2026-05-29 07:16:02 +00:00
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# Конфигурация пайплайна транскрибации совещаний
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# Профили оборудования
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profiles:
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# Текущий: MacBook Air M4, 16GB RAM
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mac_m4:
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device: cpu # MPS на Mac может быть медленнее/багован; CPU + int8 стабильнее
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compute_type: int8
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2026-05-29 09:42:07 +00:00
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batch_size: 2 # Оптимум для CPU (1.2-1.3x быстрее, RAM ~4.5 GB)
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2026-05-29 07:16:02 +00:00
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model: large-v3
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language: ru
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diarize: true
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# Будущий: GPU с 8GB VRAM
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gpu_8gb:
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device: cuda
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compute_type: float16 # или int8 если не хватает памяти
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batch_size: 1 # large-v3 + alignment + diarization в ~8GB
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model: large-v3
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language: ru
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diarize: true
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# Универсальный CPU (без GPU)
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cpu_best:
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device: cpu
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compute_type: int8
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batch_size: 1
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model: large-v3
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language: ru
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diarize: true
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# Активный профиль (можно переопределить через CLI: --profile gpu_8gb)
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active_profile: mac_m4
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# Настройки диаризации
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hf_token: null # HuggingFace токен для pyannote. Установите через env: HF_TOKEN
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# Настройки выходного документа
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output:
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2026-05-29 08:39:13 +00:00
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formats: [docx, md] # Список форматов: docx, md, txt. Можно указать один или несколько.
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2026-05-29 07:16:02 +00:00
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include_timestamps: true
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speaker_label_style: name # name | id | none
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paragraph_pause_sec: 2.0 # новый абзац, если пауза > N секунд
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Replace LightRAG with native Python RAG engine + add deploy tooling
- New: src/rag/engine/ — in-process hybrid search (FTS5 BM25 + sqlite-vec + LLM rerank)
- New: src/rag/qmd/ — compatibility layer (qmd_query, qmd_chat, qmd_chat_stream, qmd_index_*)
- New: src/ingest/stub_writer.py — .md stubs for binary files (videos, archives)
- New: scripts/deploy.sh + scripts/pull_models.sh + Makefile + .env.example
- Removed: LightRAG, sentence-transformers embedding via separate package, rag_standalone/
- Removed: @nousresearch/qmd npm dep (package not published); Node.js from Dockerfile
- Updated: tests/ (46 passed), docker-compose, .dockerignore, config.yaml, README
Engine: in-process Python (no daemon, no npm), sentence-transformers 384-dim,
RRF fusion (k=60), BM25 + vector with numpy fallback. WebSocket API unchanged.
Deploy: 'git clone' + 'make init' + 'make pull-models MODELS_SOURCE=...' + 'make up'.
Models (5.83 GB) live outside git; pulled via rsync from dev host.
2026-06-10 11:24:01 +00:00
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# Настройки RAG (native Python engine: BM25/FTS5 + sqlite-vec + LLM rerank)
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# Движок работает in-process; внешние сервисы не требуются.
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2026-06-01 14:40:58 +00:00
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rag:
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enabled: true
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auto_index: true
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sections:
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- Планировка
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- Конструкции
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- MEP
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- Отделка
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- Общие вопросы
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- Согласование
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- Контроль качества
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Replace LightRAG with native Python RAG engine + add deploy tooling
- New: src/rag/engine/ — in-process hybrid search (FTS5 BM25 + sqlite-vec + LLM rerank)
- New: src/rag/qmd/ — compatibility layer (qmd_query, qmd_chat, qmd_chat_stream, qmd_index_*)
- New: src/ingest/stub_writer.py — .md stubs for binary files (videos, archives)
- New: scripts/deploy.sh + scripts/pull_models.sh + Makefile + .env.example
- Removed: LightRAG, sentence-transformers embedding via separate package, rag_standalone/
- Removed: @nousresearch/qmd npm dep (package not published); Node.js from Dockerfile
- Updated: tests/ (46 passed), docker-compose, .dockerignore, config.yaml, README
Engine: in-process Python (no daemon, no npm), sentence-transformers 384-dim,
RRF fusion (k=60), BM25 + vector with numpy fallback. WebSocket API unchanged.
Deploy: 'git clone' + 'make init' + 'make pull-models MODELS_SOURCE=...' + 'make up'.
Models (5.83 GB) live outside git; pulled via rsync from dev host.
