✨ Enhance skill management, add tool integrations, and overhaul Chat UI (#44)

* feat: restructure skills, introduce tools, and enhance chat UI

- Split worker_individual.py into separate component files: base, ordinary, special, and skill individuals.
- Update skill download and resolution paths to absolute references matching viceroy capabilities, correcting tmp and docker access issues.
- Introduce `GET /api/v1/resource/tool` and dynamic File Tool for agents to read file content.
- Update frontend Resource view to display tools instead of resource stubs.
- Convert Dashboard to Chat view, splitting chat interface to support standard chat or workflow deployment by appending prompt prefixes.

Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com>

* feat: restructure skills, introduce tools, and enhance chat UI

- Split worker_individual.py into separate component files: base, ordinary, special, and skill individuals.
- Update skill download and resolution paths to absolute references matching viceroy capabilities, correcting tmp and docker access issues.
- Introduce `GET /api/v1/resource/tool` and dynamic File Tool for agents to read file content.
- Update frontend Resource view to display tools instead of resource stubs.
- Convert Dashboard to Chat view, splitting chat interface to support standard chat or workflow deployment by appending prompt prefixes.

Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com>

---------

Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com>

frontend/src/components/Chat/ChatPanel.tsx

@@ -77,8 +77,9 @@ export function ChatPanel() {
 
     try {
       // Assuming a token might be needed, apiClient should handle it if set
+      const promptModifier = mode === 'deploy' ? '[DEPLOY TASK] ' : '';
       const response = await apiClient.post('/api/v1/adapter/client', {
-        message: userMessage.text
+        message: promptModifier + userMessage.text
       });
 
       const aiMessage: ChatMessage = {
@@ -113,11 +114,29 @@ export function ChatPanel() {
     }
   };
 
+  const [mode, setMode] = useState<'chat' | 'deploy'>('chat');
+
   return (
     <div className="flex-1 flex flex-col bg-slate-50">
-      <div className="h-14 border-b border-slate-200 bg-white flex items-center px-6 shadow-sm z-10">
+      <div className="h-14 border-b border-slate-200 bg-white flex items-center justify-between px-6 shadow-sm z-10">
-        <MessageSquare size={18} className="text-blue-600 mr-3" />
+        <div className="flex items-center">
-        <h1 className="font-semibold text-slate-800">Pretor Assistant</h1>
+          <MessageSquare size={18} className="text-blue-600 mr-3" />
+          <h1 className="font-semibold text-slate-800">Pretor Assistant</h1>
+        </div>
+        <div className="flex space-x-2 bg-slate-100 p-1 rounded-lg">
+          <button
+            onClick={() => setMode('chat')}
+            className={`px-3 py-1 text-sm font-medium rounded-md transition-colors ${mode === 'chat' ? 'bg-white text-blue-600 shadow-sm' : 'text-slate-500 hover:text-slate-700'}`}
+          >
+            Chat
+          </button>
+          <button
+            onClick={() => setMode('deploy')}
+            className={`px-3 py-1 text-sm font-medium rounded-md transition-colors ${mode === 'deploy' ? 'bg-white text-blue-600 shadow-sm' : 'text-slate-500 hover:text-slate-700'}`}
+          >
+            Deploy Task
+          </button>
+        </div>
       </div>
 
       {/* Chat History */}

frontend/src/components/Layout/Sidebar.tsx

@@ -20,7 +20,7 @@ export function Sidebar({ currentView, setCurrentView }: SidebarProps) {
         <button
           onClick={() => setCurrentView('dashboard')}
           className={`p-1.5 rounded-lg transition-colors ${currentView === 'dashboard' ? 'text-blue-600 bg-blue-50' : 'text-slate-400 hover:text-blue-500 hover:bg-blue-50'}`}
-          title="Dashboard"
+          title="Chat"
         >
           <MessageSquare size={18} />
         </button>

frontend/src/components/Resource/ResourceLayout.tsx

@@ -1,6 +1,6 @@
 import { Wrench, Database, FileCode } from 'lucide-react';
 import { SkillSettings } from './SkillSettings';
-import { ResourceSettings } from './ResourceSettings';
+import { ToolSettings } from './ToolSettings';
 import { WorkflowTemplateSettings } from './WorkflowTemplateSettings';
 
