nanobot/nanobot/nanobot.py
chengyongru 7aa5b9b17b refactor(image-generation): introduce provider registry to eliminate manual wiring
Adds ImageGenerationProvider ABC with shared __init__, _http_post(), and
_require_images(). Introduces _IMAGE_GEN_PROVIDERS registry with
register/get/image_gen_provider_configs() helpers.

Four existing providers (OpenRouter, AIHubMix, Gemini, MiniMax) now inherit
from the base class and self-register. Adding a new provider only requires
writing one class + one registration line.

Eliminates if/else chains in the tool dispatch and hardcoded provider config
dicts in commands.py (3 sites) and nanobot.py (1 site). Fixes the agent CLI
command missing image_generation_provider_configs entirely.

Also simplifies test monkeypatch targets to patch the registry lookup.
2026-05-18 17:20:54 +08:00

105 lines
3.1 KiB
Python

"""High-level programmatic interface to nanobot."""
from __future__ import annotations
from dataclasses import dataclass
from pathlib import Path
from typing import Any
from nanobot.agent.hook import AgentHook, SDKCaptureHook
from nanobot.agent.loop import AgentLoop
from nanobot.providers.image_generation import image_gen_provider_configs
@dataclass(slots=True)
class RunResult:
"""Result of a single agent run."""
content: str
tools_used: list[str]
messages: list[dict[str, Any]]
class Nanobot:
"""Programmatic facade for running the nanobot agent.
Usage::
bot = Nanobot.from_config()
result = await bot.run("Summarize this repo", hooks=[MyHook()])
print(result.content)
"""
def __init__(self, loop: AgentLoop) -> None:
self._loop = loop
@classmethod
def from_config(
cls,
config_path: str | Path | None = None,
*,
workspace: str | Path | None = None,
) -> Nanobot:
"""Create a Nanobot instance from a config file.
Args:
config_path: Path to ``config.json``. Defaults to
``~/.nanobot/config.json``.
workspace: Override the workspace directory from config.
"""
from nanobot.config.loader import load_config, resolve_config_env_vars
from nanobot.config.schema import Config
resolved: Path | None = None
if config_path is not None:
resolved = Path(config_path).expanduser().resolve()
if not resolved.exists():
raise FileNotFoundError(f"Config not found: {resolved}")
config: Config = resolve_config_env_vars(load_config(resolved))
if workspace is not None:
config.agents.defaults.workspace = str(
Path(workspace).expanduser().resolve()
)
loop = AgentLoop.from_config(
config,
image_generation_provider_configs=image_gen_provider_configs(config),
)
return cls(loop)
async def run(
self,
message: str,
*,
session_key: str = "sdk:default",
hooks: list[AgentHook] | None = None,
) -> RunResult:
"""Run the agent once and return the result.
Args:
message: The user message to process.
session_key: Session identifier for conversation isolation.
Different keys get independent history.
hooks: Optional lifecycle hooks for this run.
"""
capture = SDKCaptureHook()
prev = self._loop._extra_hooks
base_hooks = list(hooks) if hooks is not None else list(prev or [])
self._loop._extra_hooks = [capture, *base_hooks]
try:
response = await self._loop.process_direct(
message, session_key=session_key,
)
finally:
self._loop._extra_hooks = prev
content = (response.content if response else None) or ""
return RunResult(
content=content,
tools_used=capture.tools_used,
messages=capture.messages,
)