2026-06-10 11:24:01 +00:00
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# Native RAG engine (in-process, без демонов)
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qmd_collection_root: ./processed # ENV override: QMD_COLLECTION_ROOT
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qmd_use_rerank: true # LLM-реранкер (2-3 сек warm)
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embed_model: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 # ENV: RAG_EMBED_MODEL
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# OpenCode LLM (чат-генерация ответов поверх найденного контекста)
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2026-06-01 14:40:58 +00:00
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chat_backend: opencode
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chat_model: deepseek-v4-flash-free
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Replace LightRAG with native Python RAG engine + add deploy tooling
- New: src/rag/engine/ — in-process hybrid search (FTS5 BM25 + sqlite-vec + LLM rerank)
- New: src/rag/qmd/ — compatibility layer (qmd_query, qmd_chat, qmd_chat_stream, qmd_index_*)
- New: src/ingest/stub_writer.py — .md stubs for binary files (videos, archives)
- New: scripts/deploy.sh + scripts/pull_models.sh + Makefile + .env.example
- Removed: LightRAG, sentence-transformers embedding via separate package, rag_standalone/
- Removed: @nousresearch/qmd npm dep (package not published); Node.js from Dockerfile
- Updated: tests/ (46 passed), docker-compose, .dockerignore, config.yaml, README
Engine: in-process Python (no daemon, no npm), sentence-transformers 384-dim,
RRF fusion (k=60), BM25 + vector with numpy fallback. WebSocket API unchanged.
Deploy: 'git clone' + 'make init' + 'make pull-models MODELS_SOURCE=...' + 'make up'.
Models (5.83 GB) live outside git; pulled via rsync from dev host.
2026-06-10 11:24:01 +00:00
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chat_max_tokens: 8192
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opencode_api_key: "sk-4jJBUMS7WJyBOtZZAexsSy6aT4NKOYp2gA19WLlaux8jHMw0HvyCl1V45Jf8SONz" # Или через env: OPENCODE_API_KEY
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opencode_url: "https://opencode.ai/zen/v1"
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# Классификация и summary (metadata layer, поверх движка)
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2026-06-01 14:40:58 +00:00
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summary_auto: true
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summary_model: deepseek-v4-flash-free
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summary_chunk_size: 10000
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classify_chunk_size: 7000
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Replace LightRAG with native Python RAG engine + add deploy tooling
- New: src/rag/engine/ — in-process hybrid search (FTS5 BM25 + sqlite-vec + LLM rerank)
- New: src/rag/qmd/ — compatibility layer (qmd_query, qmd_chat, qmd_chat_stream, qmd_index_*)
- New: src/ingest/stub_writer.py — .md stubs for binary files (videos, archives)
- New: scripts/deploy.sh + scripts/pull_models.sh + Makefile + .env.example
- Removed: LightRAG, sentence-transformers embedding via separate package, rag_standalone/
- Removed: @nousresearch/qmd npm dep (package not published); Node.js from Dockerfile
- Updated: tests/ (46 passed), docker-compose, .dockerignore, config.yaml, README
Engine: in-process Python (no daemon, no npm), sentence-transformers 384-dim,
RRF fusion (k=60), BM25 + vector with numpy fallback. WebSocket API unchanged.
Deploy: 'git clone' + 'make init' + 'make pull-models MODELS_SOURCE=...' + 'make up'.
Models (5.83 GB) live outside git; pulled via rsync from dev host.
2026-06-10 11:24:01 +00:00
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classify_model: mimo-v2.5-free
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index_model: mimo-v2.5-free # legacy alias, используется в legacy-классификации
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2026-06-01 14:40:58 +00:00
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# Очередь обработки
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queue:
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transcribe_workers: 2
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postprocess_workers: 1
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2026-06-01 16:16:23 +00:00
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ingest_workers: 1
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# Ingest документов (MD, PDF, DOCX, XLSX, TXT)
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ingest:
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auto_classify: true
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pdf_ocr: true
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doc_types:
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- meeting
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- specification
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- estimate
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- contract
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- report
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- correspondence
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- other
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2026-06-01 14:40:58 +00:00
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2026-06-01 15:54:25 +00:00
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# Авторизация и multi-tenant (org + projects)
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auth:
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jwt_secret: "" # Обязательно задайте JWT_SECRET в .env для production
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jwt_expire_hours: 168
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database_path: ./data/transcriba.db
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bootstrap:
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org_slug: merakom
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org_name: "МЕРАКОМ"
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admin_username: admin
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admin_password: "admin123" # Смените после первого входа; или AUTH_ADMIN_PASSWORD в .env
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default_projects:
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- slug: "2026"
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name: "2026"
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- slug: "gp-merakom"
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name: "ГП МЕРАКОМ"
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2026-05-29 07:16:02 +00:00
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# Пути
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paths:
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output_dir: ./output
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temp_dir: ./tmp
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