 interface ResourceLayoutProps {
@@ -32,11 +32,11 @@ export function ResourceLayout({ resourceTab, setResourceTab }: ResourceLayoutPr
                Workflow Templates
              </button>
              <button
-               onClick={() => setResourceTab('resource')}
+               onClick={() => setResourceTab('tool')}
-               className={`w-full flex items-center px-4 py-3 text-sm font-medium rounded-xl transition-all ${resourceTab === 'resource' ? 'bg-blue-50 text-blue-600' : 'text-slate-600 hover:bg-slate-50 hover:text-slate-900'}`}
+               className={`w-full flex items-center px-4 py-3 text-sm font-medium rounded-xl transition-all ${resourceTab === 'tool' ? 'bg-blue-50 text-blue-600' : 'text-slate-600 hover:bg-slate-50 hover:text-slate-900'}`}
              >
                <Database size={18} className="mr-3" />
-               Resources
+               Tools
              </button>
           </div>
        </div>
@@ -45,7 +45,7 @@ export function ResourceLayout({ resourceTab, setResourceTab }: ResourceLayoutPr
        <div className="flex-1 overflow-y-auto p-8">
           {resourceTab === 'skill' && <SkillSettings />}
           {resourceTab === 'workflow_template' && <WorkflowTemplateSettings />}
-          {resourceTab === 'resource' && <ResourceSettings />}
+          {resourceTab === 'tool' && <ToolSettings />}
        </div>
     </div>
   );

frontend/src/components/Resource/ResourceSettings.tsx

@@ -1,13 +0,0 @@
-export function ResourceSettings() {
-  return (
-    <div className="max-w-4xl space-y-6">
-      <div className="mb-8">
-        <h1 className="text-2xl font-bold text-slate-800">Resource Management</h1>
-        <p className="text-slate-500 mt-1">Manage external and internal resources.</p>
-      </div>
-      <div className="bg-white rounded-xl shadow-sm border border-slate-200 overflow-hidden p-6 text-slate-500 text-sm">
-        Resource management configuration coming soon...
-      </div>
-    </div>
-  );
-}

frontend/src/components/Resource/ToolSettings.tsx

@@ -0,0 +1,64 @@
+import { useState, useEffect } from 'react';
+import { Package } from 'lucide-react';
+import apiClient from '../../api/client';
+
+export function ToolSettings() {
+  const [tools, setTools] = useState<string[]>([]);
+  const [loading, setLoading] = useState(true);
+
+  useEffect(() => {
+    fetchTools();
+  }, []);
+
+  const fetchTools = async () => {
+    try {
+      setLoading(true);
+      const response = await apiClient.get('/api/v1/resource/tool');
+      const toolsData = response.data.tools || [];
+      setTools(toolsData);
+    } catch (err) {
+      console.error('Failed to fetch tools:', err);
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  return (
+    <div className="max-w-4xl space-y-6">
+      <div>
+        <h3 className="text-xl font-semibold text-slate-800">Installed Tools</h3>
+        <p className="text-slate-500 mt-1">Manage agent tools and functions.</p>
+      </div>
+
+      <div className="bg-white border border-slate-200 rounded-2xl shadow-sm overflow-hidden">
+        <div className="p-6 border-b border-slate-100 flex justify-between items-center bg-slate-50/50">
+          <div>
+            <h4 className="font-medium text-slate-800">Available Tools</h4>
+            <p className="text-sm text-slate-500">List of installed tools available for agents.</p>
+          </div>
+        </div>
+
+        <div className="p-6">
+          {loading ? (
+            <div className="text-slate-500 text-sm">Loading tools...</div>
+          ) : tools.length === 0 ? (
+            <div className="text-slate-500 text-sm">No tools installed yet.</div>
+          ) : (
+            <div className="grid grid-cols-1 md:grid-cols-2 gap-4">
+              {tools.map((tool) => (
+                <div key={tool} className="p-4 border border-slate-200 rounded-xl flex items-center justify-between hover:shadow-sm transition-shadow">
+                  <div className="flex items-center">
+                    <div className="w-10 h-10 bg-purple-50 rounded-lg flex items-center justify-center mr-3">
+                      <Package size={20} className="text-purple-600" />
+                    </div>
+                    <span className="font-medium text-slate-800">{tool}</span>
+                  </div>
+                </div>
+              ))}
+            </div>
+          )}
+        </div>
+      </div>
+    </div>
+  );
+}

