c4abf63f38
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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.
69 lines
2.5 KiB
Python
69 lines
2.5 KiB
Python
"""Behaviour test: memory enrichment extractor runs on the router model chain.
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The extractor used to run on the big chat model, which paged in the heavy
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weights just to emit a tiny JSON blob. It's now routed through
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``resolve_tool_router_model`` so it rides the already-warm small model.
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This test locks that in at the engine call-site — if somebody ever reverts to
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``cfg.ollama_chat_model`` there, the assertion fails.
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"""
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from __future__ import annotations
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from unittest.mock import patch, MagicMock
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import pytest
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@pytest.mark.unit
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def test_enrichment_extractor_uses_router_model_chain():
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from jarvis.reply import engine as engine_mod
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captured: dict[str, str] = {}
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def _fake_extract(query, base_url, chat_model, **kwargs):
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captured["chat_model"] = chat_model
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return {"keywords": [], "questions": []}
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cfg = MagicMock()
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cfg.ollama_base_url = "http://localhost:11434"
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cfg.ollama_chat_model = "big-chat"
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cfg.intent_judge_model = "small-judge"
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cfg.tool_router_model = ""
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cfg.llm_tools_timeout_sec = 5.0
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cfg.llm_thinking_enabled = False
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cfg.memory_enrichment_source = "diary"
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cfg.memory_enrichment_max_snippets = 3
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with patch.object(engine_mod, "extract_search_params_for_memory", side_effect=_fake_extract), \
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patch.object(engine_mod, "search_conversation_memory_by_keywords", return_value=[], create=True), \
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patch.object(engine_mod, "_build_enrichment_context_hint", return_value=""):
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# Call the internal enrichment helper directly via the same path the
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# engine does — if the symbol moves, this import will fail loudly.
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engine_mod.extract_search_params_for_memory(
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"hello",
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cfg.ollama_base_url,
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engine_mod.resolve_tool_router_model(cfg),
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timeout_sec=cfg.llm_tools_timeout_sec,
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thinking=cfg.llm_thinking_enabled,
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context_hint="",
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)
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assert captured["chat_model"] == "small-judge", (
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"enrichment extractor should resolve via resolve_tool_router_model, "
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"not cfg.ollama_chat_model"
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)
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@pytest.mark.unit
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def test_resolve_tool_router_model_is_public():
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"""The symbol is imported cross-layer (daemon, memory viewer, listener),
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so it must stay part of the public API — underscore-prefixed names are not
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allowed."""
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from jarvis.reply import engine
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assert hasattr(engine, "resolve_tool_router_model")
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assert not hasattr(engine, "_resolve_tool_router_model"), (
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"the private alias was removed — callers should use the public name"
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)
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