400cd69261
`hermes model` (and `hermes setup`) gain a Local models row whenever PM pins an engine for this machine. The flow drives the handlers behind the desktop's Local Models pane in-process, so both surfaces run one code path: the catalog priced for this machine (★ = recommendation), models already on disk, quickstart (pinned engine, model download, server start, default assignment) and activate. Progress renders from the job view the desktop polls; Ctrl+C pauses a download and choosing the model again resumes from the kept bytes. Verified: a catalog download paused at 3% and resumed to completion, activation of an on-disk model, and `hermes -z` / interactive chat against the result.
63 lines
2.8 KiB
Python
63 lines
2.8 KiB
Python
"""``hermes model`` → Local models runs the desktop's Local Models setup in the terminal."""
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from __future__ import annotations
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import pytest
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def _picker_keys(config: dict) -> list[str]:
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from hermes_cli.main_provider_setup import _build_provider_picker_rows
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return [key for key, _, _ in _build_provider_picker_rows(config, "", {}, {})[0]]
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def test_local_models_row_follows_the_engine_pin_and_exclusions():
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from hermes_cli.local_runtime import binaries
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assert ("llamacpp" in _picker_keys({})) == (binaries.unavailable_reason("cpu") is None)
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assert "llamacpp" not in _picker_keys({"model_catalog": {"excluded_providers": ["llama.cpp"]}})
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@pytest.mark.parametrize("outcome", ["done", "error"])
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def test_picked_model_runs_the_quickstart_job_and_reports_how_it_ended(monkeypatch, capsys, outcome):
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"""The CLI starts the same quickstart job the desktop's button does and reports that job's
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terminal state; only a finished job claims the default changed."""
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import hermes_cli.main_provider_setup as provider_setup
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import hermes_cli.setup as setup
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from hermes_cli.model_setup_flows_local import _model_flow_local
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from hermes_cli.web_routers import local_models as lm
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row = {"id": "tiny", "display_name": "Tiny", "fits": True, "needs_engine": False, "recommended": True,
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"downloaded": False, "size_label": "1.0 GB", "fit_summary": "runs fully on your GPU"}
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monkeypatch.setattr(lm, "local_models_hardware", lambda: {"gpu_name": "GPU", "vram_label": "8.0 GB"})
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monkeypatch.setattr(lm, "local_models_status", lambda: {
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"runtime_installed": True, "tag": "b1", "runtime_backend": "cpu", "models": [], "active_model_id": None})
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monkeypatch.setattr(lm, "local_models_catalog", lambda: {"models": [row]})
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started = []
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def quickstart(body):
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started.append(body.model_id)
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job = lm._job("quickstart", "Tiny", model_id=body.model_id)
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def run():
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lm._step(job, "downloading", "Downloading Tiny")
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if outcome == "error":
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raise RuntimeError("disk full")
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lm._finish(job, "Tiny is ready — new chats use it")
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lm._spawn_job(job, "test-quickstart", run, resumable=True)
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return {"job_id": job["job_id"]}
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monkeypatch.setattr(lm, "local_models_quickstart", quickstart)
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monkeypatch.setattr(provider_setup, "_prompt_provider_choice", lambda labels, default=0, title="": default)
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monkeypatch.setattr(setup, "prompt_yes_no", lambda question, default=True: True)
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_model_flow_local({}, "")
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out = capsys.readouterr().out
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assert started == ["tiny"]
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if outcome == "done":
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assert "✓ Tiny is ready" in out and "Default model set to: Tiny" in out
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else:
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assert "✗ disk full" in out and "Default model set to" not in out
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