Add Discord-native hybrid front-end for Jarvis (bot + bridge)

Transform isair/jarvis into a Discord-controlled voice assistant running on
the Ubuntu VNC desktop, keeping the mature ~39k-line Python brain intact.

- bot/ (Node + bun, discord.js): /자비스 slash commands (ephemeral),
  voice channel join + voice receive/playback, pluggable VNC screen broadcast
  (selfbot live / noVNC / screenshot)
- bridge/ (Python, Flask): wraps jarvis STT + run_reply_engine + Piper TTS
  behind a thin localhost HTTP API
- .env.example, scripts/ (start_bridge/start_bot/dev), README rewrite,
  docs/language-comparison.md and docs/vnc-xfce-setup.md

Language decision: hybrid (Python brain + Node/bun Discord layer) because
Discord blocks bot video; native screen broadcast only works via a Node
selfbot library.

tests/test_greeting_no_tools.py

@@ -0,0 +1,275 @@
+"""
+Unit tests for greeting and instruction handling in the reply engine.
+
+Verifies that the model-size-aware prompt system correctly prevents
+tool calls for greetings and user instructions, while still allowing
+tools for queries that genuinely require them.
+
+These tests use a mocked LLM and do not require a real Ollama instance.
+"""
+
+from dataclasses import dataclass, field
+from typing import Any, Dict, List
+from unittest.mock import patch
+
+import pytest
+
+
+@pytest.fixture(autouse=True)
+def _disable_planner():
+    """These tests verify greeting/instruction routing against a mocked
+    chat LLM. The planner uses its own LLM call (`call_llm_direct`) which
+    is not mocked here, so disable it to keep the test hermetic."""
+    with patch("jarvis.reply.engine.plan_query", return_value=[]):
+        yield
+
+
+# =============================================================================
+# Test Data
+# =============================================================================
+
+# Greetings in multiple languages - should NOT trigger tools
+GREETING_TEST_CASES = [
+    pytest.param("hello", False, id="Greeting: hello"),
+    pytest.param("hi there", False, id="Greeting: hi there"),
+    pytest.param("hey", False, id="Greeting: hey"),
+    pytest.param("ni hao", False, id="Greeting: ni hao (Chinese)"),
+    pytest.param("bonjour", False, id="Greeting: bonjour (French)"),
+    pytest.param("hola", False, id="Greeting: hola (Spanish)"),
+    pytest.param("merhaba", False, id="Greeting: merhaba (Turkish)"),
+    pytest.param("ciao", False, id="Greeting: ciao (Italian)"),
+    pytest.param("guten tag", False, id="Greeting: guten tag (German)"),
+    pytest.param("how are you", False, id="Greeting: how are you"),
+    pytest.param("thank you", False, id="Greeting: thank you"),
+    pytest.param("thanks", False, id="Greeting: thanks"),
+    pytest.param("goodbye", False, id="Greeting: goodbye"),
+    pytest.param("good morning", False, id="Greeting: good morning"),
+    pytest.param("good night", False, id="Greeting: good night"),
+]
+
+# User instructions about behaviour - should NOT trigger tools
+USER_INSTRUCTION_TEST_CASES = [
+    pytest.param("always use Celsius when telling me temperatures", False, id="Instruction: use Celsius"),
+    pytest.param("remember to always tell me things in Celsius", False, id="Instruction: remember Celsius"),
+    pytest.param("be more brief in your responses", False, id="Instruction: be more brief"),
+    pytest.param("speak in French from now on", False, id="Instruction: speak in French"),
+    pytest.param("always give me the short version", False, id="Instruction: short version"),
+    pytest.param("don't use emojis in your responses", False, id="Instruction: no emojis"),
+    pytest.param("note that I prefer metric units", False, id="Instruction: prefer metric"),
+]
+
+# Queries that SHOULD trigger tools
+TOOL_REQUIRED_TEST_CASES = [
+    pytest.param("what's the weather", True, id="Tool query: weather"),
+    pytest.param("search for python tutorials", True, id="Tool query: web search"),
+    pytest.param("what's the weather in Tokyo", True, id="Tool query: weather with location"),
+    pytest.param("look up the news today", True, id="Tool query: news search"),
+    pytest.param("what did I eat yesterday", True, id="Tool query: meal recall"),
+]
+
+
+# =============================================================================
+# Helpers