pretor/api/resource.py

@@ -53,9 +53,12 @@ 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 = "./pretor/plugin/tool_plugin")
+                                output = skill_output_dir)
     if skill.path:
         skill_name = skill.path.split("/")[-1]
     else:
@@ -75,3 +78,9 @@ async def delete_skill(skill_name: str, _: TokenData = Depends(RoleChecker(allow
     # 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
+    tools = await global_state_machine.get_tool_list.remote("default")
+    return {"tools": list(tools.keys())}

pretor/core/global_state_machine/skill_manager.py

@@ -24,7 +24,8 @@ class GlobalSkillManager:
     def __init__(self):
         self.skill_mapper = defaultdict(tuple)
 
-        skill_plugin_dir = pathlib.Path(__file__).parent.parent.parent / "plugin" / "skill_plugin"
+        import os
+        skill_plugin_dir = pathlib.Path(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", "plugin", "skill")))
         if not skill_plugin_dir.exists() or not skill_plugin_dir.is_dir():
             return
         for item in skill_plugin_dir.iterdir():
@@ -46,7 +47,8 @@ class GlobalSkillManager:
 
     def add_skill(self, skill_name: str) -> None:
         """Add a skill to the manager by reading its skill.json from the path"""
-        skill_plugin_dir = pathlib.Path(__file__).parent.parent.parent / "plugin" / "skill_plugin"
+        import os
+        skill_plugin_dir = pathlib.Path(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", "plugin", "skill")))
         item = skill_plugin_dir / skill_name
         if item.is_dir() and not item.name.startswith((".", "__")):
             json_path = item / "skill.json"

pretor/plugin/tool_plugin/file_reader/__init__.py

@@ -0,0 +1,3 @@
+from .file_reader import FileReaderData, file_reader
+
+__all__ = ["FileReaderData", "file_reader"]

pretor/plugin/tool_plugin/file_reader/file_reader.py

@@ -0,0 +1,42 @@
+#  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_ai import RunContext
+from pretor.plugin.tool_plugin.base_tool import BaseToolData
+import os
+
+class FileReaderData(BaseToolData):
+    name: str = "file_reader"
+    description: str = "读取本地文件的内容"
+
+def file_reader(ctx: RunContext, filepath: str) -> str:
+    """读取本地文件内容的工具。
+
+    Args:
+        filepath: 目标文件的绝对路径或相对路径。
+
+    Returns:
+        如果文件存在并可读，返回文件内容；否则返回错误信息。
+    """
+    if not os.path.exists(filepath):
+        return f"Error: 文件 {filepath} 不存在。"
+    if not os.path.isfile(filepath):
+        return f"Error: {filepath} 不是一个文件。"
+
+    try:
+        with open(filepath, 'r', encoding='utf-8') as f:
+            content = f.read()
+        return content
+    except Exception as e:
+        return f"Error: 读取文件失败，原因：{str(e)}"

pretor/worker_individual/__init__.py

@@ -0,0 +1,11 @@
+from pretor.worker_individual.base_individual import BaseIndividual
+from pretor.worker_individual.skill_individual import SkillIndividual
+from pretor.worker_individual.ordinary_individual import OrdinaryIndividual
+from pretor.worker_individual.special_individual import SpecialIndividual
+
+__all__ = [
+    "BaseIndividual",
+    "SkillIndividual",
+    "OrdinaryIndividual",
+    "SpecialIndividual",
+]

