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/workflow.py

@@ -0,0 +1,99 @@
+#  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.utils.ray_hook import ray_actor_hook
+from fastapi import APIRouter, Request, HTTPException
+from fastapi.responses import StreamingResponse
+import asyncio
+
+workflow_router = APIRouter(prefix="/api/v1/workflow", tags=["workflow"])
+
+@workflow_router.get("/list")
+async def get_workflow_list():
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    events = await global_state_machine.list_events.remote()
+    return events
+
+
+@workflow_router.get("/{trace_id}")
+async def get_workflow_detail(trace_id: str):
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    event = await global_state_machine.get_event.remote(trace_id)
+    if not event:
+        raise HTTPException(status_code=404, detail="Workflow not found")
+
+    workflow = event.workflow
+    if not workflow:
+        return {
+            "event_id": trace_id,
+            "workflow_title": None,
+            "status": "waiting",
+            "user_name": event.user_name,
+            "message": event.message,
+            "create_time": event.create_time,
+            "steps": [],
+        }
+
+    steps = []
+    for step in workflow.work_link:
+        steps.append({
+            "step": step.step,
+            "name": step.name,
+            "node": step.node,
+            "action": step.action,
+            "desc": step.desc,
+            "status": step.status,
+            "agent_id": step.agent_id,
+        })
+    return {
+        "event_id": trace_id,
+        "workflow_title": workflow.title,
+        "status": workflow.status.status,
+        "command": workflow.command,
+        "current_step": workflow.status.step,
+        "user_name": event.user_name,
+        "message": event.message,
+        "create_time": event.create_time,
+        "steps": steps,
+    }
+
+@workflow_router.get("/sse/{trace_id}")
+async def get_workflow_sse(trace_id: str, request: Request):
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+
+    async def event_generator():
+        try:
+            while True:
+                if await request.is_disconnected():
+                    break
+
+                # You might also want to send the workflow state periodically or when updated
+                # Here we just wait for pending messages and send them
+                message = await global_state_machine.get_pending.remote(trace_id)
+                # Ensure the message is formatted as SSE
+                yield f"data: {message}\n\n"
+        except asyncio.CancelledError:
+            pass
+
+    return StreamingResponse(event_generator(), media_type="text/event-stream")
+
+@workflow_router.post("/reply/{trace_id}")
+async def post_workflow_reply(trace_id: str, request: Request):
+    data = await request.json()
+    reply_msg = data.get("message", "")
+    global_state_machine = ray_actor_hook("global_state_machine").global_state_machine
+    await global_state_machine.put_received.remote(trace_id, reply_msg)
+    return {"status": "ok"}
+