yeachan-heo--oh-my-claudecode
wehub-resource-sync
adc62957a7
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89 行
2.1 KiB
YAML
89 行
2.1 KiB
YAML
version: '3.8'
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services:
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swe-bench-runner:
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build:
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context: .
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dockerfile: Dockerfile
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container_name: swe-bench-omc
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# Environment configuration
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environment:
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- ANTHROPIC_AUTH_TOKEN=${ANTHROPIC_AUTH_TOKEN}
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- ANTHROPIC_BASE_URL=${ANTHROPIC_BASE_URL:-https://api.layofflabs.com}
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- RUN_MODE=${RUN_MODE:-vanilla}
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- MAX_WORKERS=${MAX_WORKERS:-4}
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- DATASET=${DATASET:-princeton-nlp/SWE-bench_Verified}
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- PYTHONUNBUFFERED=1
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- NODE_ENV=production
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# Volume mounts
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volumes:
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# Persist results across runs
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- ./results:/workspace/results
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# Model predictions output
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- ./predictions:/workspace/predictions
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# Cached repositories
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- ./repos:/workspace/repos
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# Execution logs
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- ./logs:/workspace/logs
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# Mount OMC source for development (optional)
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- ../:/workspace/omc-source:ro
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# Docker socket for SWE-bench container operations
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- /var/run/docker.sock:/var/run/docker.sock
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# Claude config persistence
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- claude-config:/root/.claude
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# Resource limits
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deploy:
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resources:
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limits:
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cpus: '8'
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memory: 16G
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reservations:
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cpus: '2'
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memory: 4G
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# Keep container running for interactive use
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stdin_open: true
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tty: true
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# Networking
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networks:
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- swe-bench-net
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# Working directory
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working_dir: /workspace
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# Optional: Results analysis service
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analysis:
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build:
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context: .
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dockerfile: Dockerfile
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container_name: swe-bench-analysis
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profiles:
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- analysis
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environment:
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- PYTHONUNBUFFERED=1
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volumes:
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- ./results:/workspace/results:ro
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- ./predictions:/workspace/predictions:ro
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- ./analysis:/workspace/analysis
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command: >
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python -c "
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import pandas as pd
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import json
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from pathlib import Path
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print('Analysis service ready. Mount your analysis scripts.')
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"
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networks:
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- swe-bench-net
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networks:
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swe-bench-net:
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driver: bridge
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volumes:
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claude-config:
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driver: local
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