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https://github.com/HKUDS/nanobot.git
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3202f58c41
Extract duplicated bus/provider/loop initialization from CLI commands (serve, _run_gateway, agent) and Nanobot facade into a single AgentLoop.from_config() classmethod. - Remove _make_provider() from cli/commands.py and nanobot.py - Remove inline provider creation in all three CLI entry points - AgentLoop.from_config() creates MessageBus, calls make_provider(), and assembles AgentLoop with all standard config-derived parameters - Supports **extra overrides for callers that need custom args (e.g. cron_service, session_manager, provider_snapshot_loader) - Update tests to mock make_provider at nanobot.providers.factory and add from_config classmethod to _FakeAgentLoop fixtures This is PR 1/4 of the model-preset feature decomposition.
107 lines
3.1 KiB
Python
107 lines
3.1 KiB
Python
"""High-level programmatic interface to nanobot."""
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from __future__ import annotations
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any
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from nanobot.agent.hook import AgentHook, SDKCaptureHook
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from nanobot.agent.loop import AgentLoop
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@dataclass(slots=True)
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class RunResult:
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"""Result of a single agent run."""
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content: str
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tools_used: list[str]
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messages: list[dict[str, Any]]
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class Nanobot:
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"""Programmatic facade for running the nanobot agent.
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Usage::
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bot = Nanobot.from_config()
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result = await bot.run("Summarize this repo", hooks=[MyHook()])
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print(result.content)
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"""
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def __init__(self, loop: AgentLoop) -> None:
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self._loop = loop
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@classmethod
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def from_config(
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cls,
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config_path: str | Path | None = None,
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*,
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workspace: str | Path | None = None,
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) -> Nanobot:
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"""Create a Nanobot instance from a config file.
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Args:
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config_path: Path to ``config.json``. Defaults to
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``~/.nanobot/config.json``.
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workspace: Override the workspace directory from config.
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"""
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from nanobot.config.loader import load_config, resolve_config_env_vars
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from nanobot.config.schema import Config
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resolved: Path | None = None
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if config_path is not None:
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resolved = Path(config_path).expanduser().resolve()
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if not resolved.exists():
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raise FileNotFoundError(f"Config not found: {resolved}")
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config: Config = resolve_config_env_vars(load_config(resolved))
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if workspace is not None:
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config.agents.defaults.workspace = str(
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Path(workspace).expanduser().resolve()
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)
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loop = AgentLoop.from_config(
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config,
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image_generation_provider_configs={
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"openrouter": config.providers.openrouter,
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"aihubmix": config.providers.aihubmix,
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},
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)
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return cls(loop)
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async def run(
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self,
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message: str,
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*,
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session_key: str = "sdk:default",
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hooks: list[AgentHook] | None = None,
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) -> RunResult:
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"""Run the agent once and return the result.
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Args:
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message: The user message to process.
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session_key: Session identifier for conversation isolation.
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Different keys get independent history.
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hooks: Optional lifecycle hooks for this run.
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"""
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capture = SDKCaptureHook()
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prev = self._loop._extra_hooks
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base_hooks = list(hooks) if hooks is not None else list(prev or [])
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self._loop._extra_hooks = [capture, *base_hooks]
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try:
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response = await self._loop.process_direct(
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message, session_key=session_key,
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)
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finally:
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self._loop._extra_hooks = prev
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content = (response.content if response else None) or ""
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return RunResult(
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content=content,
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tools_used=capture.tools_used,
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messages=capture.messages,
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)
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