using LLM for sentiment analysis

model-runner.env

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+# Docker Model Runner Environment Configuration
+# Copy values to your main .env file or use with --env-file
+
+# AMD GPU Configuration
+HSA_OVERRIDE_GFX_VERSION=11.0.0
+GPU_LAYERS=35
+THREADS=8
+BATCH_SIZE=512
+CONTEXT_SIZE=4096
+
+# API Configuration
+MODEL_RUNNER_PORT=11434
+LLAMA_CPP_PORT=8000
+METRICS_PORT=9090
+
+# Model Configuration
+DEFAULT_MODEL=ai/smollm2:135M-Q4_K_M
+MODEL_CACHE_DIR=/app/data/models
+MODEL_CONFIG_DIR=/app/data/config
+
+# Network Configuration
+MODEL_RUNNER_NETWORK=model-runner-network
+MODEL_RUNNER_HOST=0.0.0.0
+
+# Performance Tuning
+MAX_CONCURRENT_REQUESTS=10
+REQUEST_TIMEOUT=300
+KEEP_ALIVE=300
+
+# Logging
+LOG_LEVEL=info
+LOG_FORMAT=json
+
+# Health Check
+HEALTH_CHECK_INTERVAL=30s
+HEALTH_CHECK_TIMEOUT=10s
+HEALTH_CHECK_RETRIES=3
+HEALTH_CHECK_START_PERIOD=40s