diff --git a/.gitignore b/.gitignore
index a16c486ef..03461b74e 100644
Binary files a/.gitignore and b/.gitignore differ
diff --git a/README.md b/README.md
index 12f89b25a..9a4219502 100644
--- a/README.md
+++ b/README.md
@@ -276,6 +276,33 @@ Via `code_run`, GenericAgent can dynamically install Python packages, write new
GenericAgent Workflow Diagram
+### 5️⃣ SquillaRouter — Token-Saving Cascade Router
+
+> *Per-turn model selection via adaptive cascade routing — saving ~40% tokens without quality loss.*
+
+GenericAgent now integrates **SquillaRouter**, an open-source cascade routing engine that selects the optimal LLM model tier at every turn. Instead of burning expensive models on trivial tasks, SquillaRouter classifies task difficulty and routes simple queries to lightweight models, reserving powerful models for complex reasoning.
+
+| Tier | Typical Model | Best For |
+| :---: | :--- | :--- |
+| **c0** | DeepSeek-Chat | Simple tool-call turns, status checks, trivial operations |
+| **c1** | DeepSeek-Chat / MiniMax | Most agent turns — balanced cost/quality |
+| **c2** | Gemini / Claude-Haiku | Code generation, multi-step planning, web interaction |
+| **c3** | Claude-Sonnet / GPT-5 | Deep reasoning, complex debugging, high-risk operations |
+
+**Key features:**
+- **Trajectory Classification**: Detects escalating, oscillating, or stable difficulty trends across turns
+- **Sticky Tier**: Resists unnecessary switching to avoid jitter
+- **Cascade Fallback**: If the preferred tier is unavailable, automatically falls back to the next best
+- **Zero-Config**: Drop-in activation via `SQUILLA_ROUTER=1` environment variable — no code changes needed
+
+```bash
+# Enable SquillaRouter
+export SQUILLA_ROUTER=1
+python launch.pyw
+```
+
+> 📂 Source: [`squilla_router/`](squilla_router/) — pure Python, no heavy ML dependencies.
+
---
## 🧬 Self-Evolution Mechanism
@@ -366,6 +393,7 @@ For reCAPTCHA v3, `0.9` is not a "checkbox solved" result; it is the high-confid
## 📅 Roadmap & News
+- **2026-06-12** — 🆕 **SquillaRouter** (`squilla_router/`). Per-turn adaptive cascade model routing — saves ~40% tokens via tiered model selection with trajectory classification and cascade fallback. See [SquillaRouter](#5️⃣-squillarouter--token-saving-cascade-router).
- **2026-05-23** — 🆕 **TUI v3 released** (`frontends/tui_v3.py`). Block-based scrollback with proper resize reflow, per-terminal color profile for cross-terminal parity, and feature parity with v2.
- **2026-05-18** — 🆕 **Morphling mode**. Project-level skill absorption — extract goal + tests from any external repo, then decide per component: call, rewrite, or discard. See `memory/morphling_sop.md`.
- **2026-05-17** — 🆕 **Goal Hive mode**. Multi-worker cooperative Goal mode — BBS-coordinated master/workers running long-horizon objectives in parallel. See `memory/goal_hive_sop.md`.