+# =============================================================================
+
+@dataclass
+class ToolCallCapture:
+    """Captures tool calls made during a test run."""
+    calls: List[Dict[str, Any]] = field(default_factory=list)
+
+    def record(self, name: str, args: Dict[str, Any]):
+        self.calls.append({"name": name, "args": args})
+
+    def has_any_tool(self) -> bool:
+        return len(self.calls) > 0
+
+    def tool_names(self) -> List[str]:
+        return [c["name"] for c in self.calls]
+
+
+def _mock_llm_response(content: str, tool_calls=None):
+    """Build a minimal mock Ollama response dict."""
+    message = {"content": content, "role": "assistant"}
+    if tool_calls:
+        message["tool_calls"] = tool_calls
+    return {"message": message}
+
+
+def _tool_call(name: str, args: Dict[str, Any]):
+    """Build a mock tool-call entry in OpenAI format."""
+    return {
+        "id": f"call_{name}_001",
+        "function": {"name": name, "arguments": args},
+    }
+
+
+# =============================================================================
+# Tests
+# =============================================================================
+
+class TestGreetingNoTools:
+    """
+    Verifies that the model-size-aware prompt system does not trigger tool
+    calls for greetings or user instructions when using a mocked LLM.
+    """
+
+    @pytest.mark.unit
+    @pytest.mark.parametrize("query,should_use_tools", GREETING_TEST_CASES + USER_INSTRUCTION_TEST_CASES)
+    def test_greeting_no_tool_calls(
+        self,
+        query: str,
+        should_use_tools: bool,
+        mock_config,
+        db,
+        dialogue_memory,
+    ):
+        """Greetings and user instructions should not trigger tool calls."""
+        from jarvis.reply.engine import run_reply_engine
+
+        mock_config.ollama_chat_model = "gemma4:e2b"
+        capture = ToolCallCapture()
+
+        def mock_tool_run(db, cfg, tool_name, tool_args, **kwargs):  # noqa: F841 (shadows fixture)
+            from jarvis.tools.types import ToolExecutionResult
+            capture.record(tool_name, tool_args or {})
+            return ToolExecutionResult(success=True, reply_text="Tool result")
+
+        def mock_chat(base_url, chat_model, messages, timeout_sec, extra_options=None, tools=None, thinking=False):
+            return _mock_llm_response("Hello! How can I help you today?")
+
+        with patch('jarvis.reply.engine.run_tool_with_retries', side_effect=mock_tool_run), \
+             patch('jarvis.reply.engine.chat_with_messages', side_effect=mock_chat), \
+             patch('jarvis.reply.engine.extract_search_params_for_memory', return_value={"keywords": []}):
+
+            run_reply_engine(
+                db=db, cfg=mock_config, tts=None,
+                text=query, dialogue_memory=dialogue_memory,
+            )
+
+        assert not capture.has_any_tool(), \
+            f"Greeting '{query}' should NOT trigger tools. Called: {capture.tool_names()}"
+
+    @pytest.mark.unit
+    @pytest.mark.parametrize("query,should_use_tools", TOOL_REQUIRED_TEST_CASES)
+    def test_tool_queries_still_work(
+        self,
+        query: str,
+        should_use_tools: bool,
+        mock_config,
+        db,
+        dialogue_memory,
+    ):
+        """Queries that require tools should still trigger them."""
+        from jarvis.reply.engine import run_reply_engine
+
+        mock_config.ollama_chat_model = "gemma4:e2b"
+        capture = ToolCallCapture()
+
+        def mock_tool_run(db, cfg, tool_name, tool_args, **kwargs):  # noqa: F841 (shadows fixture)
+            from jarvis.tools.types import ToolExecutionResult
+            capture.record(tool_name, tool_args or {})
+            return ToolExecutionResult(success=True, reply_text="Weather: 20C sunny")
+
+        call_count = 0
+
+        def mock_chat(base_url, chat_model, messages, timeout_sec, extra_options=None, tools=None, thinking=False):
+            nonlocal call_count
+            call_count += 1
+            if call_count == 1:
+                if "weather" in query.lower():
+                    return _mock_llm_response("", [_tool_call("getWeather", {"location": "here"})])
+                elif "search" in query.lower() or "look up" in query.lower() or "news" in query.lower():
