Livrare LOT 1 - Didi

ai_platform/modules/embeddings/deploy/docker-compose.yml

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+# Embeddings Module - Docker Compose Configuration
+#
+# Port Allocation (x41xx = Embeddings):
+#   14100 - Embeddings API (Prod)
+#   54100 - Embeddings API (Dev)
+#   14101/54101 - vLLM Embedding Server
+#   14110/54110 - llama.cpp Embedding Server
+#
+# Profiles:
+#   api      - API server only (uses external embedding servers)
+#   vllm     - API + vLLM server (GPU required)
+#   llamacpp - API + llama.cpp server
+#
+# Naming Convention: didiAI-{module}-{service}
+#
+# Network:
+#   Uses deploy_default network (shared with other modules)
+
+networks:
+  deploy_default:
+    external: true
+
+services:
+  # ==========================================================================
+  # Embeddings API Server
+  # ==========================================================================
+  embeddings-api:
+    container_name: didiAI-embeddings-api
+    image: didiai-embeddings-api
+    build:
+      context: ..
+      dockerfile: deploy/Dockerfile
+    ports:
+      - "${EMB_PORT:-14100}:${EMB_PORT:-14100}"
+    networks:
+      - deploy_default
+    environment:
+      - EMB_PORT=${EMB_PORT:-14100}
+      - EMB_EXTERNAL_URL=${EMB_EXTERNAL_URL}
+      - EMB_DEFAULT_BACKEND=${EMB_DEFAULT_BACKEND}
+      - EMB_ENABLE_VLLM=${EMB_ENABLE_VLLM}
+      - EMB_ENABLE_LLAMACPP=${EMB_ENABLE_LLAMACPP}
+      - EMB_VLLM_BASE_URL=http://didiAI-embeddings-vllm:14101
+      - EMB_LLAMACPP_BASE_URL=http://didiAI-embeddings-llamacpp:8080
+      - EMB_API_TOKENS=${EMB_API_TOKENS:-}
+      - EMB_DASHBOARD_URL=${EMB_DASHBOARD_URL:-http://didiAI-dashboard:51300}
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:${EMB_PORT:-14100}/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 30s
+    restart: unless-stopped
+    profiles:
+      - api
+      - vllm
+      - llamacpp
+
+  # ==========================================================================
+  # vLLM Embedding Server
+  # ==========================================================================
+  # Embedding model using vLLM with --task embed (v0.8.x syntax)
+  vllm-embed:
+    container_name: didiAI-embeddings-vllm
+    image: vllm/vllm-openai:v0.8.5
+    ports:
+      - "${EMB_VLLM_PORT:-14101}:14101"
+    networks:
+      - deploy_default
+    volumes:
+      - ${HF_CACHE_DIR:-/cai2_ds_storage/hf_cache}:/root/.cache/huggingface
+    environment:
+      - HF_HOME=/root/.cache/huggingface
+      - HUGGING_FACE_HUB_TOKEN=${HF_TOKEN:-}
+      - CUDA_VISIBLE_DEVICES=${EMB_VLLM_GPU:-0}
+    command: >
+      --model ${EMB_VLLM_MODEL:-BAAI/bge-m3}
+      --host 0.0.0.0
+      --port 14101
+      --task embed
+      --trust-remote-code
+      --max-model-len ${EMB_VLLM_MAX_LEN:-8192}
+      --gpu-memory-utilization ${EMB_VLLM_GPU_UTIL:-0.50}
+      --disable-log-requests
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              device_ids: ['${EMB_VLLM_GPU:-0}']
+              capabilities: [gpu]
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:14101/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 10
+      start_period: 300s
+    restart: unless-stopped
+    profiles:
+      - vllm
+
+  # ==========================================================================
+  # llama.cpp Embedding Server
+  # ==========================================================================
+  # Embedding model using llama.cpp with --embedding
+  llamacpp-embed:
+    container_name: didiAI-embeddings-llamacpp
+    image: ghcr.io/ggml-org/llama.cpp:server-b4769
+    ports:
+      - "${EMB_LLAMACPP_PORT:-14110}:8080"
+    networks:
+      - deploy_default
+    volumes:
+      - ${MODELS_DIR:-/cai2_ds_storage/models}:/models:ro
+    command: >
+      --model /models/${EMB_LLAMACPP_MODEL:-bge-m3-q4_k_m.gguf}
+      --host 0.0.0.0
+      --port 8080
+      --embedding
+      --ctx-size ${EMB_LLAMACPP_CTX:-8192}
+      --threads ${EMB_LLAMACPP_THREADS:-4}
+      --parallel ${EMB_LLAMACPP_PARALLEL:-4}
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 60s
+    restart: unless-stopped
+    profiles:
+      - llamacpp