fix: auto-fix ruff linting errors and remove unsupported upload-artifact

handler_base/config.py

@@ -3,67 +3,69 @@ Configuration management using Pydantic Settings.
 
 Environment variables are automatically loaded and validated.
 """
+
 from typing import Optional
+
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
 
 class Settings(BaseSettings):
     """Base settings for all handler services."""
-    
+
     model_config = SettingsConfigDict(
         env_file=".env",
         env_file_encoding="utf-8",
         extra="ignore",
     )
-    
+
     # Service identification
     service_name: str = "handler"
     service_version: str = "1.0.0"
     service_namespace: str = "ai-ml"
     deployment_env: str = "production"
-    
+
     # NATS configuration
     nats_url: str = "nats://nats.ai-ml.svc.cluster.local:4222"
     nats_user: Optional[str] = None
     nats_password: Optional[str] = None
     nats_queue_group: Optional[str] = None
-    
+
     # Redis/Valkey configuration
     redis_url: str = "redis://valkey.ai-ml.svc.cluster.local:6379"
     redis_password: Optional[str] = None
-    
+
     # Milvus configuration
     milvus_host: str = "milvus.ai-ml.svc.cluster.local"
     milvus_port: int = 19530
     milvus_collection: str = "documents"
-    
+
     # Service endpoints
     embeddings_url: str = "http://embeddings-predictor.ai-ml.svc.cluster.local"
     reranker_url: str = "http://reranker-predictor.ai-ml.svc.cluster.local"
     llm_url: str = "http://vllm-predictor.ai-ml.svc.cluster.local"
     tts_url: str = "http://tts-predictor.ai-ml.svc.cluster.local"
     stt_url: str = "http://whisper-predictor.ai-ml.svc.cluster.local"
-    
+
     # OpenTelemetry configuration
     otel_enabled: bool = True
     otel_endpoint: str = "http://opentelemetry-collector.observability.svc.cluster.local:4317"
     otel_use_http: bool = False
-    
+
     # HyperDX configuration
     hyperdx_enabled: bool = False
     hyperdx_api_key: Optional[str] = None
     hyperdx_endpoint: str = "https://in-otel.hyperdx.io"
-    
+
     # MLflow configuration
     mlflow_tracking_uri: str = "http://mlflow.mlflow.svc.cluster.local:80"
     mlflow_experiment_name: Optional[str] = None
     mlflow_enabled: bool = True
-    
+
     # Health check configuration
     health_port: int = 8080
     health_path: str = "/health"
     ready_path: str = "/ready"
-    
+
     # Timeouts (seconds)
     http_timeout: float = 60.0
     nats_timeout: float = 30.0
@@ -71,14 +73,14 @@ class Settings(BaseSettings):
 
 class EmbeddingsSettings(Settings):
     """Settings for embeddings service client."""
-    
+
     embeddings_model: str = "bge"
     embeddings_batch_size: int = 32
 
 
 class LLMSettings(Settings):
     """Settings for LLM service client."""
-    
+
     llm_model: str = "default"
     llm_max_tokens: int = 2048
     llm_temperature: float = 0.7
@@ -87,13 +89,13 @@ class LLMSettings(Settings):
 
 class TTSSettings(Settings):
     """Settings for TTS service client."""
-    
+
     tts_language: str = "en"
     tts_speaker: Optional[str] = None
 
 
 class STTSettings(Settings):
     """Settings for STT service client."""
-    
+
     stt_language: Optional[str] = None  # Auto-detect
     stt_task: str = "transcribe"  # or "translate"