105 lines
5.2 KiB
Python
105 lines
5.2 KiB
Python
# Copyright 2026 zhaoxi826
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from pydantic import BaseModel
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import viceroy
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from pretor.utils.ray_hook import ray_actor_hook
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from fastapi import APIRouter, Depends
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from pretor.utils.access import TokenData
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from pretor.utils.check_user.role_check import RoleChecker
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from pretor.core.postgres_database.table import UserAuthority
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resource_router = APIRouter(prefix="/api/v1/resource")
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class Skill(BaseModel):
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"""Skill 核心组件类。
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这是一个领域数据模型或功能封装类，承载了 Skill 相关的内聚属性定义与状态维护。它的存在隔离了局部的业务复杂性，并对外提供了类型安全的访问接口。"""
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repo_url: str
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path: str | None
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@resource_router.post("/skill")
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async def install_skill(
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skill: Skill, _: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.USER))
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):
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"""处理针对 install skill 相关的 HTTP API 请求。
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该接口负责解析前端传入的载荷数据，调用底层核心业务逻辑进行处理，并组装标准化的 JSON 响应。
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Args: skill (Skill): 参与 install skill 逻辑运算或数据构建的上下文依赖对象。 _ (TokenData): 参与 install skill 逻辑运算或数据构建的上下文依赖对象。
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Returns: : 序列化后的标准网络响应模型（如包含业务状态码、成功标志及对应的数据载荷 Data）。"""
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global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
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# noinspection PyUnresolvedReferences
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import os
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skill_output_dir = os.path.abspath(
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os.path.join(os.path.dirname(__file__), "..", "plugin", "skill")
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)
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os.makedirs(skill_output_dir, exist_ok=True)
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await viceroy.install_skill_async(
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url=skill.repo_url, path=skill.path, output=skill_output_dir
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)
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if skill.path:
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skill_name = skill.path.split("/")[-1]
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else:
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skill_name = skill.repo_url.split("/")[-1]
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await global_state_machine.add_skill.remote(skill_name)
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return {"message": "创建成功"}
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@resource_router.get("/skill")
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async def get_skills(
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_: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.USER)),
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):
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"""处理针对 get skills 相关的 HTTP API 请求。
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该接口负责解析前端传入的载荷数据，调用底层核心业务逻辑进行处理，并组装标准化的 JSON 响应。
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Args: _ (TokenData): 参与 get skills 逻辑运算或数据构建的上下文依赖对象。
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Returns: : 序列化后的标准网络响应模型（如包含业务状态码、成功标志及对应的数据载荷 Data）。"""
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global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
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skills = await global_state_machine.get_skill_list.remote()
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return {"skills": skills}
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@resource_router.delete("/skill/{skill_name}")
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async def delete_skill(
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skill_name: str,
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_: TokenData = Depends(
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RoleChecker(allowed_roles=UserAuthority.SUPER_ADMINISTRATOR)
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),
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):
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"""处理针对 delete skill 相关的 HTTP API 请求。
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该接口负责解析前端传入的载荷数据，调用底层核心业务逻辑进行处理，并组装标准化的 JSON 响应。
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Args: skill_name (str): 赋予该实体的人类可读名称或标题字符串，主要用于前端 UI 展示、日志记录或模糊检索。 _ (TokenData): 参与 delete skill 逻辑运算或数据构建的上下文依赖对象。
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Returns: : 序列化后的标准网络响应模型（如包含业务状态码、成功标志及对应的数据载荷 Data）。"""
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global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
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# Note: this only removes it from the state machine manager.
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await global_state_machine.remove_skill.remote(skill_name)
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return {"message": "success"}
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@resource_router.get("/tool")
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async def get_tools(
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_: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.USER)),
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):
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"""处理针对 get tools 相关的 HTTP API 请求。
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该接口负责解析前端传入的载荷数据，调用底层核心业务逻辑进行处理，并组装标准化的 JSON 响应。
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Args: _ (TokenData): 参与 get tools 逻辑运算或数据构建的上下文依赖对象。
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Returns: : 序列化后的标准网络响应模型（如包含业务状态码、成功标志及对应的数据载荷 Data）。"""
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global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
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tool_mapper = await global_state_machine.get_tool_mapper.remote()
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all_tool_names = set()
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for scope_tools in tool_mapper.values():
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all_tool_names.update(scope_tools.keys())
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return {"tools": list(all_tool_names)}
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