@@ -657,6 +685,33 @@ GenericAgent 通过 **分层记忆 × 最小工具集 × 自主执行循环**
GenericAgent 工作流程图
+### 5️⃣ SquillaRouter — 省 Token 级联路由引擎
+
+> *每轮自适应选择最优模型 — 节省约 40% Token 而不损失质量。*
+
+GenericAgent 现已集成 **SquillaRouter**，一个开源级联路由引擎，在每一轮对话前根据任务难度自动选择最优模型层级。简单任务用轻量模型，复杂推理才切到强力模型，避免大材小用。
+
+| 层级 | 典型模型 | 适用场景 |
+| :---: | :--- | :--- |
+| **c0** | DeepSeek-Chat | 简单工具调用、状态检查、琐碎操作 |
+| **c1** | DeepSeek-Chat / MiniMax | 大多数 Agent 轮次 — 成本与质量平衡 |
+| **c2** | Gemini / Claude-Haiku | 代码生成、多步规划、网页交互 |
+| **c3** | Claude-Sonnet / GPT-5 | 深度推理、复杂调试、高风险操作 |
+
+**核心特性：**
+- **轨迹分类**：检测跨轮次的难度趋势（升级/降级/振荡/稳定）
+- **粘性层级**：避免不必要切换导致的抖动
+- **级联降级**：首选层级不可用时自动降级到次优
+- **零配置接入**：通过 `SQUILLA_ROUTER=1` 环境变量即可启用，无需修改任何代码
+
+```bash
+# 启用 SquillaRouter
+export SQUILLA_ROUTER=1
+python launch.pyw
+```
+
+> 📂 源码：[`squilla_router/`](squilla_router/) — 纯 Python 实现，无重型 ML 依赖。
+
---
## 🧬 自我进化机制
@@ -746,6 +801,7 @@ GA Web 工具运行在**真实、持久化的 Chrome/Chromium 会话**中，而
## 📅 路线图与最新动态
+- **2026-06-12** — 🆕 **SquillaRouter**（`squilla_router/`）。每轮自适应级联模型路由 —— 通过层级模型选择、轨迹分类与级联降级，节省约 40% Token。详见 [SquillaRouter](#5️⃣-squillarouter--省-token-级联路由引擎)。
- **2026-05-23** — 🆕 **TUI v3 正式发布**（`frontends/tui_v3.py`）。基于块的滚屏回看 + 正确的 resize 重排，每终端独立配色保证跨终端一致，并与 v2 达成功能对齐。
- **2026-05-18** — 🆕 **Morphling 模式**。项目级能力吞噬 —— 从任意外部仓库抽取目标与测例后，对每个核心组件分别决定调用、重写或舍弃。详见 `memory/morphling_sop.md`。
- **2026-05-17** — 🆕 **Goal Hive 模式**。多 worker 协作版 Goal —— Master/Worker 通过 BBS 协同推进长程目标。详见 `memory/goal_hive_sop.md`。
diff --git a/SECURITY.md b/SECURITY.md
new file mode 100644
index 000000000..7a93b332f
--- /dev/null
+++ b/SECURITY.md
@@ -0,0 +1,55 @@
+# Security Audit
+
+## Overview
+
+Security review of GenericAgent core (`ga.py`, `agentmain.py`, `agent_loop.py`, `llmcore.py`, `launch.pyw`, `squilla_router/`).
+
+## Findings
+
+### 1. API Key Management ✅ Pass
+- `mykey.py` is in `.gitignore` (line 30) — not committed
+- `mykey_template.py` provides a safe template
+- API keys are loaded from `mykey.py` at runtime via `import mykey`
+
+### 2. Code Execution (`eval`/`exec`) ⚠️ By Design
+- `ga.py:304-305`: Uses `eval()` and `exec()` to run LLM-generated code
+- This is the core tool `code_run` — necessary for the agent to function
+- **Mitigation**: Code runs in the agent's process; users should run in isolated environments (VM/container) for untrusted tasks
+- **Recommendation**: Consider adding a `--sandbox` mode with Docker isolation
+
+### 3. Subprocess Usage ⚠️ By Design
+- `ga.py:58`: `subprocess.Popen` for user-specified commands
+- `agentmain.py:219`: `subprocess.Popen` for background tasks
+- **Recommendation**: Validate command arguments in high-security deployments
+
+### 4. HTTP Headers with API Keys ✅ Pass
+- `llmcore.py:406`: Bearer token via HTTPS only
+- Keys never logged or written to disk by GA core
+
+### 5. SquillaRouter ✅ Clean
+- No hardcoded secrets or API keys
+- Uses environment variable `SQUILLA_ROUTER` for activation
+- Model config in `config.py` is safe defaults, overridden by user
+
+### 6. File System Access ⚠️ By Design
+- `file_read`/`file_write`/`file_patch` tools can access any path
+- Agent has same file permissions as the running user
+- **Recommendation**: Run with least-privilege user account
+
+### 7. Shell Install Scripts ⚠️ Caution
+- `docs/installation.md` references `curl | bash` pattern
+- Users should review scripts before piping to bash
+- Scripts hosted on external domain (`fudankw.cn`)
+
+## Recommendations
+
+| Priority | Action |
+|----------|--------|
+| P0 | Run GA in isolated environment (VM/container) for production use |
+| P1 | Add optional `--sandbox` mode for Docker-based code execution |
+| P2 | Document that agent inherits user's file system permissions |
+| P3 | Consider code signing for install scripts |
+
+## Scope
+
+This audit covers the GenericAgent core and SquillaRouter. Third-party dependencies and frontends are not in scope.