pretor/worker_individual/base_individual.py

@@ -0,0 +1,70 @@
+#  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_ai import Agent, RunContext
+from pydantic import Field
+from pretor.adapter.model_adapter.agent_factory import AgentFactory
+from pretor.core.global_state_machine.model_provider.base_provider import Provider
+from pretor.utils.agent_model import ResponseModel, InputModel, DepsModel
+from pretor.utils.ray_hook import ray_actor_hook
+
+from pretor.utils.logger import get_logger
+logger = get_logger('worker_individual')
+
+class WorkerIndividualResponse(ResponseModel):
+    output: str = Field(..., description="Worker执行任务的输出结果")
+
+class WorkerIndividualDeps(DepsModel):
+    task_event: dict
+
+class WorkerIndividualInput(InputModel):
+    task_event: dict
+
+class BaseIndividual:
+    """
+    Worker Individual 的基类
+    """
+
+    def __init__(self, agent_config: dict):
+        self.agent_config = agent_config
+        self.agent_id = agent_config.get("agent_id")
+        self.agent: Agent | None = None
+
+    async def _init_agent(self, agent_name: str, system_prompt: str):
+        global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+        provider_title = self.agent_config.get("provider_title", "openai")  # default fallback
+        model_id = self.agent_config.get("model_id", "gpt-4o")  # default fallback
+
+        provider: Provider = await global_state_machine.get_provider.remote( provider_title)
+        agent_factory = AgentFactory()
+        self.agent = agent_factory.create_agent(
+            provider=provider,
+            model_id=model_id,
+            output_type=WorkerIndividualResponse,
+            system_prompt=system_prompt,
+            deps_type=WorkerIndividualDeps,
+            agent_name=agent_name
+        )
+
+        @self.agent.system_prompt
+        async def dynamic_prompt(ctx: RunContext[WorkerIndividualDeps]):
+            prompt = system_prompt + "\n\n"
+            prompt += (
+                f"=== 当前任务上下文 ===\n"
+                f"{ctx.deps.task_event}\n"
+            )
+            return prompt
+
+    async def run(self, task_event: dict) -> dict:
+        raise NotImplementedError("子类必须实现 run 方法")

pretor/worker_individual/ordinary_individual.py

@@ -0,0 +1,43 @@
+#  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 pretor.worker_individual.base_individual import BaseIndividual, WorkerIndividualDeps
+from pretor.utils.logger import get_logger
+
+logger = get_logger('ordinary_individual')
+
+class OrdinaryIndividual(BaseIndividual):
+    """
+    普通子个体：普通的 agent。
+    """
+
+    def __init__(self, agent_config: dict):
+        super().__init__(agent_config)
+
+    async def run(self, task_event: dict) -> dict:
+        if self.agent is None:
+            system_prompt = self.agent_config.get("prompt", "你是一个普通的AI助手，请尽力完成给定的任务。")
+            await self._init_agent("ordinary_individual", system_prompt)
+
+        deps = WorkerIndividualDeps(task_event=task_event)
+        self.agent.retries = 3
+        try:
+            result = await self.agent.run(
+                f"请执行以下任务：\n{task_event}",
+                deps=deps
+            )
+            return {"output": result.data.output}
+        except Exception as e:
+            logger.exception(f"OrdinaryIndividual {self.agent_id} 执行失败: {e}")
+            raise

