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* refactor(dream): replace two-phase Dream class with simple cron + process_direct - Remove the heavyweight Dream class (AgentRunner-based two-phase system) from nanobot/agent/memory.py - Delete dream_phase1.md and dream_phase2.md templates - New dream.md template serves as the consolidation prompt - Cron callback uses agent.process_direct(prompt, session_key=\"dream\") instead of agent.dream.run() - Always performs git auto_commit after execution - /dream command updated to use process_direct + git commit - DreamConfig kept for backward compatibility; deprecated fields (model_override, max_batch_size, max_iterations, annotate_line_ages) are ignored but accepted in config - interval_h remains configurable via agents.defaults.dream.interval_h - Update tests and webui settings to match new architecture * feat(loop): add ephemeral mode to process_direct, skip history writes for Dream When ephemeral=True, _state_save skips enforce_file_cap (which calls raw_archive -> append_history) and consolidator.maybe_consolidate_by_tokens. This prevents Dream sessions from creating a positive feedback loop where they process their own output. The session IS still saved to disk. * fix(loop): skip extra hooks for ephemeral sessions (Dream) * feat(dream): per-run timestamped sessions with rotation for WebUI * test(config): restore DreamConfig schedule and alias tests * fix(dream): include LLM response summary in git auto-commit message The old two-phase Dream class included the Phase 1 analysis in the git commit message body. The new single-phase version lost this. Restore it by extracting resp.content from the process_direct return value and appending it to the commit message in both the cron handler and the /dream command. * fix(test): accept ephemeral kwarg in test_openai_api fake_process * refactor(dream): merge dream_session.py into MemoryStore The standalone dream_session.py module only contained three small helpers that all revolve around MemoryStore concerns (session keys, commit messages, file pruning). Fold them into MemoryStore as @staticmethod to reduce indirection and avoid a 35-line module with no independent reason to exist. * fix(test): address code review — patch correct instance, use actual function - Fix test_ephemeral_skips_raw_archive to patch loop.context.memory instead of the fixture's separate MemoryStore instance - Fix TestDreamCommitMessage to call MemoryStore.build_dream_commit_message instead of reimplementing the logic inline - Move Dream helpers in memory.py above the Consolidator section comment to avoid misleading visual boundary * fix(dream): gate cursor advancement and restrict tools maintainer edit: Dream now processes backlog from the oldest unprocessed entries, only advances the cursor after a completed ephemeral run, and uses a restricted file-only tool registry for background consolidation. * fix(dream): skip idle compact for dream sessions Dream runs use internal dream:* sessions that are pruned by Dream retention. Exclude them from AutoCompact scheduling, archive execution, and summary injection so idle-session compaction cannot truncate Dream transcripts. * fix(dream): keep batched history isolated * feat(dream): tag archived memory for single-phase Dream --------- Co-authored-by: Xubin Ren <52506698+Re-bin@users.noreply.github.com>
102 lines
3.6 KiB
Python
102 lines
3.6 KiB
Python
from pathlib import Path
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from types import SimpleNamespace
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from unittest.mock import MagicMock
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from nanobot.agent.loop import AgentLoop
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from nanobot.bus.queue import MessageBus
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from nanobot.config.loader import save_config
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from nanobot.config.schema import Config
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from nanobot.providers.factory import ProviderSnapshot, load_provider_snapshot
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from nanobot.webui.settings_api import update_agent_settings
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def _provider(default_model: str, max_tokens: int = 123) -> MagicMock:
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provider = MagicMock()
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provider.get_default_model.return_value = default_model
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provider.generation = SimpleNamespace(max_tokens=max_tokens)
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return provider
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def test_provider_refresh_updates_all_model_dependents(tmp_path: Path) -> None:
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old_provider = _provider("old-model")
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new_provider = _provider("new-model", max_tokens=456)
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loop = AgentLoop(
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bus=MessageBus(),
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provider=old_provider,
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workspace=tmp_path,
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model="old-model",
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context_window_tokens=1000,
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provider_snapshot_loader=lambda: ProviderSnapshot(
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provider=new_provider,
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model="new-model",
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context_window_tokens=2000,
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signature=("new-model",),
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),
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)
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loop._refresh_provider_snapshot()
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assert loop.provider is new_provider
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assert loop.model == "new-model"
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assert loop.context_window_tokens == 2000
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assert loop.runner.provider is new_provider
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assert loop.subagents.provider is new_provider
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assert loop.subagents.model == "new-model"
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assert loop.subagents.runner.provider is new_provider
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assert loop.consolidator.provider is new_provider
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assert loop.consolidator.model == "new-model"
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assert loop.consolidator.context_window_tokens == 2000
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assert loop.consolidator.max_completion_tokens == 456
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def test_llm_runtime_refreshes_provider_snapshot(tmp_path: Path) -> None:
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old_provider = _provider("old-model")
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new_provider = _provider("new-model", max_tokens=456)
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loop = AgentLoop(
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bus=MessageBus(),
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provider=old_provider,
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workspace=tmp_path,
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model="old-model",
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context_window_tokens=1000,
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provider_snapshot_loader=lambda: ProviderSnapshot(
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provider=new_provider,
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model="new-model",
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context_window_tokens=2000,
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signature=("new-model",),
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),
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)
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runtime = loop.llm_runtime()
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assert runtime.provider is new_provider
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assert runtime.model == "new-model"
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assert loop.provider is new_provider
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assert loop.runner.provider is new_provider
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def test_settings_context_window_refreshes_runtime_state(
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tmp_path: Path,
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monkeypatch,
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) -> None:
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config_path = tmp_path / "config.json"
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config = Config()
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config.agents.defaults.workspace = str(tmp_path / "workspace")
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config.agents.defaults.model = "openai/gpt-4o"
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config.agents.defaults.provider = "openai"
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config.agents.defaults.context_window_tokens = 65_536
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config.providers.openai.api_key = "sk-test"
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save_config(config, config_path)
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monkeypatch.setattr("nanobot.config.loader._current_config_path", config_path)
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def loader(*, preset_name: str | None = None) -> ProviderSnapshot:
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return load_provider_snapshot(config_path, preset_name=preset_name)
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loop = AgentLoop.from_config(config, provider_snapshot_loader=loader)
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payload = update_agent_settings({"context_window_tokens": ["262144"]})
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loop._refresh_provider_snapshot()
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assert payload["requires_restart"] is False
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assert loop.context_window_tokens == 262_144
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assert loop.consolidator.context_window_tokens == 262_144
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