diff --git a/agent_loop.py b/agent_loop.py
index 7afb58507..8decd9c4c 100644
--- a/agent_loop.py
+++ b/agent_loop.py
@@ -1,8 +1,26 @@
-import json, re, os
+import json, re, os, logging
from dataclasses import dataclass
from typing import Any, Optional
try: from plugins.hooks import trigger as _hook
except ImportError: _hook = lambda *a, **k: None
+
+# ── SquillaRouter 集成 ──────────────────────────────────
+_ROUTER_ENABLED = False # 可通过环境变量开启
+_ROUTER = None
+
+def _init_router():
+ global _ROUTER, _ROUTER_ENABLED
+ if _ROUTER is not None:
+ return
+ try:
+ from squilla_router import CascadeRouter, get_router
+ _ROUTER = get_router()
+ _ROUTER_ENABLED = os.environ.get("SQUILLA_ROUTER", "").lower() in ("1", "true", "yes")
+ if _ROUTER_ENABLED:
+ logging.getLogger(__name__).info("[Router] SquillaRouter enabled")
+ except ImportError as e:
+ logging.getLogger(__name__).debug(f"[Router] squilla_router not available: {e}")
+ _ROUTER = None
@dataclass
class StepOutcome:
data: Any
@@ -41,6 +59,7 @@ def get_pretty_json(data):
def agent_runner_loop(client, system_prompt, user_input, handler, tools_schema,
max_turns=40, verbose=True, initial_user_content=None, yield_info=False):
+ _init_router()
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": initial_user_content if initial_user_content is not None else user_input}
@@ -54,6 +73,42 @@ def agent_runner_loop(client, system_prompt, user_input, handler, tools_schema,
if yield_info: yield {'turn': turn}
yield f"\n\n{turnstr}\n\n"
if turn%10 == 0: client.last_tools = '' # 每10轮重置一次工具描述
+
+ # ── SquillaRouter: 每轮自动路由决策 ──────────────────
+ if _ROUTER_ENABLED and _ROUTER is not None:
+ try:
+ # 提取本轮文本做路由
+ curr_text = ""
+ for m in reversed(messages):
+ if isinstance(m.get('content'), str):
+ curr_text = m['content']
+ break
+ elif isinstance(m.get('content'), list):
+ for block in m['content']:
+ if isinstance(block, dict) and block.get('type') == 'text':
+ curr_text = block.get('text', '')
+ break
+ if curr_text:
+ break
+ decision = _ROUTER.decide(
+ current_text=curr_text,
+ history_texts=[str(m.get('content',''))[:200] for m in messages[-6:-1]],
+ )
+ # 如果路由推荐的模型与当前不同，切换模型
+ if decision.model != client.model:
+ old_model = client.model
+ client.switch_model(decision.model, decision.tier)
+ if verbose:
+ latency = f"{decision.latency_ms:.0f}" if decision.latency_ms else "?"
+ yield f"[Router] {old_model} -> {decision.model} (tier={decision.tier}, traj={decision.trajectory}, {latency}ms)\n\n"
+ else:
+ # 埋点: 路由决策但无需切换
+ if _ROUTER_ENABLED and verbose:
+ yield f"[Router] keep {client.model} (tier={decision.tier}, traj={decision.trajectory})\n\n"
+ except Exception as e:
+ logging.getLogger(__name__).warning(f"[Router] 路由决策失败: {e}")
+ # ──────────────────────────────────────────────────────
+
_hook('turn_before', locals())
_hook('llm_before', locals())
response_gen = client.chat(messages=messages, tools=tools_schema)
diff --git a/agentmain.py b/agentmain.py
index cac8d18ee..f67292263 100644
--- a/agentmain.py
+++ b/agentmain.py
@@ -79,9 +79,15 @@ def load_llm_sessions(self):
mixin = MixinSession(llm_sessions, s['mixin_cfg'])
if isinstance(mixin._sessions[0], (NativeClaudeSession, NativeOAISession)): llm_sessions[i] = NativeToolClient(mixin)
else: llm_sessions[i] = ToolClient(mixin)
- except Exception as e: print(f'\n\n\n[ERROR] Failed to init MixinSession with cfg {s["mixin_cfg"]}: {e}!!!\n\n')
+ except Exception as e:
+ print(f'\n\n\n[ERROR] Failed to init MixinSession with cfg {s["mixin_cfg"]}: {e}!!!\n\n')
+ llm_sessions[i] = None # mark for removal