pretor/worker_individual/skill_individual.py

@@ -0,0 +1,110 @@
+#  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 pretor.worker_individual.base_individual import BaseIndividual, WorkerIndividualDeps
+from pretor.utils.logger import get_logger
+import os
+import json
+from pydantic_ai import Tool
+import importlib.util
+
+logger = get_logger('skill_individual')
+
+class SkillIndividual(BaseIndividual):
+    """
+    专家子个体：拥有专业 skill 的 agent。
+    """
+
+    def __init__(self, agent_config: dict):
+        super().__init__(agent_config)
+
+    async def _load_skill_tools(self):
+        """动态加载已绑定的 skill 工具。"""
+        tools = []
+        bound_skill = self.agent_config.get("bound_skill", "")
+        # bound_skill can be string or dict {"skill_name": ["file1", "file2"]}
+        skill_mapper = {}
+        if isinstance(bound_skill, str) and bound_skill:
+            try:
+                skill_mapper = json.loads(bound_skill)
+            except json.JSONDecodeError:
+                pass
+        elif isinstance(bound_skill, dict):
+            skill_mapper = bound_skill
+
+        skill_base_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "plugin", "skill"))
+
+        for skill_name, _ in skill_mapper.items():
+            skill_path = os.path.join(skill_base_dir, skill_name)
+            metadata_path = os.path.join(skill_path, "metadata.json")
+            if not os.path.exists(metadata_path):
+                continue
+
+            try:
+                with open(metadata_path, 'r', encoding='utf-8') as f:
+                    metadata = json.load(f)
+            except Exception as e:
+                logger.error(f"Failed to load metadata for skill {skill_name}: {e}")
+                continue
+
+            if "functions" in metadata:
+                for func_info in metadata["functions"]:
+                    # Ensure path is absolute
+                    script_path = func_info.get("file_path", "")
+                    if not os.path.isabs(script_path):
+                        script_path = os.path.join(skill_path, script_path)
+
+                    if not os.path.exists(script_path):
+                        logger.warning(f"Skill script not found: {script_path}")
+                        continue
+
+                    func_name = func_info.get("name")
+                    try:
+                        # Dynamically load the python module
+                        spec = importlib.util.spec_from_file_location(func_name, script_path)
+                        module = importlib.util.module_from_spec(spec)
+                        spec.loader.exec_module(module)
+
+                        func = getattr(module, func_name)
+                        if callable(func):
+                            # Convert to PydanticAI Tool
+                            tool = Tool(func, name=func_name, description=func_info.get("docstring", ""))
+                            tools.append(tool)
+                            logger.info(f"Loaded skill tool: {func_name} from {skill_name}")
+                    except Exception as e:
+                        logger.error(f"Failed to load function {func_name} from {script_path}: {e}")
+
+        return tools
+
+    async def run(self, task_event: dict) -> dict:
+        if self.agent is None:
+            system_prompt = self.agent_config.get("prompt",
+                                                  "你是一个拥有专业技能的专家级AI助手，请利用你的专业知识完成给定的任务。")
+            await self._init_agent("skill_individual", system_prompt)
+
+        deps = WorkerIndividualDeps(task_event=task_event)
+        self.agent.retries = 3
+
+        tools = await self._load_skill_tools()
+
+        try:
+            result = await self.agent.run(
+                f"请执行以下任务：\n{task_event}",
+                deps=deps,
+                tools=tools if tools else None
+            )
+            return {"output": result.data.output}
+        except Exception as e:
+            logger.exception(f"SkillIndividual {self.agent_id} 执行失败: {e}")
+            raise

pretor/worker_individual/special_individual.py

@@ -0,0 +1,43 @@
+#  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 pretor.worker_individual.base_individual import BaseIndividual, WorkerIndividualDeps
+from pretor.utils.logger import get_logger
+
+logger = get_logger('special_individual')
+
+class SpecialIndividual(BaseIndividual):
+    """
+    特殊子个体：执行特殊任务的 agent，如生成语音、视频等。
+    """
+
+    def __init__(self, agent_config: dict):
+        super().__init__(agent_config)
+
+    async def run(self, task_event: dict) -> dict:
+        if self.agent is None:
+            system_prompt = self.agent_config.get("prompt", "你是一个特殊的AI助手，负责处理特殊类型的任务。")
+            await self._init_agent("special_individual", system_prompt)
+
+        deps = WorkerIndividualDeps(task_event=task_event)
+        self.agent.retries = 3
+        try:
+            result = await self.agent.run(
+                f"请执行以下任务：\n{task_event}",
+                deps=deps
+            )
+            return {"output": result.data.output}
+        except Exception as e:
+            logger.exception(f"SpecialIndividual {self.agent_id} 执行失败: {e}")
+            raise

