# 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 DuckLM:

```bash
bash scripts/duck.sh start
```

This starts both processes:

- `llama-server` on `http://127.0.0.1:8081/v1`
- DuckLM API/WebChat on `http://127.0.0.1:8000/`

Useful process commands:

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

Use live probes when you need backend diagnostics, not just process status:

```bash
bash scripts/duck.sh status --probe
curl --noproxy '*' 'http://127.0.0.1:8000/v1/status?probe=true'
```

4. Open WebChat:

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

Low-level llama-only commands are still available when needed:

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

MTP/speculative variant:

```bash
bash scripts/duck.sh stop
bash scripts/duck-mtp.sh start
bash scripts/duck-mtp.sh status
bash scripts/duck-mtp.sh logs --follow
```

`duck-mtp.sh` keeps DuckLM on `http://127.0.0.1:8000/` and starts the MTP-backed
`llama-server` on the normal role endpoint `http://127.0.0.1:8081/v1`, so
`config/models.yaml` does not need to change.

5. 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}'
```

6. Inspect events:

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

7. Approvals:

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

8. Stop services:

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