add precommit

examples/basic/text_generation.py

@@ -7,40 +7,43 @@ with a single AR (Autoregressive) stage.
 """
 
 import asyncio
-from vllm_omni.entrypoints.omni_llm import OmniLLM, AsyncOmniLLM
+
 from vllm_omni.config import create_ar_stage_config
+from vllm_omni.entrypoints.omni_llm import AsyncOmniLLM, OmniLLM
 
 
 def sync_example():
     """Synchronous usage example."""
     print("=== Synchronous vLLM-omni Example ===")
-    
+
     # Create a simple AR stage configuration
     stage_config = create_ar_stage_config(
         stage_id=0,
         model_path="Qwen/Qwen3-0.6B",
         input_modalities=["text"],
-        output_modalities=["text"]
+        output_modalities=["text"],
     )
-    
+
     # Initialize OmniLLM
     omni_llm = OmniLLM([stage_config])
-    
+
     # Prepare stage arguments
-    stage_args = [{
-        "prompt": "Hello, how are you today?",
-        "max_tokens": 50,
-        "temperature": 0.7
-    }]
-    
+    stage_args = [
+        {
+            "prompt": "Hello, how are you today?",
+            "max_tokens": 50,
+            "temperature": 0.7,
+        }
+    ]
+
     # Generate text
     print(f"Input: {stage_args[0]['prompt']}")
     outputs = omni_llm.generate(stage_args)
-    
+
     # Display results
     for i, output in enumerate(outputs):
         print(f"Output {i}:")
-        if hasattr(output, 'outputs') and output.outputs:
+        if hasattr(output, "outputs") and output.outputs:
             for completion in output.outputs:
                 print(f"  Text: {completion.text}")
                 print(f"  Finished: {completion.finish_reason != 'length'}")
@@ -50,33 +53,35 @@ def sync_example():
 async def async_example():
     """Asynchronous usage example."""
     print("\n=== Asynchronous vLLM-omni Example ===")
-    
+
     # Create a simple AR stage configuration
     stage_config = create_ar_stage_config(
         stage_id=0,
         model_path="Qwen/Qwen3-0.6B",
         input_modalities=["text"],
-        output_modalities=["text"]
+        output_modalities=["text"],
     )
-    
+
     # Initialize AsyncOmniLLM
     omni_llm = AsyncOmniLLM([stage_config])
-    
+
     # Prepare stage arguments
-    stage_args = [{
-        "prompt": "What is artificial intelligence?",
-        "max_tokens": 100,
-        "temperature": 0.8
-    }]
-    
+    stage_args = [
+        {
+            "prompt": "What is artificial intelligence?",
+            "max_tokens": 100,
+            "temperature": 0.8,
+        }
+    ]
+
     # Generate text asynchronously
     print(f"Input: {stage_args[0]['prompt']}")
     outputs = await omni_llm.generate_async(stage_args)
-    
+
     # Display results
     for i, output in enumerate(outputs):
         print(f"Output {i}:")
-        if hasattr(output, 'outputs') and output.outputs:
+        if hasattr(output, "outputs") and output.outputs:
             for completion in output.outputs:
                 print(f"  Text: {completion.text}")
                 print(f"  Finished: {completion.finish_reason != 'length'}")
@@ -86,36 +91,32 @@ async def async_example():
 def multi_prompt_example():
     """Example with multiple prompts."""
     print("\n=== Multi-Prompt Example ===")
-    
+
     # Create stage configuration
     stage_config = create_ar_stage_config(
         stage_id=0,
         model_path="Qwen/Qwen3-0.6B",
         input_modalities=["text"],
-        output_modalities=["text"]
+        output_modalities=["text"],
     )
-    
+
     # Initialize OmniLLM
     omni_llm = OmniLLM([stage_config])
-    
+
     # Multiple prompts
     prompts = [
         "Tell me a joke",
         "What's the weather like?",
-        "Explain quantum computing"
+        "Explain quantum computing",
     ]
-    
+
     for prompt in prompts:
         print(f"\nInput: {prompt}")
-        stage_args = [{
-            "prompt": prompt,
-            "max_tokens": 30,
-            "temperature": 0.9
-        }]
-        
+        stage_args = [{"prompt": prompt, "max_tokens": 30, "temperature": 0.9}]
+
         outputs = omni_llm.generate(stage_args)
-        
-        if outputs and hasattr(outputs[0], 'outputs') and outputs[0].outputs:
+
+        if outputs and hasattr(outputs[0], "outputs") and outputs[0].outputs:
             completion = outputs[0].outputs[0]
             print(f"Output: {completion.text}")
 
@@ -123,15 +124,15 @@ def multi_prompt_example():
 if __name__ == "__main__":
     print("vLLM-omni Simple Usage Examples")
     print("=" * 40)
-    
+
     # Run synchronous example
     sync_example()
-    
+
     # Run asynchronous example
     asyncio.run(async_example())
-    
+
     # Run multi-prompt example
     multi_prompt_example()
-    
+
     print("\n" + "=" * 40)
     print("Examples completed!")