chore: initial commit for Pretor v0.1.0-alpha

正式发布 Pretor 平台的首个 alpha 版本。本项目旨在构建一个基于分布式架构的多智能体协同工作流水线。

核心功能实现：
1. 建立基于 BaseIndividual 的动态插件加载机制。
2. 实现三类核心 worker_individual 子个体。
3. 集成 Ray 框架支持分布式集群调度。
4. 基于 PostgreSQL 的全量持久化存储方案。
5. 提供完整的 FastAPI 后端与 React 前端交互界面。

pretor/api/resource.py

@@ -0,0 +1,89 @@
+#  Copyright 2026 zhaoxi826
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+
+from pydantic import BaseModel
+import viceroy
+from pretor.core.workflow.workflow_template_generator.workflow_template import WorkflowTemplate
+from pretor.utils.ray_hook import ray_actor_hook
+from fastapi import APIRouter, Depends
+from pretor.utils.access import TokenData
+from pretor.utils.check_user.role_check import RoleChecker
+from pretor.core.database.table.user import UserAuthority
+
+resource_router = APIRouter(prefix="/api/v1/resource")
+
+@resource_router.post("/workflow_template")
+async def create_workflow_template(workflow_template: WorkflowTemplate,
+                                   _: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.USER))):
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    await global_state_machine.add_workflow_template.remote( workflow_template.name, workflow_template)
+    return {"message": "创建成功"}
+
+@resource_router.get("/workflow_template")
+async def get_workflow_templates(_: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.USER))):
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    templates = await global_state_machine.get_all_workflow_templates.remote()
+    return {"templates": templates}
+
+@resource_router.delete("/workflow_template/{template_name}")
+async def delete_workflow_template(template_name: str, _: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.SUPER_ADMINISTRATOR))):
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    await global_state_machine.delete_workflow_template.remote( template_name)
+    return {"message": "success"}
+
+
+
+class Skill(BaseModel):
+    repo_url: str
+    path: str | None
+
+@resource_router.post("/skill")
+async def install_skill(skill: Skill,
+                        _: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.USER))):
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    # noinspection PyUnresolvedReferences
+    import os
+    skill_output_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "plugin", "skill"))
+    os.makedirs(skill_output_dir, exist_ok=True)
+    await viceroy.install_skill_async(url = skill.repo_url,
+                                path = skill.path,
+                                output = skill_output_dir)
+    if skill.path:
+        skill_name = skill.path.split("/")[-1]
+    else:
+        skill_name = skill.repo_url.split("/")[-1]
+    await global_state_machine.add_skill.remote( skill_name)
+    return {"message": "创建成功"}
+
+@resource_router.get("/skill")
+async def get_skills(_: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.USER))):
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    skills = await global_state_machine.get_skill_list.remote()
+    return {"skills": skills}
+
+@resource_router.delete("/skill/{skill_name}")
+async def delete_skill(skill_name: str, _: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.SUPER_ADMINISTRATOR))):
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    # Note: this only removes it from the state machine manager.
+    await global_state_machine.remove_skill.remote( skill_name)
+    return {"message": "success"}
+
+@resource_router.get("/tool")
+async def get_tools(_: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.USER))):
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    tool_mapper = await global_state_machine.get_tool_mapper.remote()
+    all_tool_names = set()
+    for scope_tools in tool_mapper.values():
+        all_tool_names.update(scope_tools.keys())
+    return {"tools": list(all_tool_names)}