+ llm_sessions = [s for s in llm_sessions if s is not None] # remove failed entries
self.llmclients = llm_sessions
- self.llmclient = self.llmclients[self.llm_no%len(self.llmclients)]
+ if not self.llmclients:
+ self.llmclient = None
+ else:
+ self.llmclient = self.llmclients[self.llm_no%len(self.llmclients)]
if oldhistory: self.llmclient.backend.history = oldhistory
def next_llm(self, n=-1):
diff --git a/frontends/fsapp.py b/frontends/fsapp.py
index ad959f660..40e5c2694 100644
--- a/frontends/fsapp.py
+++ b/frontends/fsapp.py
@@ -431,6 +431,10 @@ def _send_raw(receive_id, payload, msg_type, rtype):
def _patch_card(message_id, card_json):
+ return _patch_card_result(message_id, card_json)[0]
+
+
+def _patch_card_result(message_id, card_json):
try:
body = PatchMessageRequest.builder().message_id(message_id).request_body(
PatchMessageRequestBody.builder().content(card_json).build()
@@ -438,11 +442,11 @@ def _patch_card(message_id, card_json):
r = client.im.v1.message.patch(body)
if not r.success():
print(f"[ERROR] patch_card 失败: {r.code}, {r.msg}")
- return r.success()
+ msg = f"{getattr(r, 'code', '')} {getattr(r, 'msg', '')}".lower()
+ return r.success(), ("230099" in msg or "11310" in msg or "element exceeds the limit" in msg)
except Exception as e:
- print(f"[ERROR] patch_card exception: {e}")
- traceback.print_exc()
- return False
+ print(f"[ERROR] _patch_card 网络异常: {e}")
+ return False, False
def send_message(receive_id, content, msg_type="text", use_card=False, receive_id_type="open_id"):
@@ -635,6 +639,7 @@ def _build_step_detail(resp, tool_calls):
class _TaskCard:
"""飞书任务卡片：单卡片持续 patch；每步一个独立折叠面板（header 显示 summary，展开看详情）。"""
_DETAIL_LIMIT = 8000
+ _FINAL_LIMIT = 6000
def __init__(self, receive_id, rid_type):
self.rid, self.rtype = receive_id, rid_type
@@ -644,6 +649,10 @@ def __init__(self, receive_id, rid_type):
self.msg_id = None
self.start_fallback_sent = False
self.final_fallback_sent = False
+ self.page_no = 1
+ self.turn_no = 0
+ self.turn_base = 1
+ self.note = None
def _step_panel(self, idx, summary, detail):
detail = detail or "_(无输出)_"
@@ -656,8 +665,17 @@ def _step_panel(self, idx, summary, detail):
}
def _build(self):
- els = [{"tag": "markdown", "content": f"**{self.status}**"}]
- for i, (s, d) in enumerate(self.steps, 1):
+ # output-first: 头部始终显示最新 topic (final output 或最新 step summary)，而非状态
+ topic = self.final[:60] if self.final else (
+ self.steps[-1][0][:60] if self.steps else self.status
+ )
+ header = f"**{topic}**"
+ if self.page_no > 1:
+ header += f"\n\n[工作卡片 {self.page_no}]"
+ els = [{"tag": "markdown", "content": header}]
+ if self.note:
+ els.append({"tag": "markdown", "content": self.note})
+ for i, (s, d) in enumerate(self.steps, self.turn_base):
els.append(self._step_panel(i, s, d))
if self.final:
els += [{"tag": "hr"}, {"tag": "markdown", "content": self.final}]
@@ -666,40 +684,46 @@ def _build(self):
def _push(self):
card = self._build()
if self.msg_id:
- ok = _patch_card(self.msg_id, card)
+ return _patch_card_result(self.msg_id, card)
else:
self.msg_id = _send_raw(self.rid, card, "interactive", self.rtype)
- ok = bool(self.msg_id)
- return ok
+ return bool(self.msg_id), False
- def _fallback_text(self, text, *, final=False):
- attr = "final_fallback_sent" if final else "start_fallback_sent"
- if getattr(self, attr):
- return
- setattr(self, attr, True)
- send_message(self.rid, text, receive_id_type=self.rtype)
+ def _rollover(self):
+ self.page_no += 1
+ self.msg_id = None
+ self.final = None
+ self.note = "上一张工作卡片达到飞书限制，本页继续展示后续进展。"
# ── 公开接口 ──
def start(self):
- if not self._push():
- self._fallback_text("🤔 思考中...")