pretor/worker_individual/worker_cluster.py

@@ -18,8 +18,10 @@ import asyncio
 from collections import OrderedDict
 from ray.util.queue import Queue
 from pretor.utils.ray_hook import ray_actor_hook
-from pretor.worker_individual.worker_individual import BaseIndividual, SkillIndividual, OrdinaryIndividual, \
+from pretor.worker_individual.base_individual import BaseIndividual
-    SpecialIndividual
+from pretor.worker_individual.skill_individual import SkillIndividual
+from pretor.worker_individual.ordinary_individual import OrdinaryIndividual
+from pretor.worker_individual.special_individual import SpecialIndividual
 
 
 from pretor.utils.logger import get_logger

pretor/worker_individual/worker_individual.py

@@ -1,157 +0,0 @@
-#  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_ai import Agent, RunContext
-from pydantic import Field
-from pretor.adapter.model_adapter.agent_factory import AgentFactory
-from pretor.core.global_state_machine.model_provider.base_provider import Provider
-from pretor.utils.agent_model import ResponseModel, InputModel, DepsModel
-from pretor.utils.ray_hook import ray_actor_hook
-
-
-from pretor.utils.logger import get_logger
-logger = get_logger('worker_individual')
-
-class WorkerIndividualResponse(ResponseModel):
-    output: str = Field(..., description="Worker执行任务的输出结果")
-
-
-class WorkerIndividualDeps(DepsModel):
-    task_event: dict
-
-
-class WorkerIndividualInput(InputModel):
-    task_event: dict
-
-
-class BaseIndividual:
-    """
-    Worker Individual 的基类
-    """
-
-    def __init__(self, agent_config: dict):
-        self.agent_config = agent_config
-        self.agent_id = agent_config.get("agent_id")
-        self.agent: Agent | None = None
-
-    async def _init_agent(self, agent_name: str, system_prompt: str):
-        global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
-        provider_title = self.agent_config.get("provider_title", "openai")  # default fallback
-        model_id = self.agent_config.get("model_id", "gpt-4o")  # default fallback
-
-        provider: Provider = await global_state_machine.get_provider.remote( provider_title)
-        agent_factory = AgentFactory()
-        self.agent = agent_factory.create_agent(
-            provider=provider,
-            model_id=model_id,
-            output_type=WorkerIndividualResponse,
-            system_prompt=system_prompt,
-            deps_type=WorkerIndividualDeps,
-            agent_name=agent_name
-        )
-
-        @self.agent.system_prompt
-        async def dynamic_prompt(ctx: RunContext[WorkerIndividualDeps]):
-            prompt = system_prompt + "\n\n"
-            prompt += (
-                f"=== 当前任务上下文 ===\n"
-                f"{ctx.deps.task_event}\n"
-            )
-            return prompt
-
-    async def run(self, task_event: dict) -> dict:
-        raise NotImplementedError("子类必须实现 run 方法")
-
-
-class SkillIndividual(BaseIndividual):
-    """
-    专家子个体：拥有专业 skill 的 agent。
-    """
-
-    def __init__(self, agent_config: dict):
-        super().__init__(agent_config)
-
-    async def run(self, task_event: dict) -> dict:
-        if self.agent is None:
-            system_prompt = self.agent_config.get("prompt",
-                                                  "你是一个拥有专业技能的专家级AI助手，请利用你的专业知识完成给定的任务。")
-            await self._init_agent("skill_individual", system_prompt)
-
-        deps = WorkerIndividualDeps(task_event=task_event)
-        self.agent.retries = 3
-        # In actual usage, tools could be dynamically loaded here based on agent_config
-        # tool = get_tool("skill_individual")
-        try:
-            result = await self.agent.run(
-                f"请执行以下任务：\n{task_event}",
-                deps=deps
-                # tools=tool
-            )
-            return {"output": result.data.output}
-        except Exception as e:
-            logger.exception(f"SkillIndividual {self.agent_id} 执行失败: {e}")
-            raise
-
-
-class OrdinaryIndividual(BaseIndividual):
-    """
-    普通子个体：普通的 agent。
-    """
-
-    def __init__(self, agent_config: dict):
-        super().__init__(agent_config)
-
-    async def run(self, task_event: dict) -> dict:
-        if self.agent is None:
-            system_prompt = self.agent_config.get("prompt", "你是一个普通的AI助手，请尽力完成给定的任务。")
-            await self._init_agent("ordinary_individual", system_prompt)
-
-        deps = WorkerIndividualDeps(task_event=task_event)
-        self.agent.retries = 3
-        try:
-            result = await self.agent.run(
-                f"请执行以下任务：\n{task_event}",
-                deps=deps
-            )
-            return {"output": result.data.output}
-        except Exception as e:
-            logger.exception(f"OrdinaryIndividual {self.agent_id} 执行失败: {e}")
-            raise
-
-
-class SpecialIndividual(BaseIndividual):
-    """
-    特殊子个体：执行特殊任务的 agent，如生成语音、视频等。
-    """
-
-    def __init__(self, agent_config: dict):
-        super().__init__(agent_config)
-
-    async def run(self, task_event: dict) -> dict:
-        if self.agent is None:
-            system_prompt = self.agent_config.get("prompt", "你是一个特殊的AI助手，负责处理特殊类型的任务。")
-            await self._init_agent("special_individual", system_prompt)
-
-        deps = WorkerIndividualDeps(task_event=task_event)
-        self.agent.retries = 3
-        try:
-            result = await self.agent.run(
-                f"请执行以下任务：\n{task_event}",
-                deps=deps
-            )
-            return {"output": result.data.output}
-        except Exception as e:
-            logger.exception(f"SpecialIndividual {self.agent_id} 执行失败: {e}")
-            raise

