_path}")
         start_time = time.time()
@@ -140,7 +140,7 @@ def _load_model(self):
 
     def run(self):
         """
-        CLI interactive session. Not for SDK. 
+        CLI interactive session. Not for SDK.
         """
         while True:
             generated_text = ""
@@ -189,7 +189,7 @@ def run(self):
             except Exception as e:
                 logging.error(f"Error during generation: {e}", exc_info=True)
             print("\n")
-    
+
     def create_chat_completion(self, messages, temperature=0.7, max_tokens=2048, top_k=50, top_p=1.0, stream=False, stop=None):
         """
         Used for SDK. Generate completion for a chat conversation.
@@ -207,7 +207,7 @@ def create_chat_completion(self, messages, temperature=0.7, max_tokens=2048, top
             Iterator: Iterator for the completion.
         """
         return self.model.create_chat_completion(messages=messages, temperature=temperature, max_tokens=max_tokens, top_k=top_k, top_p=top_p, stream=stream, stop=stop)
-    
+
     def create_completion(self, prompt, temperature=0.7, max_tokens=2048, top_k=50, top_p=1.0, echo=False, stream=False, stop=None):
         """
         Used for SDK. Generate completion for a given prompt.

nexa/gguf/nexa_inference_vlm.py

@@ -86,7 +86,7 @@ class NexaVLMInference:
     top_k (int): Top-k sampling parameter.
     top_p (float): Top-p sampling parameter
     """
-    
+
 
     def __init__(self, model_path, stop_words=None, **kwargs):
         self.params = DEFAULT_TEXT_GEN_PARAMS
@@ -146,7 +146,7 @@ def __init__(self, model_path, stop_words=None, **kwargs):
                 )
                 exit(1)
 
-    # @SpinningCursorAnimation()
+    @SpinningCursorAnimation()
     def _load_model(self):
         logging.debug(f"Loading model from {self.downloaded_path}")
         start_time = time.time()
@@ -240,18 +240,18 @@ def run(self):
             except Exception as e:
                 logging.error(f"Error during generation: {e}", exc_info=True)
             print("\n")
-    
-    def create_chat_completion(self, 
-                            messages, 
-                            max_tokens:int = 2048, 
+
+    def create_chat_completion(self,
+                            messages,
+                            max_tokens:int = 2048,
                             temperature: float = 0.2,
                             top_p: float = 0.95,
                             top_k: int = 40,
-                            stream=False, 
+                            stream=False,
                             stop=[]):
         """
         Generate text completion for a given chat prompt.
-        
+
         Args:
             messages (list): List of messages in the chat prompt.
             temperature (float): Temperature for sampling.
@@ -260,7 +260,7 @@ def create_chat_completion(self,
             top_p (float): Top-p sampling parameter.
             stream (bool): Stream the output.
             stop (list): List of stop words for early stopping.
-        
+
         Returns:
             Iterator: An iterator of the generated text completion
             return format:
@@ -285,9 +285,9 @@ def create_chat_completion(self,
                     "prompt_tokens": 57,
                     "total_tokens": 74
                 }
-            }          
-            usage: message = completion.choices[0].message.content  
-            
+            }
+            usage: message = completion.choices[0].message.content
+
         """
         return self.model.create_chat_completion(
             messages=messages,

nexa/gguf/nexa_inference_voice.py

@@ -69,7 +69,7 @@ def __init__(self, model_path, **kwargs):
                 exit(1)
 
 
-    # @SpinningCursorAnimation()
+    @SpinningCursorAnimation()
     def _load_model(self):
         from faster_whisper import WhisperModel
 
@@ -91,7 +91,7 @@ def run(self):
                 print(EXIT_REMINDER)
             except Exception as e:
                 logging.error(f"Error during text generation: {e}", exc_info=True)
-    
+
     def transcribe(self, audio, **kwargs):
         """
         Transcribe the audio file.
@@ -171,7 +171,7 @@ def transcribe(self, audio, **kwargs):
             audio,
             **kwargs,
         )
-        
+
 
     def _transcribe_audio(self, audio_path):
         logging.debug(f"Transcribing audio from: {audio_path}")