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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.
Performance tests
Per-context timings for the reply pipeline. Excluded from the default pytest run
(see pytest.ini's addopts = -m "not performance").
Running
pytest tests/performance/ -v -m performance -s
The -s flag lets the report table print to stdout. Tests auto-skip when Ollama
is unreachable, so the harness is safe to leave in the repo.
Env vars
| Var | Default | Description |
|---|---|---|
JARVIS_PERF_OLLAMA_URL |
http://localhost:11434 |
Ollama endpoint |
JARVIS_PERF_MODEL |
gemma4:e2b |
Model pulled in Ollama for the run |
JARVIS_PERF_RUNS |
3 |
Runs per query (bump for tighter p95) |
JARVIS_PERF_REPORT_DIR |
tests/performance/reports/ |
JSON report output |
PERF_RUNS=3 is a fast-iteration default. For stable p95 numbers when
benchmarking a change, use JARVIS_PERF_RUNS=10 or higher.
What it measures
test_micro_benchmark_tiny_prompt— one warmup + N tiny round-trips. Hardware baseline: the floor for every context's per-call cost.test_pipeline_timings_by_context— three representative queries × N runs ofrun_reply_engine, with per-context timings bucketed via stack-frame inspection intiming_recorder.py.
Shape invariants (not absolute numbers):
- Evaluator p50 ≤ main chat turn p50 × 1.5.
- Tool router p50 ≤ main chat turn p50 × 1.5.
- Enrichment extractor shares the router model chain.
Unmapped callers print as other:<qualname> — that's a signal to update the
_CALLER_TO_CONTEXT map in timing_recorder.py alongside docs/llm_contexts.md.
Reports are written to reports/ and git-ignored.