pyr0ball
4d66c04d1e
- Dockerfile.finetune: PyTorch 2.3/CUDA 12.1 base + unsloth + training stack - finetune_local.py: auto-register model via Ollama HTTP API after GGUF export; path-translate between finetune container mount and Ollama's view; update config/llm.yaml automatically; DOCS_DIR env override for Docker - prepare_training_data.py: DOCS_DIR env override so make prepare-training works correctly inside the app container - compose.yml: add finetune service (cpu/single-gpu/dual-gpu profiles); DOCS_DIR=/docs injected into app + finetune containers - compose.podman-gpu.yml: CDI device override for finetune service - Makefile: make prepare-training + make finetune targets
123 lines
3.2 KiB
YAML
123 lines
3.2 KiB
YAML
# compose.yml — Peregrine by Circuit Forge LLC
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# Profiles: remote | cpu | single-gpu | dual-gpu
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services:
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app:
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build: .
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ports:
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- "${STREAMLIT_PORT:-8501}:8501"
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volumes:
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- ./config:/app/config
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- ./data:/app/data
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- ${DOCS_DIR:-~/Documents/JobSearch}:/docs
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environment:
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- STAGING_DB=/app/data/staging.db
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- DOCS_DIR=/docs
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- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:-}
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- OPENAI_COMPAT_URL=${OPENAI_COMPAT_URL:-}
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- OPENAI_COMPAT_KEY=${OPENAI_COMPAT_KEY:-}
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depends_on:
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searxng:
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condition: service_healthy
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restart: unless-stopped
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searxng:
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image: searxng/searxng:latest
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ports:
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- "${SEARXNG_PORT:-8888}:8080"
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volumes:
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- ./docker/searxng:/etc/searxng:ro
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healthcheck:
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test: ["CMD", "wget", "-q", "--spider", "http://localhost:8080/"]
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interval: 10s
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timeout: 5s
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retries: 3
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restart: unless-stopped
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ollama:
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image: ollama/ollama:latest
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ports:
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- "${OLLAMA_PORT:-11434}:11434"
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volumes:
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- ${OLLAMA_MODELS_DIR:-~/models/ollama}:/root/.ollama
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- ./docker/ollama/entrypoint.sh:/entrypoint.sh
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environment:
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- OLLAMA_MODELS=/root/.ollama
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- DEFAULT_OLLAMA_MODEL=${OLLAMA_DEFAULT_MODEL:-llama3.2:3b}
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entrypoint: ["/bin/bash", "/entrypoint.sh"]
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profiles: [cpu, single-gpu, dual-gpu]
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restart: unless-stopped
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ollama-gpu:
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extends:
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service: ollama
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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device_ids: ["0"]
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capabilities: [gpu]
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profiles: [single-gpu, dual-gpu]
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vision:
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build:
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context: .
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dockerfile: scripts/vision_service/Dockerfile
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ports:
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- "${VISION_PORT:-8002}:8002"
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environment:
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- VISION_MODEL=${VISION_MODEL:-vikhyatk/moondream2}
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- VISION_REVISION=${VISION_REVISION:-2025-01-09}
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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device_ids: ["0"]
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capabilities: [gpu]
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profiles: [single-gpu, dual-gpu]
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restart: unless-stopped
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vllm:
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image: vllm/vllm-openai:latest
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ports:
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- "${VLLM_PORT:-8000}:8000"
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volumes:
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- ${VLLM_MODELS_DIR:-~/models/vllm}:/models
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command: >
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--model /models/${VLLM_MODEL:-Ouro-1.4B}
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--trust-remote-code
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--max-model-len 4096
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--gpu-memory-utilization 0.75
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--enforce-eager
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--max-num-seqs 8
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--cpu-offload-gb ${CPU_OFFLOAD_GB:-0}
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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device_ids: ["1"]
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capabilities: [gpu]
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profiles: [dual-gpu]
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restart: unless-stopped
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finetune:
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build:
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context: .
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dockerfile: Dockerfile.finetune
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volumes:
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- ${DOCS_DIR:-~/Documents/JobSearch}:/docs
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- ${OLLAMA_MODELS_DIR:-~/models/ollama}:/ollama-models
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- ./config:/app/config
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environment:
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- DOCS_DIR=/docs
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- OLLAMA_URL=http://ollama:11434
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- OLLAMA_MODELS_MOUNT=/ollama-models
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- OLLAMA_MODELS_OLLAMA_PATH=/root/.ollama
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depends_on:
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ollama:
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condition: service_started
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profiles: [cpu, single-gpu, dual-gpu]
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restart: "no"
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