feat: initial commit

llm/docker-compose.yml

@@ -0,0 +1,62 @@
+# Backendy LLM uruchamiane kontenerowo. Sterowane profilami, żeby jeden plik
+# obsłużył kilka wariantów i żeby `docker compose up` bez profilu nic nie robił.
+#
+#   docker compose --profile vllm-gpu up -d      # Linux + NVIDIA
+#   docker compose --profile ollama   up -d      # awaryjnie, obie platformy
+#
+# Zwykle nie wywołujesz tego wprost - robi to `task llm:up`.
+
+name: agentic-codemod-llm
+
+services:
+
+  vllm:
+    profiles: ["vllm-gpu"]
+    image: vllm/vllm-openai:${VLLM_IMAGE_TAG:-latest}
+    command: >
+      --model ${LLM_SERVE_MODEL:-Qwen/Qwen3-4B-Instruct-2507}
+      --max-model-len=16384
+      --enable-auto-tool-choice
+      --tool-call-parser=hermes
+      --gpu-memory-utilization=${VLLM_GPU_UTIL:-0.90}
+    ports:
+      - "${LLM_PORT:-8000}:8000"
+    volumes:
+      # Cache modeli poza kontenerem - restart nie oznacza ponownego pobierania.
+      - ${HF_CACHE:-${HOME}/.cache/huggingface}:/root/.cache/huggingface
+    environment:
+      HUGGING_FACE_HUB_TOKEN: ${HUGGING_FACE_HUB_TOKEN:-}
+    # vLLM używa pamięci dzielonej do komunikacji między workerami
+    ipc: host
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: all
+              capabilities: [gpu]
+    healthcheck:
+      test: ["CMD-SHELL", "python3 -c \"import urllib.request;urllib.request.urlopen('http://localhost:8000/health')\""]
+      interval: 15s
+      timeout: 5s
+      retries: 40
+      start_period: 300s
+    restart: unless-stopped
+
+  ollama:
+    profiles: ["ollama"]
+    image: ollama/ollama:${OLLAMA_IMAGE_TAG:-latest}
+    ports:
+      - "${OLLAMA_PORT:-11434}:11434"
+    volumes:
+      - ollama-models:/root/.ollama
+    healthcheck:
+      test: ["CMD-SHELL", "ollama list >/dev/null 2>&1"]
+      interval: 10s
+      timeout: 5s
+      retries: 30
+      start_period: 30s
+    restart: unless-stopped
+
+volumes:
+  ollama-models: