feat(tools): introduce plugin-based tool discovery and runtime context protocol
This commit implements a progressive refactoring of the tool system to support plugin discovery, scoped loading, and protocol-driven runtime context injection. Key changes: - Add Tool ABC metadata (tool_name, _scopes) and ToolContext dataclass for dependency injection. - Introduce ToolLoader with pkgutil-based builtin discovery and entry_points-based third-party plugin loading. - Add scope filtering (core/subagent/memory) so different contexts load appropriate tool sets. - Introduce ContextAware protocol and RequestContext dataclass to replace hardcoded per-tool context injection in AgentLoop. - Add RuntimeState / MutableRuntimeState protocols to decouple MyTool from AgentLoop. - Migrate all built-in tools to declare scopes and implement create()/enabled() hooks. - Migrate MessageTool, SpawnTool, CronTool, and MyTool to ContextAware. - Refactor AgentLoop to use ToolLoader and protocol-driven context injection. - Refactor SubagentManager to use ToolLoader(scope="subagent") with per-run FileStates isolation. - Register all built-in tools via pyproject.toml entry_points. - Add comprehensive tests for loader scopes, entry_points, ContextAware, subagent tools, and runtime state sync.
This commit is contained in:
chengyongru
Xubin Ren
+62
-61
@@ -1,7 +1,8 @@
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"""Configuration schema using Pydantic."""
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from __future__ import annotations
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from pathlib import Path
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from typing import Any, Literal
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from typing import TYPE_CHECKING, Any, Literal
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from pydantic import AliasChoices, BaseModel, ConfigDict, Field
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from pydantic.alias_generators import to_camel
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@@ -9,12 +10,19 @@ from pydantic_settings import BaseSettings
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from nanobot.cron.types import CronSchedule
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if TYPE_CHECKING:
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from nanobot.agent.tools.image_generation import ImageGenerationToolConfig
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from nanobot.agent.tools.self import MyToolConfig
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from nanobot.agent.tools.shell import ExecToolConfig
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from nanobot.agent.tools.web import WebToolsConfig
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class Base(BaseModel):
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"""Base model that accepts both camelCase and snake_case keys."""
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model_config = ConfigDict(alias_generator=to_camel, populate_by_name=True)
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class ChannelsConfig(Base):
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"""Configuration for chat channels.
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@@ -198,45 +206,6 @@ class GatewayConfig(Base):
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heartbeat: HeartbeatConfig = Field(default_factory=HeartbeatConfig)
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class WebSearchConfig(Base):
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"""Web search tool configuration."""
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provider: str = "duckduckgo" # brave, tavily, duckduckgo, searxng, jina, kagi, olostep
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api_key: str = ""
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base_url: str = "" # SearXNG base URL
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max_results: int = 5
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timeout: int = 30 # Wall-clock timeout (seconds) for search operations
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class WebFetchConfig(Base):
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"""Web fetch tool configuration."""
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use_jina_reader: bool = True
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class WebToolsConfig(Base):
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"""Web tools configuration."""
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enable: bool = True
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proxy: str | None = (
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None # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
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)
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user_agent: str | None = None
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search: WebSearchConfig = Field(default_factory=WebSearchConfig)
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fetch: WebFetchConfig = Field(default_factory=WebFetchConfig)
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class ExecToolConfig(Base):
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"""Shell exec tool configuration."""
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enable: bool = True
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timeout: int = 60
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path_append: str = ""
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sandbox: str = "" # sandbox backend: "" (none) or "bwrap"
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allowed_env_keys: list[str] = Field(default_factory=list) # Env var names to pass through to subprocess (e.g. ["GOPATH", "JAVA_HOME"])
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allow_patterns: list[str] = Field(default_factory=list) # Regex patterns that bypass deny_patterns (e.g. [r"rm\s+-rf\s+/tmp/"])
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deny_patterns: list[str] = Field(default_factory=list) # Extra regex patterns to block (appended to built-in list)
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class MCPServerConfig(Base):
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"""MCP server connection configuration (stdio or HTTP)."""
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@@ -249,32 +218,28 @@ class MCPServerConfig(Base):
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tool_timeout: int = 30 # seconds before a tool call is cancelled
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enabled_tools: list[str] = Field(default_factory=lambda: ["*"]) # Only register these tools; accepts raw MCP names or wrapped mcp_<server>_<tool> names; ["*"] = all tools; [] = no tools
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class MyToolConfig(Base):
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"""Self-inspection tool configuration."""
