- Implement robustSentenceSplit across reader.js and backend (miner.py, cefr.py) to prevent false cutoffs on honorifics (Mr., Mrs., Dr.), single-letter initials (John F. Kennedy), decimals, acronyms (U.S., U.K.), and abbreviations (No. 4, etc.) - Upgrade translation prompt to professional literary Russian, eliminating literal word-for-word translation and preserving titles/honorifics - Inject surrounding paragraph context into translation API to avoid out-of-context translations - Inject offline dictionary hints into LLM prompt for accurate contextual word meaning - Prefer qwen2.5:3b for higher translation fluency and fidelity - Purge truncated cache entries from sentence_translations and restore Card 30 (briefcase) with authentic full sentence - Bump Service Worker cache to notes-v6.0 - Add unit tests for robust sentence splitting, prompt formatting, and translation API
33 lines
750 B
YAML
33 lines
750 B
YAML
services:
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study-web:
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build: .
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container_name: study-qpid-pro
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restart: unless-stopped
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ports:
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- "127.0.0.1:8002:8002"
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volumes:
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- ./data:/app/data
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- ./app:/app/app
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environment:
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- HOST=0.0.0.0
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- PORT=8002
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- DEBUG=False
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- SECRET_KEY=study-qpid-pro-secret-key-change-in-prod
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- ADMIN_USERNAME=kopri
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- DB_PATH=/app/data/notes.db
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- OLLAMA_BASE_URL=http://ollama:11434
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- OLLAMA_MODEL=qwen2.5:3b
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depends_on:
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- ollama
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ollama:
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image: ollama/ollama:latest
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container_name: study-ollama
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restart: unless-stopped
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ports:
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- "127.0.0.1:11434:11434"
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volumes:
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- ./data/ollama:/root/.ollama
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environment:
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- OLLAMA_KEEP_ALIVE=5m
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