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https://github.com/NousResearch/hermes-agent.git
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346149c4f8
An "Estimate" action asks the auto-routed auxiliary model for a rough token
count + complexity band (S/M/L) with a one-line rationale — tokens, not
dollars, since providers don't report cost reliably. POST /estimate (typed
title/body, for the create dialog) and POST /tasks/{id}/estimate (existing
cards) share one core. Desktop renders it inline ("~15k tok · Medium") with a
"makes a model call" disclaimer; SDK exports compactNumber.
102 lines
3.4 KiB
Python
102 lines
3.4 KiB
Python
"""Kanban dashboard plugin: task effort estimate.
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The estimate endpoints call the auto-routed auxiliary model and parse a
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compact JSON reply (tokens + complexity + rationale). Tests monkeypatch
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``call_llm`` so no network is touched.
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"""
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from __future__ import annotations
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import importlib.util
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import sys
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import types
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from pathlib import Path
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import pytest
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from fastapi import FastAPI
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from fastapi.testclient import TestClient
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from hermes_cli import kanban_db as kb
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def _load_plugin_router():
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repo_root = Path(__file__).resolve().parents[2]
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plugin_file = repo_root / "plugins" / "kanban" / "dashboard" / "plugin_api.py"
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spec = importlib.util.spec_from_file_location("hermes_kanban_plugin_est_test", plugin_file)
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mod = importlib.util.module_from_spec(spec)
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sys.modules[spec.name] = mod
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spec.loader.exec_module(mod)
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return mod.router
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@pytest.fixture
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def kanban_home(tmp_path, monkeypatch):
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home = tmp_path / ".hermes"
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home.mkdir()
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monkeypatch.setenv("HERMES_HOME", str(home))
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monkeypatch.setattr(Path, "home", lambda: tmp_path)
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kb.init_db()
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return home
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@pytest.fixture
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def client(kanban_home):
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app = FastAPI()
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app.include_router(_load_plugin_router(), prefix="/api/plugins/kanban")
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return TestClient(app)
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def _fake_resp(content: str, model: str = "aux-mini"):
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msg = types.SimpleNamespace(content=content)
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return types.SimpleNamespace(choices=[types.SimpleNamespace(message=msg)], model=model)
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def test_estimate_parses_model_json(client, monkeypatch):
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task_id = client.post("/api/plugins/kanban/tasks", json={"title": "big refactor"}).json()["task"]["id"]
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import agent.auxiliary_client as aux
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def fake_call_llm(**kwargs):
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assert kwargs.get("task") == "kanban_estimator"
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return _fake_resp('{"est_tokens": 42000, "complexity": "M", "rationale": "multi-file edit"}')
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monkeypatch.setattr(aux, "call_llm", fake_call_llm)
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body = client.post(f"/api/plugins/kanban/tasks/{task_id}/estimate").json()
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assert body["ok"] is True
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assert body["est_tokens"] == 42000
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assert body["complexity"] == "M"
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assert body["rationale"] == "multi-file edit"
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assert body["model"] == "aux-mini"
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def test_estimate_tolerates_unparseable_reply(client, monkeypatch):
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task_id = client.post("/api/plugins/kanban/tasks", json={"title": "vague"}).json()["task"]["id"]
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import agent.auxiliary_client as aux
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monkeypatch.setattr(aux, "call_llm", lambda **kw: _fake_resp("I cannot estimate this, sorry."))
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assert client.post(f"/api/plugins/kanban/tasks/{task_id}/estimate").json()["ok"] is False
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def test_estimate_unknown_task_404(client):
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assert client.post("/api/plugins/kanban/tasks/t_missing/estimate").status_code == 404
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def test_estimate_from_text_no_task(client, monkeypatch):
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"""The create dialog estimates from typed title/body before a task exists."""
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import agent.auxiliary_client as aux
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monkeypatch.setattr(
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aux, "call_llm",
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lambda **kw: _fake_resp('{"est_tokens": 8000, "complexity": "S", "rationale": "localized"}'),
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)
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body = client.post(
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"/api/plugins/kanban/estimate", json={"title": "tweak a label", "body": "in settings"}
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).json()
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assert body["ok"] is True
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assert body["est_tokens"] == 8000
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assert body["complexity"] == "S"
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def test_estimate_from_text_requires_title(client):
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assert client.post("/api/plugins/kanban/estimate", json={"title": " ", "body": "x"}).json()["ok"] is False
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