feat: implement plugin architecture and application settings with Svelte UI
- Added plugin base and loader for backend extensibility - Implemented application settings management with config persistence - Created Svelte-based frontend with Dashboard and Settings pages - Added API routes for plugins, tasks, and settings - Updated documentation and specifications - Improved project structure and developer tools
This commit is contained in:
140
backend/src/core/plugin_base.py
Normal file → Executable file
140
backend/src/core/plugin_base.py
Normal file → Executable file
@@ -1,71 +1,71 @@
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from abc import ABC, abstractmethod
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from typing import Dict, Any
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from pydantic import BaseModel, Field
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# [DEF:PluginBase:Class]
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# @SEMANTICS: plugin, interface, base, abstract
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# @PURPOSE: Defines the abstract base class that all plugins must implement to be recognized by the system. It enforces a common structure for plugin metadata and execution.
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# @LAYER: Core
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# @RELATION: Used by PluginLoader to identify valid plugins.
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# @INVARIANT: All plugins MUST inherit from this class.
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class PluginBase(ABC):
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"""
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Base class for all plugins.
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Plugins must inherit from this class and implement the abstract methods.
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"""
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@property
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@abstractmethod
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def id(self) -> str:
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"""A unique identifier for the plugin."""
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pass
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@property
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@abstractmethod
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def name(self) -> str:
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"""A human-readable name for the plugin."""
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pass
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@property
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@abstractmethod
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def description(self) -> str:
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"""A brief description of what the plugin does."""
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pass
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@property
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@abstractmethod
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def version(self) -> str:
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"""The version of the plugin."""
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pass
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@abstractmethod
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def get_schema(self) -> Dict[str, Any]:
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"""
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Returns the JSON schema for the plugin's input parameters.
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This schema will be used to generate the frontend form.
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"""
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pass
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@abstractmethod
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async def execute(self, params: Dict[str, Any]):
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"""
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Executes the plugin's logic.
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The `params` argument will be validated against the schema returned by `get_schema()`.
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"""
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pass
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# [/DEF]
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# [DEF:PluginConfig:Class]
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# @SEMANTICS: plugin, config, schema, pydantic
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# @PURPOSE: A Pydantic model used to represent the validated configuration and metadata of a loaded plugin. This object is what gets exposed to the API layer.
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# @LAYER: Core
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# @RELATION: Instantiated by PluginLoader after validating a PluginBase instance.
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class PluginConfig(BaseModel):
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"""Pydantic model for plugin configuration."""
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id: str = Field(..., description="Unique identifier for the plugin")
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name: str = Field(..., description="Human-readable name for the plugin")
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description: str = Field(..., description="Brief description of what the plugin does")
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version: str = Field(..., description="Version of the plugin")
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input_schema: Dict[str, Any] = Field(..., description="JSON schema for input parameters", alias="schema")
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from abc import ABC, abstractmethod
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from typing import Dict, Any
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from pydantic import BaseModel, Field
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# [DEF:PluginBase:Class]
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# @SEMANTICS: plugin, interface, base, abstract
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# @PURPOSE: Defines the abstract base class that all plugins must implement to be recognized by the system. It enforces a common structure for plugin metadata and execution.
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# @LAYER: Core
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# @RELATION: Used by PluginLoader to identify valid plugins.
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# @INVARIANT: All plugins MUST inherit from this class.
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class PluginBase(ABC):
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"""
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Base class for all plugins.
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Plugins must inherit from this class and implement the abstract methods.
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"""
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@property
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@abstractmethod
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def id(self) -> str:
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"""A unique identifier for the plugin."""
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pass
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@property
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@abstractmethod
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def name(self) -> str:
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"""A human-readable name for the plugin."""
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pass
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@property
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@abstractmethod
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def description(self) -> str:
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"""A brief description of what the plugin does."""
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pass
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@property
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@abstractmethod
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def version(self) -> str:
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"""The version of the plugin."""
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pass
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@abstractmethod
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def get_schema(self) -> Dict[str, Any]:
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"""
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Returns the JSON schema for the plugin's input parameters.
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This schema will be used to generate the frontend form.
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"""
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pass
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@abstractmethod
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async def execute(self, params: Dict[str, Any]):
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"""
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Executes the plugin's logic.
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The `params` argument will be validated against the schema returned by `get_schema()`.
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"""
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pass
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# [/DEF]
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# [DEF:PluginConfig:Class]
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# @SEMANTICS: plugin, config, schema, pydantic
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# @PURPOSE: A Pydantic model used to represent the validated configuration and metadata of a loaded plugin. This object is what gets exposed to the API layer.
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# @LAYER: Core
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# @RELATION: Instantiated by PluginLoader after validating a PluginBase instance.
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class PluginConfig(BaseModel):
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"""Pydantic model for plugin configuration."""
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id: str = Field(..., description="Unique identifier for the plugin")
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name: str = Field(..., description="Human-readable name for the plugin")
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description: str = Field(..., description="Brief description of what the plugin does")
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version: str = Field(..., description="Version of the plugin")
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input_schema: Dict[str, Any] = Field(..., description="JSON schema for input parameters", alias="schema")
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# [/DEF]
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