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Todomat — TODO orchestration with NLP2DSL, ITERUN, and curllm pipelines

Project description

Todomat

AI Cost Tracking

PyPI Version Python License AI Cost Human Time Model

  • 🤖 LLM usage: $0.1500 (1 commits)
  • 👤 Human dev: ~$100 (1.0h @ $100/h, 30min dedup)

Generated on 2026-06-07 using openrouter/qwen/qwen3-coder-next


Stack testowy strony www dla klientów wdrażających automatyzację przez prompty.

Łączy Open WebUI z curllm (dane online), NLP2DSL (procesy biznesowe) i ITERUN (usługi/API/stacki) przez OpenAI-compatible router.

Szybki start

cp .env.example .env
./scripts/bootstrap.sh
./scripts/test-local.sh

Endpointy

Usługa URL
Open WebUI http://localhost:3000
Pipeline Router http://localhost:9099/v1
Trigger Gateway http://localhost:8084/trigger
curllm API (opcjonalnie) http://localhost:8810

curllm — dane z internetu

./scripts/start-curllm.sh   # opcjonalnie, pełny browser+LLM

Domyślnie adapter używa lekkiego HTTP fetch (CURLLM_LIGHT_FETCH=1). Pełny curllm: CURLLM_LIGHT_FETCH=0 + uruchomiony API na :8810.

Open WebUI — połączenie

Admin → Settings → Connections:

Base URL: http://pipeline-router:9099/v1   # gdy Open WebUI w sieci todomat
API Key:  dev-key

Jeśli Open WebUI działa poza compose: http://host.docker.internal:9099/v1. Po ./scripts/bootstrap.sh kontener openwebui jest automatycznie podłączany do sieci todomat_todomat-net.

Przykładowe prompty

Zob. examples/prompts/ — w tym orchestration.md (usługi, getv, desktop, workflow).

MCP (Cursor / agenty)

Jeden router MCP routuje do curllm, nlp2dsl i iterun:

pip install -e .
./scripts/start-mcp.sh

Dokumentacja: docs/MCP.md · konfiguracja Cursor: examples/mcp-cursor.json

Orchestracja (URI, MCP, wiele usług)

Przewodnik uruchomienia i kontroli usług, artefaktów, zmiennych getv i zadań:

./scripts/sync-env-from-getv.sh llm/groq   # zmienne → .env
./scripts/install-mcp-stack.sh             # MCP + nlp2uri + getv

Dokumentacja

License

Licensed under Apache-2.0.

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