"""Tests for the ``ollama_num_predict`` chat-output cap.

The cap bounds worst-case reply latency by limiting how many tokens the chat
model may generate per turn. Spoken (TTS) answers are 1-2 sentences, so the
default headroom never clips a normal answer and stays above tool-call JSON.

These tests verify behaviour:
- the config default is present,
- the value is threaded into the Ollama request as the ``num_predict`` option,
- the reply loop forwards it to the chat call (and disables it at 0).
"""

from unittest.mock import Mock, patch

import pytest

from src.jarvis.config import get_default_config
from src.jarvis.memory.conversation import DialogueMemory
from src.jarvis.reply.engine import run_reply_engine


# ---------------------------------------------------------------------------
# Config default
# ---------------------------------------------------------------------------

def test_default_config_has_num_predict_cap():
    config = get_default_config()
    assert config["ollama_num_predict"] == 512


# ---------------------------------------------------------------------------
# Transport: extra_options.num_predict reaches the Ollama payload options
# ---------------------------------------------------------------------------

@patch("jarvis.llm.requests.post")
def test_chat_with_messages_forwards_num_predict(mock_post):
    from jarvis.llm import chat_with_messages

    mock_resp = Mock()
    mock_resp.status_code = 200
    mock_resp.json.return_value = {"message": {"content": "ok"}}
    mock_resp.raise_for_status = Mock()
    mock_post.return_value = mock_resp

    chat_with_messages(
        "http://localhost:11434",
        "test-large",
        [{"role": "user", "content": "hi"}],
        extra_options={"num_predict": 512},
    )
    _, kwargs = mock_post.call_args
    options = (kwargs.get("json") or {}).get("options") or {}
    assert options.get("num_predict") == 512


# ---------------------------------------------------------------------------
# Reply loop wiring
# ---------------------------------------------------------------------------

def _mock_cfg(num_predict):
    cfg = Mock()
    cfg.ollama_base_url = "http://localhost:11434"
    cfg.ollama_chat_model = "test-large"  # avoid SMALL-model text-tool path
    cfg.ollama_num_predict = num_predict
    cfg.voice_debug = False
    cfg.llm_tools_timeout_sec = 8.0
    cfg.llm_embed_timeout_sec = 10.0
    cfg.llm_chat_timeout_sec = 45.0
    cfg.llm_digest_timeout_sec = 8.0
    cfg.memory_enrichment_max_results = 5
    cfg.memory_enrichment_source = "diary"
    cfg.memory_digest_enabled = False
    cfg.tool_result_digest_enabled = False
    cfg.location_ip_address = None
    cfg.location_auto_detect = False
    cfg.location_enabled = False
    cfg.agentic_max_turns = 8
    cfg.tool_search_max_calls = 3
    cfg.tool_selection_strategy = "all"
    cfg.tool_carryover_max_turns = 2
    cfg.tool_carryover_per_entry_chars = 1200
    cfg.mcps = {}
    cfg.llm_thinking_enabled = False
    cfg.tts_engine = "none"
    cfg.ollama_embed_model = "test-embed"
    return cfg


def _run_single_turn(cfg):
    """Drive one reply turn that answers in plain text and capture the
    chat call's extra_options."""
    with patch("src.jarvis.reply.engine.plan_query", return_value=[]), \
         patch("src.jarvis.reply.engine.extract_search_params_for_memory", return_value={}), \
         patch("src.jarvis.reply.engine.extract_text_from_response", return_value="Hello."), \
         patch("src.jarvis.reply.engine.chat_with_messages") as mock_chat:
        mock_chat.return_value = {"message": {"content": "Hello."}}
        run_reply_engine(db=Mock(), cfg=cfg, tts=None,
                         text="hi", dialogue_memory=DialogueMemory())
        assert mock_chat.called
        return mock_chat.call_args.kwargs.get("extra_options")


@pytest.mark.unit
def test_reply_loop_caps_output_when_enabled():
    extra = _run_single_turn(_mock_cfg(512))
    assert extra == {"num_predict": 512}


@pytest.mark.unit
def test_reply_loop_no_cap_when_zero():
    extra = _run_single_turn(_mock_cfg(0))
    assert extra is None