# How To Run

1. Install dependencies:

```bash
python3 -m venv .venv
. .venv/bin/activate
python -m pip install -e ".[dev]"
```

2. Configure:

```bash
cp .env.example .env
```

The default `DUCK_MAIN_MODEL_PATH` points to `./models/Qwen3.6/nonMTP/Qwen3.6-35B-A3B-UD-Q4_K_M.gguf`.

3. Start `llama-server`:

```bash
bash scripts/llama/start_main.sh start
```

Useful process commands:

```bash
bash scripts/llama/start_main.sh status
bash scripts/llama/start_main.sh logs --follow
bash scripts/llama/start_main.sh restart
bash scripts/llama/start_main.sh stop
```

4. Start DuckLM API:

```bash
python -m duck_core.api
```

5. Open WebChat:

```text
http://127.0.0.1:8000/
```

6. Send a task:

```bash
curl -X POST http://127.0.0.1:8000/v1/chat \
  -H "Content-Type: application/json" \
  -d '{"message":"Скажи коротко, что ты DuckLM","workspace":"./workspace","debug":true}'
```

7. Inspect events:

```bash
curl http://127.0.0.1:8000/v1/tasks/<task_id>/events
```

8. Approvals:

```bash
curl http://127.0.0.1:8000/v1/approvals/pending
```

9. Stop services:

```bash
bash scripts/llama/start_main.sh stop
docker compose -f docker-compose.memory.yml down
```