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refactor: use a single agent model path

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This commit is contained in:
wuyang
2026-07-26 18:50:51 +08:00
parent 2e8e81c790
commit d95d06233f
23 changed files with 330 additions and 454 deletions
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agent_platform/bootstrap.py
+26 -9
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@@ -9,6 +9,10 @@ import httpx
from agent_platform.models import MODEL_SPECS
LEGACY_MODEL_IDS = {
f"{mode}-{strength}" for mode in ("chat", "work") for strength in ("light", "medium", "high", "extreme")
}
def _required(name: str) -> str:
value = os.getenv(name, "").strip()
@@ -33,27 +37,24 @@ def _model_payload() -> list[dict[str, Any]]:
public_read = [{"principal_type": "user", "principal_id": "*", "permission": "read"}]
items = []
for spec in MODEL_SPECS.values():
is_chat = spec.mode == "chat"
items.append(
{
"id": spec.public_id,
"base_model_id": None,
"name": spec.display_name,
"params": {"function_calling": "native"} if is_chat else {},
"params": {},
"meta": {
"description": (
"快速问答，使用原生工具循环。" if is_chat else "长链路工作，使用 K1412 Work Agent。"
),
"toolIds": ["server:workspace"] if is_chat else [],
"description": (f"K1412 Agent；思考：{spec.thinking_label}。"),
"toolIds": [],
"capabilities": {
"tool_calling": is_chat,
"tool_calling": False,
"builtin_tools": False,
"file_context": False,
"citations": False,
"vision": False,
"file_upload": False,
},
"tags": [{"name": "Chat" if is_chat else "Work"}],
"tags": [{"name": "Agent"}],
},
"access_grants": public_read,
"is_active": True,
@@ -151,6 +152,22 @@ async def bootstrap() -> None:
)
tool_server_response.raise_for_status()
for model_id in sorted(LEGACY_MODEL_IDS):
existing = await client.get(
f"{base_url}/api/v1/models/model",
headers=headers,
params={"id": model_id},
)
if existing.status_code == 404:
continue
existing.raise_for_status()
delete_response = await client.post(
f"{base_url}/api/v1/models/model/delete",
headers=headers,
json={"id": model_id},
)
delete_response.raise_for_status()
model_response = await client.post(
f"{base_url}/api/v1/models/import",
headers=headers,
@@ -158,7 +175,7 @@ async def bootstrap() -> None:
)
model_response.raise_for_status()
print("Open WebUI bootstrap complete: auth policy, workspace tools, and eight fixed Agent entries are ready.")
print("Open WebUI bootstrap complete: auth policy, workspace tools, and four Agent models are ready.")
def run() -> None:
agent_platform/models.py
+59 -35
View File
@@ -3,8 +3,6 @@ from __future__ import annotations
from dataclasses import dataclass
from typing import Literal
Mode = Literal["chat", "work"]
Strength = Literal["light", "medium", "high", "extreme"]
Provider = Literal["k1412", "deepseek"]
@@ -12,49 +10,70 @@ Provider = Literal["k1412", "deepseek"]
class ModelSpec:
public_id: str
display_name: str
mode: Mode
strength: Strength
provider: Provider
provider_model: str
thinking_enabled: bool
thinking_label: str
thinking_adjustable: bool
reasoning_effort: str | None
max_output_tokens: int
max_iterations: int
context_char_budget: int
_TIERS = {
"light": ("轻度", "k1412", "ChatGPT-5.6:Luna", False, None, 4_096, 8, 120_000),
"medium": ("中", "k1412", "ChatGPT-5.6:Terra", False, None, 4_096, 16, 240_000),
"high": ("高", "k1412", "ChatGPT-5.6:Sol", False, None, 4_096, 24, 400_000),
"extreme": ("极高", "deepseek", "deepseek-v4-pro", True, "max", 16_384, 32, 800_000),
}
MODEL_SPECS: dict[str, ModelSpec] = {
f"{mode}-{strength}": ModelSpec(
public_id=f"{mode}-{strength}",
display_name=f"{'Chat' if mode == 'chat' else 'Work'} · {label}",
mode=mode,
strength=strength,
provider=provider,
provider_model=provider_model,
thinking_enabled=thinking_enabled,
reasoning_effort=reasoning_effort,
max_output_tokens=max_output_tokens,
max_iterations=max_iterations,
context_char_budget=context_budget,
)
for mode in ("chat", "work")
for strength, (
label,
provider,
provider_model,
thinking_enabled,
reasoning_effort,
max_output_tokens,
max_iterations,
context_budget,
) in _TIERS.items()
"luna": ModelSpec(
public_id="luna",
display_name="Luna",
provider="k1412",
provider_model="ChatGPT-5.6:Luna",
