Files
notes-qpid-pro/docker-compose.yml
T
Antigravity 532e2ec3b2 fix(ai,reader): robust sentence segmentation without abbreviation cutoffs & context-aware literary translation
- 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
2026-10-06 22:32:36 +03:00

33 lines
750 B
YAML

services:
study-web:
build: .
container_name: study-qpid-pro
restart: unless-stopped
ports:
- "127.0.0.1:8002:8002"
volumes:
- ./data:/app/data
- ./app:/app/app
environment:
- HOST=0.0.0.0
- PORT=8002
- DEBUG=False
- SECRET_KEY=study-qpid-pro-secret-key-change-in-prod
- ADMIN_USERNAME=kopri
- DB_PATH=/app/data/notes.db
- OLLAMA_BASE_URL=http://ollama:11434
- OLLAMA_MODEL=qwen2.5:3b
depends_on:
- ollama
ollama:
image: ollama/ollama:latest
container_name: study-ollama
restart: unless-stopped
ports:
- "127.0.0.1:11434:11434"
volumes:
- ./data/ollama:/root/.ollama
environment:
- OLLAMA_KEEP_ALIVE=5m