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