nanobot/tests/tools/test_message_tool_suppress.py

"""Test message tool suppress logic for final replies."""

import asyncio
from pathlib import Path
from unittest.mock import AsyncMock, MagicMock

import pytest

from nanobot.agent.context import TranscriptInput
from nanobot.agent.loop import AgentLoop
from nanobot.agent.tools.message import MessageTool
from nanobot.bus.events import InboundMessage, OutboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.providers.base import LLMResponse, ToolCallRequest


def _make_loop(tmp_path: Path) -> AgentLoop:
    bus = MessageBus()
    provider = MagicMock()
    provider.get_default_model.return_value = "test-model"
    return AgentLoop(bus=bus, provider=provider, workspace=tmp_path, model="test-model")


class TestMessageToolSuppressLogic:
    """Final reply suppressed only when message tool sends to the same target."""

    @pytest.mark.asyncio
    @pytest.mark.parametrize("ephemeral", [False, True])
    async def test_suppress_when_sent_to_same_target(
        self,
        tmp_path: Path,
        ephemeral: bool,
    ) -> None:
        loop = _make_loop(tmp_path)
        tool_call = ToolCallRequest(
            id="call1", name="message",
            arguments={"content": "Hello", "channel": "feishu", "chat_id": "chat123"},
        )
        calls = iter([
            LLMResponse(content="", tool_calls=[tool_call]),
            LLMResponse(content="Done", tool_calls=[]),
        ])
        loop.provider.chat_with_retry = AsyncMock(side_effect=lambda *a, **kw: next(calls))
        loop.tools.get_definitions = MagicMock(return_value=[])

        sent: list[OutboundMessage] = []
        mt = loop.tools.get("message")
        if isinstance(mt, MessageTool):
            mt.set_send_callback(AsyncMock(side_effect=lambda m: sent.append(m)))

        msg = InboundMessage(channel="feishu", sender_id="user1", chat_id="chat123", content="Send")
        result = await loop._process_message(msg, ephemeral=ephemeral)

        assert len(sent) == 1
        assert result is None  # suppressed

    @pytest.mark.asyncio
    async def test_not_suppress_when_sent_to_different_target(self, tmp_path: Path) -> None:
        loop = _make_loop(tmp_path)
        tool_call = ToolCallRequest(
            id="call1", name="message",
            arguments={"content": "Email content", "channel": "email", "chat_id": "user@example.com"},
        )
        calls = iter([
            LLMResponse(content="", tool_calls=[tool_call]),
            LLMResponse(content="I've sent the email.", tool_calls=[]),
        ])
        loop.provider.chat_with_retry = AsyncMock(side_effect=lambda *a, **kw: next(calls))
        loop.tools.get_definitions = MagicMock(return_value=[])

        sent: list[OutboundMessage] = []
        mt = loop.tools.get("message")
        if isinstance(mt, MessageTool):
            mt.set_send_callback(AsyncMock(side_effect=lambda m: sent.append(m)))

        msg = InboundMessage(channel="feishu", sender_id="user1", chat_id="chat123", content="Send email")
        result = await loop._process_message(msg)

        assert len(sent) == 1
        assert sent[0].channel == "email"
        assert result is not None  # not suppressed
        assert result.channel == "feishu"

    @pytest.mark.asyncio
    async def test_not_suppress_when_no_message_tool_used(self, tmp_path: Path) -> None:
        loop = _make_loop(tmp_path)
        loop.provider.chat_with_retry = AsyncMock(return_value=LLMResponse(content="Hello!", tool_calls=[]))
        loop.tools.get_definitions = MagicMock(return_value=[])

        msg = InboundMessage(channel="feishu", sender_id="user1", chat_id="chat123", content="Hi")
        result = await loop._process_message(msg)