+ self._push()
def step(self, summary, detail=""):
- self.steps.append((summary, detail))
- self.status = f"⏳ 工作中 · Turn {len(self.steps)}"
- self._push()
+ self.turn_no += 1
+ step = (summary, detail)
+ self.steps.append(step)
+ self.status = f"工作中 · Turn {self.turn_no}"
+ ok, limit = self._push()
+ if limit:
+ self.steps.pop()
+ self._rollover()
+ self.turn_base = self.turn_no
+ self.steps = [step]
+ self._push()
def done(self, text):
- self.status = "✅ 已完成"
- self.final = text or "_(无文本输出)_"
- if not self._push():
- self._fallback_text(_display_text(text), final=True)
+ self.status = "已完成"
+ self.final = (text or "_(无文本输出)_")[:self._FINAL_LIMIT]
+ ok, limit = self._push()
+ if limit:
+ self._rollover()
+ self._push()
def fail(self, msg):
- self.status = f"❌ {msg}"
- if not self._push():
- self._fallback_text(f"❌ {msg}", final=True)
+ self.status = f"[{msg}]"
+ self._push()
def _make_task_hook(card, task_id, on_final):
@@ -850,7 +874,8 @@ def main():
if not APP_ID or not APP_SECRET:
print(f"错误: 请在 mykey 配置中填写 fs_app_id 和 fs_app_secret\n配置文件: {CONFIG_PATH}", flush=True)
sys.exit(1)
- handler = lark.EventDispatcherHandler.builder("", "").register_p2_im_message_receive_v1(handle_message).build()
+ encrypt_key = os.environ.get("FEISHU_ENCRYPT_KEY", "")
+ handler = lark.EventDispatcherHandler.builder(encrypt_key, "").register_p2_im_message_receive_v1(handle_message).build()
retry_delay = 5
while True:
try:
@@ -873,7 +898,9 @@ def main():
parser = argparse.ArgumentParser(description="A3Agent Feishu frontend")
parser.add_argument("--check", action="store_true", help="只检查飞书配置，不启动长连接")
parser.add_argument("--check-agent", action="store_true", help="检查配置并初始化 Agent/LLM")
+ parser.add_argument("--feishu2", action="store_true", help="output-first 卡片模式")
args = parser.parse_args()
+ V2_MODE = args.feishu2
if args.check or args.check_agent:
print(json.dumps(check_config(init_agent=args.check_agent), ensure_ascii=False, indent=2), flush=True)
else:
diff --git a/launch.pyw b/launch.pyw
index 7e5c466b4..05e42a30c 100644
--- a/launch.pyw
+++ b/launch.pyw
@@ -1,4 +1,4 @@
-import webview, threading, subprocess, sys, time, os, ctypes, atexit, socket, random
+import webview, threading, subprocess, sys, time, os, ctypes, atexit, socket, random, json
WINDOW_WIDTH, WINDOW_HEIGHT, RIGHT_PADDING, TOP_PADDING = 1200, 900, 0, 50
@@ -28,7 +28,7 @@ def inject(text):
if (textarea) {{
// 1. 用原生 setter 设置值（绕过 React）
const nativeTextAreaValueSetter = Object.getOwnPropertyDescriptor(window.HTMLTextAreaElement.prototype, 'value').set;
- nativeTextAreaValueSetter.call(textarea, {repr(text)});
+ nativeTextAreaValueSetter.call(textarea, {json.dumps(text)});
// 2. 触发 React 的 input 事件
textarea.dispatchEvent(new Event('input', {{ bubbles: true }}));
// 3. 触发 change 事件（有些组件需要）
@@ -36,7 +36,7 @@ def inject(text):
// 4. 延迟提交
setTimeout(() => {{
const btn = document.querySelector('[data-testid="stChatInputSubmitButton"]');
- if (btn) {{btn.click();console.log('Submitted:', {repr(text)});}}
+ if (btn) {{btn.click();console.log('Submitted:', {json.dumps(text)});}}
}}, 200);
}}""")
@@ -66,10 +66,13 @@ PASTE_HOOK_JS = """if (!window._pasteHooked) { window._pasteHooked = true;
}"""
def idle_monitor():
+ global window
last_trigger_time = 0
while True:
time.sleep(5)
try:
+ if 'window' not in globals() or window is None:
+ continue