thinking_enabled=True,
thinking_label="开启（不分档）",
thinking_adjustable=False,
reasoning_effort=None,
max_output_tokens=4_096,
max_iterations=8,
context_char_budget=120_000,
),
"terra": ModelSpec(
public_id="terra",
display_name="Terra",
provider="k1412",
provider_model="ChatGPT-5.6:Terra",
thinking_enabled=True,
thinking_label="开启（不分档）",
thinking_adjustable=False,
reasoning_effort=None,
max_output_tokens=4_096,
max_iterations=16,
context_char_budget=240_000,
),
"sol": ModelSpec(
public_id="sol",
display_name="Sol",
provider="k1412",
provider_model="ChatGPT-5.6:Sol",
thinking_enabled=True,
thinking_label="开启（不分档）",
thinking_adjustable=False,
reasoning_effort=None,
max_output_tokens=4_096,
max_iterations=24,
context_char_budget=400_000,
),
"deepseek-v4-pro": ModelSpec(
public_id="deepseek-v4-pro",
display_name="DeepSeek V4 Pro",
provider="deepseek",
provider_model="deepseek-v4-pro",
thinking_enabled=True,
thinking_label="极高",
thinking_adjustable=False,
reasoning_effort="max",
max_output_tokens=16_384,
max_iterations=32,
context_char_budget=800_000,
),
}
@@ -74,6 +93,11 @@ def openai_model_list() -> dict:
"object": "model",
"owned_by": "k1412-agent",
"name": spec.display_name,
"k1412": {
"thinking_enabled": spec.thinking_enabled,
"thinking_label": spec.thinking_label,
"thinking_adjustable": spec.thinking_adjustable,
},
}
for spec in MODEL_SPECS.values()
],
agent_platform/runtime/__init__.py
+1 -1
View File
@@ -1 +1 @@
"""Model gateway and independently evolvable Work Agent runtime."""
"""Model gateway and independently evolvable K1412 Agent runtime."""
agent_platform/runtime/app.py
+4 -14
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@@ -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
+3 -3
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@@ -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
+3 -3
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@@ -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,
agent_platform/store.py
-45
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@@ -1,6 +1,5 @@
from __future__ import annotations
import asyncio
import uuid
from collections.abc import AsyncIterator
from contextlib import asynccontextmanager
@@ -16,17 +15,6 @@ class Base(DeclarativeBase):
pass
class ConversationMode(Base):
__tablename__ = "agent_conversation_modes"
__table_args__ = (UniqueConstraint("user_id", "chat_id"),)
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
user_id: Mapped[str] = mapped_column(String(128), index=True)
chat_id: Mapped[str] = mapped_column(String(256), index=True)
mode: Mapped[str] = mapped_column(String(16))
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC))
class RunEvent(Base):
__tablename__ = "agent_run_events"
@@ -64,8 +52,6 @@ class RuntimeStore:
def __init__(self, url: str) -> None:
self.engine: AsyncEngine = create_async_engine(url, pool_pre_ping=True)
self.sessions = async_sessionmaker(self.engine, expire_on_commit=False)
self._mode_locks: dict[tuple[str, str], asyncio.Lock] = {}
self._lock_guard = asyncio.Lock()
async def initialize(self) -> None:
async with self.engine.begin() as connection:
@@ -79,37 +65,6 @@ class RuntimeStore:
async with self.sessions() as session:
yield session
async def _mode_lock(self, user_id: str, chat_id: str) -> asyncio.Lock:
key = (user_id, chat_id)
async with self._lock_guard:
return self._mode_locks.setdefault(key, asyncio.Lock())
async def select_mode(self, user_id: str, chat_id: str, requested: str) -> str:
if requested not in {"chat", "work"}:
raise ValueError("Invalid conversation mode")
if not chat_id:
return requested
lock = await self._mode_lock(user_id, chat_id)
async with lock:
async with self.session() as session:
row = await session.scalar(
select(ConversationMode).where(
ConversationMode.user_id == user_id,
ConversationMode.chat_id == chat_id,
)
)
if row is None:
session.add(ConversationMode(user_id=user_id, chat_id=chat_id, mode=requested))
await session.commit()
return requested
if row.mode == "work" and requested == "chat":
return "work"
if row.mode != requested:
row.mode = requested
row.updated_at = datetime.now(UTC)
await session.commit()
return row.mode
async def append_event(
self,
run_id: str,