feat: Enhance plugin runtime configuration and hook management
- Added `inactive_plugins` field to `RunnerReadyPayload` and `ReloadPluginResultPayload` to track plugins that are not activated due to being disabled or unmet dependencies. - Introduced `InspectPluginConfigPayload` and `InspectPluginConfigResultPayload` for inspecting plugin configuration metadata. - Implemented `PluginActivationStatus` enum to better represent plugin activation states. - Updated `_activate_plugin` method to return activation status and handle inactive plugins accordingly. - Added hooks for send service to allow modification of messages before and after sending. - Created new runtime routes for listing hook specifications in the WebUI. - Refactored plugin configuration handling to utilize runtime inspection for better accuracy and flexibility. - Enhanced error handling and logging for plugin configuration operations.
This commit is contained in:
DrSmoothl
178
src/plugin_runtime/hook_payloads.py
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178
src/plugin_runtime/hook_payloads.py
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"""运行时 Hook 载荷序列化辅助。"""
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from __future__ import annotations
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from typing import Any, Dict, List, Sequence
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from src.chat.message_receive.message import SessionMessage
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from src.common.data_models.llm_service_data_models import PromptMessage
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from src.llm_models.payload_content.message import Message
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from src.llm_models.payload_content.tool_option import ToolCall, ToolDefinitionInput, normalize_tool_options
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from src.plugin_runtime.host.message_utils import PluginMessageUtils
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def serialize_session_message(message: SessionMessage) -> Dict[str, Any]:
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"""将会话消息序列化为 Hook 可传输载荷。
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Args:
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message: 待序列化的会话消息。
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Returns:
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Dict[str, Any]: 可通过插件运行时传输的消息字典。
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"""
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return dict(PluginMessageUtils._session_message_to_dict(message))
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def deserialize_session_message(raw_message: Any) -> SessionMessage:
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"""从 Hook 载荷恢复会话消息。
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Args:
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raw_message: Hook 返回的消息字典。
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Returns:
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SessionMessage: 恢复后的会话消息对象。
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Raises:
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ValueError: 消息结构不合法时抛出。
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"""
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if not isinstance(raw_message, dict):
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raise ValueError("Hook 返回的 `message` 必须是字典")
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return PluginMessageUtils._build_session_message_from_dict(raw_message)
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def serialize_tool_calls(tool_calls: Sequence[ToolCall] | None) -> List[Dict[str, Any]]:
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"""将工具调用列表序列化为 Hook 可传输载荷。
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Args:
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tool_calls: 原始工具调用列表。
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Returns:
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List[Dict[str, Any]]: 序列化后的工具调用列表。
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"""
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if not tool_calls:
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return []
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return [
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{
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"id": tool_call.call_id,
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"function": {
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"name": tool_call.func_name,
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"arguments": dict(tool_call.args or {}),
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},
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}
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for tool_call in tool_calls
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]
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def deserialize_tool_calls(raw_tool_calls: Any) -> List[ToolCall]:
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"""从 Hook 载荷恢复工具调用列表。
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Args:
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raw_tool_calls: Hook 返回的工具调用列表。
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Returns:
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List[ToolCall]: 恢复后的工具调用列表。
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Raises:
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ValueError: 结构不合法时抛出。
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"""
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if raw_tool_calls in (None, []):
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return []
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if not isinstance(raw_tool_calls, list):
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raise ValueError("Hook 返回的 `tool_calls` 必须是列表")
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normalized_tool_calls: List[ToolCall] = []
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for raw_tool_call in raw_tool_calls:
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if not isinstance(raw_tool_call, dict):
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raise ValueError("Hook 返回的工具调用项必须是字典")
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function_info = raw_tool_call.get("function", {})
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if isinstance(function_info, dict):
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function_name = function_info.get("name")
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function_arguments = function_info.get("arguments")
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else:
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function_name = raw_tool_call.get("name")
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function_arguments = raw_tool_call.get("arguments")
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call_id = raw_tool_call.get("id") or raw_tool_call.get("call_id")
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if not isinstance(call_id, str) or not isinstance(function_name, str):
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raise ValueError("Hook 返回的工具调用缺少 `id` 或函数名称")
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normalized_tool_calls.append(
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ToolCall(
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call_id=call_id,
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func_name=function_name,
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args=function_arguments if isinstance(function_arguments, dict) else {},
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)
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)
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return normalized_tool_calls
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def serialize_prompt_messages(messages: Sequence[Message]) -> List[PromptMessage]:
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"""将 LLM 消息列表序列化为 Hook 可传输载荷。
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Args:
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messages: 原始 LLM 消息列表。
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Returns:
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List[PromptMessage]: 序列化后的消息字典列表。
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"""
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serialized_messages: List[PromptMessage] = []
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for message in messages:
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serialized_message: PromptMessage = {
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"role": message.role.value,
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"content": message.content,
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}
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if message.tool_call_id:
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serialized_message["tool_call_id"] = message.tool_call_id
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if message.tool_calls:
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serialized_message["tool_calls"] = serialize_tool_calls(message.tool_calls)
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serialized_messages.append(serialized_message)
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return serialized_messages
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def deserialize_prompt_messages(raw_messages: Any) -> List[Message]:
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"""从 Hook 载荷恢复 LLM 消息列表。
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Args:
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raw_messages: Hook 返回的消息列表。
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Returns:
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List[Message]: 恢复后的 LLM 消息列表。
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Raises:
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ValueError: 结构不合法时抛出。
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"""
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if not isinstance(raw_messages, list):
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raise ValueError("Hook 返回的 `messages` 必须是列表")
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from src.services.llm_service import _build_message_from_dict
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normalized_messages: List[Message] = []
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for raw_message in raw_messages:
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if not isinstance(raw_message, dict):
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raise ValueError("Hook 返回的消息项必须是字典")
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normalized_messages.append(_build_message_from_dict(raw_message))
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return normalized_messages
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def serialize_tool_definitions(tool_definitions: Sequence[ToolDefinitionInput]) -> List[Dict[str, Any]]:
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"""将工具定义列表序列化为 Hook 可传输载荷。
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Args:
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tool_definitions: 原始工具定义列表。
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Returns:
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List[Dict[str, Any]]: 序列化后的工具定义列表。
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"""
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normalized_tool_options = normalize_tool_options(list(tool_definitions))
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if not normalized_tool_options:
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return []
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return [tool_option.to_openai_function_schema() for tool_option in normalized_tool_options]
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