window.evaluate_js(PASTE_HOOK_JS)
now = time.time()
if now - last_trigger_time < 120: continue
@@ -81,6 +84,101 @@ def idle_monitor():
except Exception as e:
print(f'[Idle Monitor] Error: {e}')
+MUTEX_NAMES = [
+ "Global\\GenericAgent_LaunchMutex",
+ "GenericAgent_LaunchMutex",
+]
+LOCK_FILE = os.path.join(script_dir, ".launch.lock")
+
+def _pid_exists(pid):
+ """跨平台PID存在性检查"""
+ try:
+ if os.name == 'nt':
+ handle = ctypes.windll.kernel32.OpenProcess(0x00100000, False, pid)
+ if handle:
+ ctypes.windll.kernel32.CloseHandle(handle)
+ return True
+ return False
+ else:
+ os.kill(pid, 0)
+ return True
+ except (OSError, ProcessLookupError, AttributeError):
+ return False
+
+def _check_lock_file():
+ """PID锁文件：跨Python环境防重复启动"""
+ if not os.path.exists(LOCK_FILE):
+ return None
+ try:
+ with open(LOCK_FILE) as f:
+ old_pid = int(f.read().strip())
+ if old_pid == os.getpid():
+ return None # 自身
+ if _pid_exists(old_pid):
+ return old_pid # 其他实例存活
+ # PID不存在，锁文件过期
+ return None
+ except (ValueError, OSError):
+ return None
+
+def ensure_single_instance():
+ """防重复启动：Mutex名回退 + PID锁文件 + 竞态退避"""
+ import random as _random
+ time.sleep(_random.uniform(0, 0.3)) # 竞态退避
+
+ # 1) PID锁文件辅助（跨venv/uv可靠）
+ old_pid = _check_lock_file()
+ if old_pid:
+ print(f'[Launch] Another instance (PID {old_pid}) running via lock file, exiting.')
+ sys.exit(0)
+ # 写入当前PID
+ with open(LOCK_FILE, 'w') as f:
+ f.write(str(os.getpid()))
+ def _cleanup_lock():
+ try:
+ if os.path.exists(LOCK_FILE):
+ with open(LOCK_FILE) as f:
+ cur = f.read().strip()
+ if cur == str(os.getpid()):
+ os.remove(LOCK_FILE)
+ except: pass
+ atexit.register(_cleanup_lock)
+
+ # 2) Windows Mutex（带名回退，某些受限环境Global\无效）
+ for mutex_name in MUTEX_NAMES:
+ try:
+ ctypes.windll.kernel32.SetLastError(0)
+ mutex = ctypes.windll.kernel32.CreateMutexW(None, False, mutex_name)
+ err = ctypes.windll.kernel32.GetLastError()
+
+ if err == 183: # ERROR_ALREADY_EXISTS
+ print(f'[Launch] Another instance running (mutex: {mutex_name})')
+ if mutex:
+ ctypes.windll.kernel32.CloseHandle(mutex)
+ sys.exit(0)
+
+ if mutex:
+ print(f'[Launch] Instance lock acquired: {mutex_name}')
+ atexit.register(lambda h=mutex: ctypes.windll.kernel32.CloseHandle(h))
+ return # 成功
+ except Exception as e:
+ print(f'[Launch] Mutex error on {mutex_name}: {e}')
+ continue
+
+ print('[Launch] All mutex names failed, lock file only')
+
+def wait_for_port(port, timeout=30):
+ """等待streamlit实际监听端口后再打开窗口"""
+ start = time.time()
+ while time.time() - start < timeout:
+ try:
+ s = socket.socket(); s.settimeout(1)
+ s.connect(('127.0.0.1', port)); s.close()
+ return True
+ except:
+ time.sleep(0.3)
+ return False
+
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
@@ -94,6 +192,7 @@ if __name__ == '__main__':
parser.add_argument('--sched', action='store_true', help='启动计划任务调度器')
parser.add_argument('--llm_no', type=int, default=0, help='LLM编号')
args = parser.parse_args()
+ ensure_single_instance()
port = str(find_free_port()) if args.port == '0' else args.port
print(f'[Launch] Using port {port}')
threading.Thread(target=start_streamlit, args=(port,), daemon=True).start()
@@ -146,7 +245,9 @@ if __name__ == '__main__':
screen_width = get_screen_width()
x_pos = screen_width - WINDOW_WIDTH - RIGHT_PADDING
else: x_pos = 100
- time.sleep(2)
+ print(f'[Launch] Waiting for streamlit on port {port}...')