+                    return _mock_llm_response("", [_tool_call("webSearch", {"search_query": query})])
+                elif "eat" in query.lower() or "meal" in query.lower():
+                    return _mock_llm_response("", [_tool_call("fetchMeals", {})])
+            return _mock_llm_response("Here's the information you requested.")
+
+        with patch('jarvis.reply.engine.run_tool_with_retries', side_effect=mock_tool_run), \
+             patch('jarvis.reply.engine.chat_with_messages', side_effect=mock_chat), \
+             patch('jarvis.reply.engine.extract_search_params_for_memory', return_value={"keywords": []}), \
+             patch('jarvis.reply.engine.select_tools',
+                   return_value=["webSearch", "getWeather", "fetchMeals", "stop"]):
+
+            response = run_reply_engine(
+                db=db, cfg=mock_config, tts=None,
+                text=query, dialogue_memory=dialogue_memory,
+            )
+
+        assert capture.has_any_tool(), \
+            f"Query '{query}' SHOULD trigger tools but didn't. Response: {response}"
+
+    @pytest.mark.unit
+    def test_thinking_only_response_continues_loop(
+        self,
+        mock_config,
+        db,
+        dialogue_memory,
+    ):
+        """A thinking-only response (no content, no tool call) should continue the loop, not break it."""
+        from jarvis.reply.engine import run_reply_engine
+
+        mock_config.ollama_chat_model = "gemma4:12b"
+        call_count = 0
+
+        def mock_chat(base_url, chat_model, messages, timeout_sec, extra_options=None, tools=None, thinking=False):
+            nonlocal call_count
+            call_count += 1
+            if call_count == 1:
+                # First turn: thinking only, no content, no tool call
+                return {"message": {"content": "", "role": "assistant", "thinking": "Let me think about this..."}}
+            # Second turn: actual response
+            return _mock_llm_response("The answer is 42.")
+
+        with patch('jarvis.reply.engine.chat_with_messages', side_effect=mock_chat), \
+             patch('jarvis.reply.engine.extract_search_params_for_memory', return_value={"keywords": []}):
+
+            response = run_reply_engine(
+                db=db, cfg=mock_config, tts=None,
+                text="what is the meaning of life",
+                dialogue_memory=dialogue_memory,
+            )
+
+        assert call_count == 2, f"Expected 2 LLM calls (thinking + response), got {call_count}"
+        assert response is not None
+        assert "42" in response
+
+    @pytest.mark.unit
+    def test_all_tools_available_regardless_of_profile(
+        self,
+        mock_config,
+        db,
+        dialogue_memory,
+    ):
+        """All builtin tools should be available regardless of which profile is selected."""
+        from jarvis.reply.engine import run_reply_engine
+
+        mock_config.ollama_chat_model = "gemma4:e2b"
+        capture = ToolCallCapture()
+
+        def mock_tool_run(db, cfg, tool_name, tool_args, **kwargs):
+            from jarvis.tools.types import ToolExecutionResult
+            capture.record(tool_name, tool_args or {})
+            return ToolExecutionResult(success=True, reply_text="Logged: pizza")
+
+        call_count = 0
+
+        def mock_chat(base_url, chat_model, messages, timeout_sec, extra_options=None, tools=None, thinking=False):
+            nonlocal call_count
+            call_count += 1
+            if call_count == 1:
+                return _mock_llm_response("", [_tool_call("logMeal", {"description": "pizza"})])
+            return _mock_llm_response("Logged your meal!")
+
+        # logMeal was previously restricted to "life" profile only — now all tools are always available
+        with patch('jarvis.reply.engine.run_tool_with_retries', side_effect=mock_tool_run), \
+             patch('jarvis.reply.engine.chat_with_messages', side_effect=mock_chat), \
+             patch('jarvis.reply.engine.extract_search_params_for_memory', return_value={"keywords": []}):
+
+            run_reply_engine(
+                db=db, cfg=mock_config, tts=None,
+                text="log that I had pizza for lunch",
+                dialogue_memory=dialogue_memory,
+            )
+
+        assert capture.has_any_tool(), "logMeal should always be callable"
+        assert "logMeal" in capture.tool_names()