didi-lot1-ai/ai_platform/modules/rerank/deploy/docker-compose.yml

131 lines
4.2 KiB
YAML

# Rerank Module - Docker Compose Configuration
#
# Port Allocation (x42xx = Reranking):
# 14200 - Rerank API (Prod)
# 54200 - Rerank API (Dev)
# 14201/54201 - vLLM Rerank Server
# 14210/54210 - llama.cpp Rerank Server
#
# Profiles:
# api - API server only (uses external rerank 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:
# ==========================================================================
# Rerank API Server
# ==========================================================================
rerank-api:
container_name: didiAI-rerank-api
image: didiai-rerank-api
build:
context: ..
dockerfile: deploy/Dockerfile
ports:
- "${RERANK_PORT:-14200}:${RERANK_PORT:-14200}"
networks:
- deploy_default
environment:
- RERANK_PORT=${RERANK_PORT:-14200}
- RERANK_EXTERNAL_URL=${RERANK_EXTERNAL_URL}
- RERANK_DEFAULT_BACKEND=${RERANK_DEFAULT_BACKEND}
- RERANK_ENABLE_VLLM=${RERANK_ENABLE_VLLM}
- RERANK_ENABLE_LLAMACPP=${RERANK_ENABLE_LLAMACPP}
- RERANK_VLLM_BASE_URL=http://didiAI-rerank-vllm:14201
- RERANK_LLAMACPP_BASE_URL=http://didiAI-rerank-llamacpp:8080
- RERANK_API_TOKENS=${RERANK_API_TOKENS:-}
- RERANK_DASHBOARD_URL=${RERANK_DASHBOARD_URL:-http://didiAI-dashboard:51300}
healthcheck:
test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:${RERANK_PORT:-14200}/health')"]
interval: 30s
timeout: 10s
retries: 3
start_period: 30s
restart: unless-stopped
profiles:
- api
- vllm
- llamacpp
# ==========================================================================
# vLLM Rerank Server
# ==========================================================================
# Cross-encoder model using vLLM with --task score (v0.8.x syntax)
vllm-rerank:
container_name: didiAI-rerank-vllm
image: vllm/vllm-openai:v0.8.5
ports:
- "${RERANK_VLLM_PORT:-14201}:14201"
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=${RERANK_VLLM_GPU:-0}
command: >
--model ${RERANK_VLLM_MODEL:-BAAI/bge-reranker-v2-m3}
--host 0.0.0.0
--port 14201
--task score
--trust-remote-code
--max-model-len ${RERANK_VLLM_MAX_LEN:-8192}
--gpu-memory-utilization ${RERANK_VLLM_GPU_UTIL:-0.50}
--disable-log-requests
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids: ['${RERANK_VLLM_GPU:-0}']
capabilities: [gpu]
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:14201/health"]
interval: 30s
timeout: 10s
retries: 10
start_period: 300s
restart: unless-stopped
profiles:
- vllm
# ==========================================================================
# llama.cpp Rerank Server
# ==========================================================================
# Cross-encoder model using llama.cpp with --reranking
llamacpp-rerank:
container_name: didiAI-rerank-llamacpp
image: ghcr.io/ggml-org/llama.cpp:server-b4769
ports:
- "${RERANK_LLAMACPP_PORT:-14210}:8080"
networks:
- deploy_default
volumes:
- ${MODELS_DIR:-/cai2_ds_storage/models}:/models:ro
command: >
--model /models/${RERANK_LLAMACPP_MODEL:-bge-reranker-v2-m3-q4_k_m.gguf}
--host 0.0.0.0
--port 8080
--reranking
--ctx-size ${RERANK_LLAMACPP_CTX:-8192}
--threads ${RERANK_LLAMACPP_THREADS:-4}
--parallel ${RERANK_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