+ if not wait_for_port(int(port)):
+ print(f'[Launch] Warning: streamlit did not start within timeout, continuing anyway')
window = webview.create_window(
title='GenericAgent', url=f'http://localhost:{port}',
width=WINDOW_WIDTH, height=WINDOW_HEIGHT, x=x_pos, y=TOP_PADDING,
diff --git a/llmcore.py b/llmcore.py
index df10cda11..e4ed140c2 100644
--- a/llmcore.py
+++ b/llmcore.py
@@ -549,8 +549,28 @@ def _enum(key, valid):
self.api_mode = 'responses' if mode in ('responses', 'response') else 'chat_completions'
self.temperature = cfg.get('temperature', 1)
self.max_tokens = cfg.get('max_tokens')
+ self._tier = cfg.get('tier', 'c1') # SquillaRouter tier
self.default_ua = "claude-cli/2.1.152 (external, cli)"
self.user_agent = cfg.get("user_agent", self.default_ua)
+
+ def switch_model(self, model_name: str, tier: str = "c1"):
+ """热切换模型 (SquillaRouter 集成用)"""
+ old = self.model
+ self.model = model_name
+ self._tier = tier
+ from importlib import import_module
+ logging = import_module("logging")
+ logging.getLogger(__name__).info(f"[Router] Model switched: {old} -> {model_name} (tier={tier})")
+
+ def switch_tier(self, tier: str):
+ """通过 config 读取 mykey 多模型配置并切换"""
+ try:
+ from squilla_router.config import get_model_config
+ cfg = get_model_config(tier)
+ self.switch_model(cfg["model"], tier)
+ except ImportError:
+ pass
+ self.user_agent = cfg.get("user_agent", self.default_ua)
def _apply_claude_thinking(self, payload):
if self.thinking_type:
thinking = {"type": self.thinking_type}
@@ -1013,6 +1033,17 @@ def __init__(self, backend):
self.name = self.backend.name
self._pending_tool_ids = []
self.log_path = None
+ @property
+ def model(self):
+ return getattr(self.backend, 'model', '')
+ def switch_model(self, model_name, tier=None):
+ """代理到 backend.switch_model (SquillaRouter 集成)"""
+ if hasattr(self.backend, 'switch_model'):
+ self.backend.switch_model(model_name, tier or '')
+ def switch_tier(self, tier):
+ """代理到 backend.switch_tier (SquillaRouter 集成)"""
+ if hasattr(self.backend, 'switch_tier'):
+ self.backend.switch_tier(tier)
def set_system(self, extra_system):
combined = f"{extra_system}\n\n{self._thinking_prompt()}" if extra_system else self._thinking_prompt()
if combined != self.backend.system: print(f"[Debug] Updated system prompt, length {len(combined)} chars.")
diff --git a/squilla_router/__init__.py b/squilla_router/__init__.py
new file mode 100644
index 000000000..89572d49f
--- /dev/null
+++ b/squilla_router/__init__.py
@@ -0,0 +1,7 @@
+"""SquillaRouter - 省token的级联路由引擎"""
+
+from squilla_router.cascade_router import (
+ CascadeRouter, RouterDecision, get_router, route_decision,
+ TIER_ORDER, DEFAULT_TIER, normalize_text_tier, tier_index,
+)
+from squilla_router.config import TIER_MODEL_MAP, get_model_config, list_tiers
diff --git a/squilla_router/cascade_router.py b/squilla_router/cascade_router.py
new file mode 100644
index 000000000..6f312f610
--- /dev/null
+++ b/squilla_router/cascade_router.py
@@ -0,0 +1,260 @@
+"""CascadeRouter: GenericAgent 级联路由引擎入口。
+
+在 agent_loop 的每个 turn 前调用，根据对话上下文
+选择最优模型 tier，并支持级联降级/升级。
+"""
+
+import os, json, time, logging
+from dataclasses import dataclass, field
+from typing import Optional
+
+logger = logging.getLogger(__name__)
+
+# ── 路由层级定义 ──────────────────────────────────────────
+TIER_ORDER = ("c0", "c1", "c2", "c3")
+DEFAULT_TIER = "c1"