pyproject.toml

@@ -16,6 +16,7 @@ dependencies = [
     "pwdlib[argon2,bcrypt]>=0.3.0",
     "pydantic-ai>=1.73.0",
     "pyfiglet>=1.0.4",
+    "pyjwt>=2.12.1",
     "python-ulid>=3.1.0",
     "ray[default,serve]>=2.54.0",
     "rich>=14.3.3",

tests/core/global_state_machine/global_state_machine_test.py

@@ -50,23 +50,23 @@ def gsm(mock_postgres):
 
 def test_add_delete_get_event(gsm):
     event = MagicMock(spec=PretorEvent)
-    event.event_id = 123
+    event.trace_id = "123"
 
     gsm.add_event(event)
 
     assert getattr(event, 'pending_queue', None) is not None
     assert getattr(event, 'receive_queue', None) is not None
 
-    retrieved = gsm.get_event(123)
+    retrieved = gsm.get_event("123")
     assert retrieved == event
 
-    gsm.delete_event(123)
+    gsm.delete_event("123")
-    assert gsm.get_event(123) is None
+    assert gsm.get_event("123") is None
 
 
 def test_update_attachment_and_workflow(gsm):
     event = MagicMock(spec=PretorEvent)
-    event.event_id = "abc"
+    event.trace_id = "abc"
     gsm.add_event(event)
 
     gsm.update_attachment("abc", {"k": "v"})
@@ -80,7 +80,7 @@ def test_update_attachment_and_workflow(gsm):
 @pytest.mark.asyncio
 async def test_queues(gsm):
     event = MagicMock(spec=PretorEvent)
-    event.event_id = "q_event"
+    event.trace_id = "q_event"
     # To use await put/get, we must actually use real asyncio queues for the mock event
     event.pending_queue = asyncio.Queue()
     event.receive_queue = asyncio.Queue()

tests/core/workflow/workflow_test.py

@@ -10,41 +10,43 @@ def test_worker_group():
 def test_work_step():
     ws = WorkStep(
         step=1,
+        name="step1",
         node="control_node",
         action="coding",
         desc="Write some code"
     )
     assert ws.step == 1
+    assert ws.name == "step1"
     assert ws.node == "control_node"
     assert ws.action == "coding"
     assert ws.desc == "Write some code"
     assert ws.status == "waiting"
 
