Files
FabledScribe/docker-compose.yml
T
bvandeusen 931a059e9f GPU support, parallel intent+context, and increased context window
Docker Compose:
- Enable Ollama GPU passthrough (nvidia, count: all) in both dev and prod files
- Add OLLAMA_FLASH_ATTENTION=1 (faster attention on GPU in both files)
- Add OLLAMA_MAX_LOADED_MODELS=2 and OLLAMA_KEEP_ALIVE=30m to prod (was already in dev)
- Remove 8G memory limit from prod Ollama service (CPU-bound constraint, no longer valid)

llm.py:
- Increase num_ctx 16384 → 32768 in stream_chat and stream_chat_with_tools (GPU VRAM allows it)
- Increase num_predict cap 4096 → 8192 for tool-augmented responses

generation_task.py:
- Parallelize build_context, get_tools_for_user, and get_setting all from the start
- As soon as tools list is ready (fast DB call), launch classify_intent as an asyncio.Task
- Await build_context and classify_intent together via asyncio.gather
- Intent result is pre-computed before the generation loop; loop just reads pre_intent on round 0
- intent_ms timing now reflects wall-clock time from intent start to completion

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-18 19:29:31 -05:00

50 lines
1.2 KiB
YAML

services:
app:
build: .
ports:
- "5000:5000"
depends_on:
db:
condition: service_healthy
ollama:
condition: service_started
environment:
DATABASE_URL: "postgresql+asyncpg://${POSTGRES_USER:-fabled}:${POSTGRES_PASSWORD:-fabled}@db:5432/${POSTGRES_DB:-fabledassistant}"
OLLAMA_URL: "http://ollama:11434"
OLLAMA_MODEL: "${OLLAMA_MODEL:-llama3.1}"
SECRET_KEY: "${SECRET_KEY:-dev-secret-change-me}"
db:
image: postgres:16-alpine
volumes:
- pgdata:/var/lib/postgresql/data
environment:
POSTGRES_USER: ${POSTGRES_USER:-fabled}
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-fabled}
POSTGRES_DB: ${POSTGRES_DB:-fabledassistant}
healthcheck:
test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-fabled}"]
interval: 5s
timeout: 5s
retries: 5
ollama:
image: ollama/ollama
volumes:
- ollama_models:/root/.ollama
environment:
OLLAMA_MAX_LOADED_MODELS: "2"
OLLAMA_KEEP_ALIVE: "30m"
OLLAMA_FLASH_ATTENTION: "1"
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
volumes:
pgdata:
ollama_models: