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src/writing_studio/core/config.py

@@ -43,7 +43,6 @@ class Settings(BaseSettings):
 
     # Model Configuration
     default_model: str = Field(default="distilgpt2", description="Default HuggingFace model")
-    model_cache_dir: str = Field(default="./models", description="Model cache directory")
     max_model_length: int = Field(default=512, ge=1, description="Maximum model input length")
     default_max_length: int = Field(default=300, ge=1, description="Default generation length")
     default_num_sequences: int = Field(default=1, ge=1, description="Number of sequences")
@@ -91,7 +90,7 @@ class Settings(BaseSettings):
             return [origin.strip() for origin in v.split(",") if origin.strip()]
         return v
 
-    @field_validator("model_cache_dir", "log_file_path")
+    @field_validator("log_file_path")
     @classmethod
     def ensure_directory_exists(cls, v: str) -> str:
         """Ensure directory exists for file paths."""

src/writing_studio/services/model_service.py

@@ -58,10 +58,10 @@ class ModelService:
             start_time = time.time()
 
             # Load model with error handling
+            # Note: cache_dir is handled automatically by transformers
             self._current_model = pipeline(
                 "text-generation",
                 model=model_name,
-                cache_dir=settings.model_cache_dir,
             )
             self._current_model_name = model_name
 
@@ -119,13 +119,14 @@ class ModelService:
             logger.info(f"Generating text with model: {self._current_model_name}")
             start_time = time.time()
 
-            # Generate text
+            # Generate text with proper parameters
             result = self._current_model(
                 prompt,
                 max_length=params["max_length"],
                 num_return_sequences=params["num_sequences"],
                 do_sample=True,
                 temperature=params["temperature"],
+                pad_token_id=self._current_model.tokenizer.eos_token_id,  # Avoid warnings
             )
 
             generated_text = result[0]["generated_text"]