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enable: bool = True # register the `my` tool (agent runtime state inspection)
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allow_set: bool = False # let `my` modify loop state (read-only if False)
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class ImageGenerationToolConfig(Base):
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"""Image generation tool configuration."""
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enabled: bool = False
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provider: str = "openrouter"
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model: str = "openai/gpt-5.4-image-2"
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default_aspect_ratio: str = "1:1"
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default_image_size: str = "1K"
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max_images_per_turn: int = Field(default=4, ge=1, le=8)
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save_dir: str = "generated"
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def _lazy_default(module_path: str, class_name: str) -> Any:
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"""Deferred import helper for ToolsConfig default factories."""
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import importlib
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module = importlib.import_module(module_path)
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return getattr(module, class_name)()
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class ToolsConfig(Base):
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"""Tools configuration."""
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"""Tools configuration.
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web: WebToolsConfig = Field(default_factory=WebToolsConfig)
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exec: ExecToolConfig = Field(default_factory=ExecToolConfig)
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my: MyToolConfig = Field(default_factory=MyToolConfig)
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image_generation: ImageGenerationToolConfig = Field(default_factory=ImageGenerationToolConfig)
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Field types for tool-specific sub-configs are resolved via model_rebuild()
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at the bottom of this file to avoid circular imports (tool modules import
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Base from schema.py).
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"""
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web: WebToolsConfig = Field(default_factory=lambda: _lazy_default("nanobot.agent.tools.web", "WebToolsConfig"))
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exec: ExecToolConfig = Field(default_factory=lambda: _lazy_default("nanobot.agent.tools.shell", "ExecToolConfig"))
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my: MyToolConfig = Field(default_factory=lambda: _lazy_default("nanobot.agent.tools.self", "MyToolConfig"))
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image_generation: ImageGenerationToolConfig = Field(
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default_factory=lambda: _lazy_default("nanobot.agent.tools.image_generation", "ImageGenerationToolConfig"),
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)
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restrict_to_workspace: bool = False # restrict all tool access to workspace directory
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mcp_servers: dict[str, MCPServerConfig] = Field(default_factory=dict)
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ssrf_whitelist: list[str] = Field(default_factory=list) # CIDR ranges to exempt from SSRF blocking (e.g. ["100.64.0.0/10"] for Tailscale)
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@@ -389,3 +354,39 @@ class Config(BaseSettings):
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return None
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model_config = ConfigDict(env_prefix="NANOBOT_", env_nested_delimiter="__")
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def _resolve_tool_config_refs() -> None:
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"""Resolve forward references in ToolsConfig by importing tool config classes.
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Must be called after all modules are loaded (breaks circular imports).
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Re-exports the classes into this module's namespace so existing imports
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like ``from nanobot.config.schema import ExecToolConfig`` continue to work.
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"""
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import sys
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from nanobot.agent.tools.image_generation import ImageGenerationToolConfig
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from nanobot.agent.tools.self import MyToolConfig
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from nanobot.agent.tools.shell import ExecToolConfig
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from nanobot.agent.tools.web import WebFetchConfig, WebSearchConfig, WebToolsConfig
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# Re-export into this module's namespace
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mod = sys.modules[__name__]
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mod.ExecToolConfig = ExecToolConfig # type: ignore[attr-defined]
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mod.WebToolsConfig = WebToolsConfig # type: ignore[attr-defined]
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mod.WebSearchConfig = WebSearchConfig # type: ignore[attr-defined]
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mod.WebFetchConfig = WebFetchConfig # type: ignore[attr-defined]
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mod.MyToolConfig = MyToolConfig # type: ignore[attr-defined]
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mod.ImageGenerationToolConfig = ImageGenerationToolConfig # type: ignore[attr-defined]
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ToolsConfig.model_rebuild()
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Config.model_rebuild()
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# Eagerly resolve when the import chain allows it (no circular deps at this
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# point). If it fails (first import triggers a cycle), the rebuild will
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# happen lazily when Config/ToolsConfig is first used at runtime.
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try:
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_resolve_tool_config_refs()
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except ImportError:
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pass
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