refactor: use a single agent model path

agent_platform/runtime/__init__.py

@@ -1 +1 @@
-"""Model gateway and independently evolvable Work Agent runtime."""
+"""Model gateway and independently evolvable K1412 Agent runtime."""

agent_platform/runtime/app.py

@@ -10,7 +10,7 @@ from typing import Annotated, Any
 
 import httpx
 import uvicorn
-from fastapi import FastAPI, Header, HTTPException, status
+from fastapi import FastAPI, Header, HTTPException
 from fastapi.responses import JSONResponse, StreamingResponse
 
 from agent_platform.auth import UserIdentity, decode_openwebui_identity, verify_service_bearer
@@ -198,16 +198,6 @@ def create_app(
             return await forward_direct()
 
         stable_chat_id = (chat_id or message_id or f"ephemeral-{uuid.uuid4().hex}").strip()
-        selected_mode = await app.state.store.select_mode(identity.user_id, chat_id or "", spec.mode)
-        if selected_mode == "work" and spec.mode == "chat":
-            raise HTTPException(
-                status_code=status.HTTP_409_CONFLICT,
-                detail="This conversation has been upgraded to Work and cannot return to Chat.",
-            )
-
-        if spec.mode == "chat":
-            return await forward_direct()
-
         messages = [message.model_dump(exclude_none=True) for message in body.messages]
         if not body.stream:
 
@@ -224,7 +214,7 @@ def create_app(
             )
             return _completion(body.model, answer)
 
-        async def work_stream() -> AsyncIterator[bytes]:
+        async def agent_stream() -> AsyncIterator[bytes]:
             queue: asyncio.Queue[tuple[str, Any]] = asyncio.Queue()
 
             async def publish(event_type: str, payload: dict[str, Any]) -> None:
@@ -255,7 +245,7 @@ def create_app(
                     if kind == "done":
                         break
                     if kind == "error":
-                        yield _sse_chunk(body.model, f"\n\nWork 运行失败：{value}")
+                        yield _sse_chunk(body.model, f"\n\nAgent 运行失败：{value}")
                         continue
                     if kind == "answer":
                         text = str(value)
@@ -271,7 +261,7 @@ def create_app(
                 await asyncio.gather(task, return_exceptions=True)
 
         return StreamingResponse(
-            work_stream(),
+            agent_stream(),
             media_type="text/event-stream",
             headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
         )

agent_platform/runtime/loop.py

@@ -28,7 +28,7 @@ from agent_platform.store import RuntimeStore
 EventCallback = Callable[[str, dict[str, Any]], Awaitable[None]]
 
 WORK_SYSTEM_PROMPT = """\
-You are Work, an autonomous coding Agent operating in one isolated user workspace at /workspace.
+You are K1412 Agent, an autonomous coding Agent operating in one isolated user workspace at /workspace.
 
 Own the outcome: inspect the workspace, form a plan for non-trivial work, make scoped changes, run
 relevant verification, and report concrete results. Use tools instead of inventing file contents or
@@ -514,8 +514,8 @@ class AgentLoop:
         await recorder.emit(
             "run.created",
             {
-                "model_tier": spec.strength,
-                "strategy_version": "work-loop-v2",
+                "model_id": spec.public_id,
+                "strategy_version": "agent-loop-v3",
                 "scheduler_version": "safe-parallel-v1",
                 "context_policy": "recent-visible-v1",
             },

agent_platform/runtime/tools.py

@@ -200,14 +200,14 @@ TOOL_METADATA: dict[str, ToolMetadata] = {
     ),
     "remember": ToolMetadata(
         "remember",
-        "Store a durable user preference or fact that will help future Work tasks.",
+        "Store a durable user preference or fact that will help future Agent tasks.",
         object_schema({"content": {"type": "string"}}, ["content"]),
         False,
         False,
     ),
     "recall_memory": ToolMetadata(
         "recall_memory",
-        "Search durable Work memory for this user.",
+        "Search durable Agent memory for this user.",
         object_schema(
             {
                 "query": {"type": "string", "default": ""},
@@ -219,7 +219,7 @@ TOOL_METADATA: dict[str, ToolMetadata] = {
     ),
     "forget_memory": ToolMetadata(
         "forget_memory",
-        "Delete one durable Work memory by id.",
+        "Delete one durable Agent memory by id.",
         object_schema({"memory_id": {"type": "string"}}, ["memory_id"]),
         False,
         False,