        assert result is not None
        assert "Hello" in result.content

    @pytest.mark.asyncio
    async def test_internal_message_check_keeps_final_response(self, tmp_path: Path) -> None:
        loop = _make_loop(tmp_path)
        tool_call = ToolCallRequest(
            id="call1", name="message",
            arguments={"content": "all clear", "channel": "feishu", "chat_id": "chat123"},
        )
        calls = iter([
            LLMResponse(content="", tool_calls=[tool_call]),
            LLMResponse(content="Heartbeat summary", tool_calls=[]),
        ])
        loop.provider.chat_with_retry = AsyncMock(side_effect=lambda *a, **kw: next(calls))
        loop.tools.get_definitions = MagicMock(return_value=[])

        mt = loop.tools.get("message")
        assert isinstance(mt, MessageTool)
        token = mt.set_suppress_delivery(True)
        try:
            msg = InboundMessage(
                channel="feishu", sender_id="user1", chat_id="chat123", content="Check",
            )
            result = await loop._process_message(msg)
        finally:
            mt.reset_suppress_delivery(token)

        assert result is not None
        assert result.content == "Heartbeat summary"

    @pytest.mark.asyncio
    async def test_injected_followup_with_message_tool_does_not_emit_empty_fallback(
        self, tmp_path: Path
    ) -> None:
        loop = _make_loop(tmp_path)
        tool_call = ToolCallRequest(
            id="call1", name="message",
            arguments={"content": "Tool reply", "channel": "feishu", "chat_id": "chat123"},
        )
        calls = iter([
            LLMResponse(content="First answer", tool_calls=[]),
            LLMResponse(content="", tool_calls=[tool_call]),
            LLMResponse(content="", tool_calls=[]),
            LLMResponse(content="", tool_calls=[]),
            LLMResponse(content="", tool_calls=[]),
        ])
        loop.provider.chat_with_retry = AsyncMock(side_effect=lambda *a, **kw: next(calls))
        loop.tools.get_definitions = MagicMock(return_value=[])

        sent: list[OutboundMessage] = []
        mt = loop.tools.get("message")
        if isinstance(mt, MessageTool):
            mt.set_send_callback(AsyncMock(side_effect=lambda m: sent.append(m)))

        pending_queue = asyncio.Queue()
        await pending_queue.put(
            InboundMessage(channel="feishu", sender_id="user1", chat_id="chat123", content="follow-up")
        )

        msg = InboundMessage(channel="feishu", sender_id="user1", chat_id="chat123", content="Start")
        result = await loop._process_message(msg, pending_queue=pending_queue)

        assert len(sent) == 1
        assert sent[0].content == "Tool reply"
        assert result is None

    async def test_progress_hides_internal_reasoning(self, tmp_path: Path) -> None:
        loop = _make_loop(tmp_path)
        tool_call = ToolCallRequest(id="call1", name="read_file", arguments={"path": "foo.txt"})
        calls = iter([
            LLMResponse(
                content="Visible<think>hidden</think>",
                tool_calls=[tool_call],
                reasoning_content="secret reasoning",
                thinking_blocks=[{"signature": "sig", "thought": "secret thought"}],
            ),
            LLMResponse(content="Done", tool_calls=[]),
        ])
        loop.provider.chat_with_retry = AsyncMock(side_effect=lambda *a, **kw: next(calls))
        loop.tools.get_definitions = MagicMock(return_value=[])
        loop.tools.execute = AsyncMock(return_value="ok")

        progress: list[tuple[str, bool]] = []

        async def on_progress(content: str, *, tool_hint: bool = False) -> None:
            progress.append((content, tool_hint))

        result = await loop._run_agent_loop(
            TranscriptInput(history=[], current_message=None),
            runtime=loop.llm_runtime(),
            on_progress=on_progress,
        )

        assert result.final_content == "Done"
        assert progress == [
            ("Visible", False),
            ('read foo.txt', True),
        ]

class TestMessageToolSchema:

    def test_schema_discourages_current_chat_replies(self) -> None:
        tool = MessageTool()

        assert "Do not use this for the normal reply in the current chat" in tool.description
        assert "generate_image creates images in the current chat" in tool.description
        assert (
            "Do not use this for a normal reply in the current chat"
            in tool.parameters["properties"]["content"]["description"]
        )