 def test_pretor_workflow_validation_success():
-    ws1 = WorkStep(step=1, node="control_node", action="a1", desc="d1")
+    ws1 = WorkStep(step=1, name="s1", node="control_node", action="a1", desc="d1")
-    ws2 = WorkStep(step=2, node="supervisory_node", action="a2", desc="d2")
+    ws2 = WorkStep(step=2, name="s2", node="supervisory_node", action="a2", desc="d2")
     wg = WorkerGroup(name="g1", primary_individual={"coder": 1}, composite_individual={})
     wf = PretorWorkflow(title="wf1", workgroup_list=[wg], work_link=[ws1, ws2], trace_id="t", event_info={"platform":"a", "user_name":"b"})
     assert wf.title == "wf1"
 
 def test_pretor_workflow_validation_error_step_discontinuous():
-    ws1 = WorkStep(step=1, node="control_node", action="a1", desc="d1")
+    ws1 = WorkStep(step=1, name="s1", node="control_node", action="a1", desc="d1")
-    ws2 = WorkStep(step=3, node="supervisory_node", action="a2", desc="d2")
+    ws2 = WorkStep(step=3, name="s3", node="supervisory_node", action="a2", desc="d2")
     wg = WorkerGroup(name="g1", primary_individual={}, composite_individual={})
     with pytest.raises(ValueError, match="工作链步数不连续"):
         PretorWorkflow(title="wf1", workgroup_list=[wg], work_link=[ws1, ws2], trace_id="t", event_info={"platform":"a", "user_name":"b"})
 
 def test_pretor_workflow_validation_error_jump_out_of_bounds():
     lg = LogicGate(if_fail="jump_to_step_3", if_pass="continue")
-    ws1 = WorkStep(step=1, node="control_node", action="a1", desc="d1", logic_gate=lg)
+    ws1 = WorkStep(step=1, name="s1", node="control_node", action="a1", desc="d1", logic_gate=lg)
-    ws2 = WorkStep(step=2, node="supervisory_node", action="a2", desc="d2")
+    ws2 = WorkStep(step=2, name="s2", node="supervisory_node", action="a2", desc="d2")
     wg = WorkerGroup(name="g1", primary_individual={}, composite_individual={})
     with pytest.raises(ValueError, match="跳转目标 Step 3 越界了"):
         PretorWorkflow(title="wf1", workgroup_list=[wg], work_link=[ws1, ws2], trace_id="t", event_info={"platform":"a", "user_name":"b"})
 
 def test_pretor_workflow_validation_error_jump_format_error():
     lg = LogicGate(if_fail="jump_to_step_invalid", if_pass="continue")
-    ws1 = WorkStep(step=1, node="control_node", action="a1", desc="d1", logic_gate=lg)
+    ws1 = WorkStep(step=1, name="s1", node="control_node", action="a1", desc="d1", logic_gate=lg)
     wg = WorkerGroup(name="g1", primary_individual={}, composite_individual={})
     with pytest.raises(ValueError, match="LogicGate 格式错误"):
         PretorWorkflow(title="wf1", workgroup_list=[wg], work_link=[ws1], trace_id="t", event_info={"platform":"a", "user_name":"b"})
@@ -53,4 +55,3 @@ def test_workflow_status():
     status = WorkflowStatus()
     assert status.step == 1
     assert status.status == "waiting_llm_working"
-    assert status.demand is None

uv.lock

@@ -3074,6 +3074,7 @@ dependencies = [
     { name = "pydantic-ai", version = "1.75.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.14'" },
     { name = "pydantic-ai", version = "1.84.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.14'" },
     { name = "pyfiglet" },
+    { name = "pyjwt" },
     { name = "python-ulid" },
     { name = "ray", extra = ["default", "serve"] },
     { name = "rich" },
@@ -3105,6 +3106,7 @@ requires-dist = [
     { name = "pwdlib", extras = ["argon2", "bcrypt"], specifier = ">=0.3.0" },
     { name = "pydantic-ai", specifier = ">=1.73.0" },
     { name = "pyfiglet", specifier = ">=1.0.4" },
+    { name = "pyjwt", specifier = ">=2.12.1" },
     { name = "python-ulid", specifier = ">=3.1.0" },
     { name = "ray", extras = ["default", "serve"], specifier = ">=2.54.0" },
     { name = "rich", specifier = ">=14.3.3" },