c2743251e9
Self-evolving AI scientist framework built on LangGraph/LangChain with CLI/TUI core, FastAPI gateway, and Next.js frontend. Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>
226 lines
6.1 KiB
Python
226 lines
6.1 KiB
Python
"""Tests for shared persistent status-bar helpers."""
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from __future__ import annotations
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import asyncio
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from datetime import datetime, timedelta
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from typing import ClassVar
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from langchain_core.messages import HumanMessage
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from EvoScientist.cli.status_bar import (
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SessionStatusSnapshot,
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apply_assistant_text_to_snapshot,
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apply_user_text_to_snapshot,
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build_session_status_snapshot,
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build_status_fragments,
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build_status_text,
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make_usage_status_snapshot,
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shorten_model_name,
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status_style_name,
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trim_status_text,
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)
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def _render_fragments(fragments: list[tuple[str, str]]) -> str:
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return "".join(text for _, text in fragments)
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def test_build_status_fragments_wide_layout():
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snapshot = SessionStatusSnapshot(
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model_full="openai/gpt-5.4",
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model_short="gpt-5.4",
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context_tokens=12_345,
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context_window=128_000,
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context_percent=10,
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)
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rendered = _render_fragments(
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build_status_fragments(
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snapshot,
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datetime.now() - timedelta(minutes=3),
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100,
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)
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)
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assert "gpt-5.4" in rendered
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assert "12.3K/128K" in rendered
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assert "[█" in rendered
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assert "10%" in rendered
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assert "3m" in rendered
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def test_build_status_fragments_medium_layout():
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snapshot = SessionStatusSnapshot(
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model_full="openai/gpt-5.4",
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model_short="gpt-5.4",
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context_tokens=48_000,
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context_window=100_000,
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context_percent=48,
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)
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rendered = _render_fragments(
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build_status_fragments(
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snapshot,
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datetime.now() - timedelta(seconds=40),
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60,
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)
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)
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assert "gpt-5.4" in rendered
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assert "48%" in rendered
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assert "40s" in rendered
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assert "/" not in rendered
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def test_build_status_fragments_narrow_layout():
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snapshot = SessionStatusSnapshot(
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model_full="anthropic/claude-sonnet-4-20250514",
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model_short=shorten_model_name("anthropic/claude-sonnet-4-20250514"),
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context_tokens=95_000,
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context_window=100_000,
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context_percent=95,
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)
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rendered = _render_fragments(
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build_status_fragments(
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snapshot,
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datetime.now() - timedelta(hours=2),
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40,
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)
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)
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assert snapshot.model_short in rendered
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assert "2h" in rendered
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assert "%" not in rendered
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def test_trim_status_text_adds_ellipsis():
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assert trim_status_text("abcdefghijk", 8) == "abcde..."
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def test_status_style_name_thresholds():
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assert status_style_name(49) == "good"
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assert status_style_name(50) == "warn"
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assert status_style_name(80) == "warn"
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assert status_style_name(81) == "bad"
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assert status_style_name(95) == "critical"
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def test_build_status_text_uses_rich_styles():
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snapshot = SessionStatusSnapshot(
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model_full="openai/gpt-5.4",
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model_short="gpt-5.4",
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context_tokens=10_000,
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context_window=100_000,
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context_percent=10,
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)
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text = build_status_text(snapshot, datetime.now(), 100)
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assert str(text)
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assert text.spans
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def test_build_session_status_snapshot_uses_fallback_window(monkeypatch):
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async def _fake_messages(thread_id: str):
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assert thread_id == "thread-1"
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return [HumanMessage(content="existing")]
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class _FakeModel:
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model_name: ClassVar[str] = "provider/demo-model"
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profile: ClassVar[dict[str, object]] = {}
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def _fake_count(messages):
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assert len(messages) == 2
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assert messages[-1].content == "pending"
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return 42_000
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monkeypatch.setattr(
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"EvoScientist.cli.status_bar.get_thread_messages",
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_fake_messages,
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)
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monkeypatch.setattr(
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"EvoScientist.cli.status_bar._get_default_chat_model",
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lambda: _FakeModel(),
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)
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monkeypatch.setattr(
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"EvoScientist.cli.status_bar.count_tokens_approximately",
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_fake_count,
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)
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snapshot = asyncio.run(
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build_session_status_snapshot(
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"thread-1",
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pending_user_text="pending",
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)
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)
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assert snapshot.model_full == "provider/demo-model"
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assert snapshot.model_short == "demo-model"
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assert snapshot.context_tokens == 42_000
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assert snapshot.context_window == 200_000
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assert snapshot.context_percent == 21
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def test_apply_assistant_text_to_snapshot_updates_context(monkeypatch):
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snapshot = SessionStatusSnapshot(
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model_full="provider/demo-model",
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model_short="demo-model",
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context_tokens=10_000,
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context_window=100_000,
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context_percent=10,
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)
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monkeypatch.setattr(
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"EvoScientist.cli.status_bar.estimate_message_tokens",
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lambda text, message_type="ai": 550,
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)
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updated = apply_assistant_text_to_snapshot(snapshot, "streamed response")
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assert updated.context_tokens == 10_550
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assert updated.context_percent == 11
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def test_apply_user_text_to_snapshot_updates_context(monkeypatch):
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snapshot = SessionStatusSnapshot(
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model_full="provider/demo-model",
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model_short="demo-model",
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context_tokens=46_751,
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context_window=163_840,
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context_percent=29,
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context_source="usage",
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)
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monkeypatch.setattr(
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"EvoScientist.cli.status_bar.estimate_message_tokens",
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lambda text, message_type="human": 320,
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)
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updated = apply_user_text_to_snapshot(snapshot, "good")
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assert updated.context_tokens == 47_071
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assert updated.context_percent == 29
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assert updated.context_source == "usage"
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def test_make_usage_status_snapshot_marks_usage_source(monkeypatch):
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class _FakeModel:
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model_name: ClassVar[str] = "provider/demo-model"
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profile: ClassVar[dict[str, object]] = {"max_input_tokens": 128_000}
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monkeypatch.setattr(
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"EvoScientist.cli.status_bar._get_default_chat_model",
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lambda: _FakeModel(),
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)
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snapshot = make_usage_status_snapshot(42_000)
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assert snapshot.model_full == "provider/demo-model"
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assert snapshot.model_short == "demo-model"
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assert snapshot.context_tokens == 42_000
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assert snapshot.context_window == 128_000
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assert snapshot.context_percent == 33
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assert snapshot.context_source == "usage"
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