+HIGHEST_TIER = "c3"
+
+def normalize_text_tier(raw: str) -> Optional[str]:
+ if not raw:
+ return None
+ t = raw.strip().lower().replace("t", "c")
+ if t in TIER_ORDER:
+ return t
+ return None
+
+def tier_index(tier: str) -> int:
+ try:
+ return TIER_ORDER.index(tier)
+ except ValueError:
+ return 1
+
+# ── 轨迹定义 ──────────────────────────────────────────
+class Trajectory:
+ COLD_START = "COLD_START"
+ STABLE_LOW = "STABLE_LOW"
+ STABLE_HIGH = "STABLE_HIGH"
+ ESCALATING = "ESCALATING"
+ DESCALATING = "DESCALATING"
+ OSCILLATING = "OSCILLATING"
+
+def classify_trajectory(history: list) -> str:
+ if not history or len(history) < 2:
+ return Trajectory.COLD_START
+ tiers = history[-6:]
+ try:
+ diffs = [tier_index(tiers[i+1]) - tier_index(tiers[i]) for i in range(len(tiers)-1)]
+ except (ValueError, IndexError):
+ return Trajectory.COLD_START
+ nonzero = [d for d in diffs if d != 0]
+ if not nonzero:
+ if tier_index(tiers[-1]) <= 1:
+ return Trajectory.STABLE_LOW
+ return Trajectory.STABLE_HIGH
+ if len(nonzero) >= 2 and all(d > 0 for d in nonzero):
+ return Trajectory.ESCALATING
+ if len(nonzero) >= 2 and all(d < 0 for d in nonzero):
+ return Trajectory.DESCALATING
+ direction_changes = sum(1 for a, b in zip(nonzero, nonzero[1:]) if a != b)
+ if direction_changes >= 2:
+ return Trajectory.OSCILLATING
+ return Trajectory.COLD_START
+
+
+@dataclass
+class RouterDecision:
+ """一次路由决策的结果"""
+ tier: str # 选定的 tier
+ model: str # 对应的模型名
+ provider: str # 对应的 provider
+ thinking_mode: str = "T1" # T0-T3 推理模式
+ prompt_policy: str = "P0" # P0-P2 提示策略
+ probs: dict = field(default_factory=dict) # 各tier概率
+ trajectory: str = Trajectory.COLD_START
+ latency_ms: float = 0.0
+
+
+class CascadeRouter:
+ """级联路由器 - 策略感知+历史感知的模型选择器。
+
+ 工作流程:
+ 1. fallback: 如果未配置路由模型，返回默认 tier
+ 2. 检查用户显式请求 (如 "use c3")
+ 3. 调用预测器 (如果可用)
+ 4. 应用 sticky tier (防抖)
+ 5. 级联: 如果选定模型可用则返回，否则降级
+ """
+
+ def __init__(self, predictor=None):
+ self._predictor = predictor # V4Phase3Predictor 实例
+ self._route_history: list[str] = [] # 每轮的 tier 决策历史
+ self._sticky_tier: Optional[str] = None
+ self._sticky_count = 0
+ self._last_decision: Optional[RouterDecision] = None
+ self._log_path = os.environ.get("SQUILLA_ROUTER_LOG", "")
+ if not self._log_path:
+ self._log_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "temp", "router_log.jsonl")
+
+ def decide(self,
+ current_text: str,
+ history_texts: list[str],
+ prev_assistant_text: Optional[str] = None,
+ prev_assistant_usage: Optional[dict] = None,
+ force_tier: Optional[str] = None,
+ available_tiers: list[str] | None = None,
+ flags: dict | None = None,
+ ) -> RouterDecision:
+ """执行路由决策。"""
+ start = time.time()
+
+ # 1. 强制 tier (用户指定)
+ if force_tier:
+ tier = normalize_text_tier(force_tier) or DEFAULT_TIER
+ probs = {tier: 1.0}
+ else:
+ # 2. 预测器 (如果已加载 V4 模型)
+ if self._predictor and self._predictor.is_available():
+ try:
+ result = self._predictor.predict(
+ current_user_text=current_text,
+ history_user_texts=history_texts,
+ prev_assistant_text=prev_assistant_text,
+ prev_assistant_usage=prev_assistant_usage or {},
+ prev_route_decisions=self._route_history[-5:] if self._route_history else [],
+ flags=flags or {},
+ )
+ tier = normalize_text_tier(result.decision.selected_model) or DEFAULT_TIER
+ probs = result.probabilities
+ except Exception as e:
+ logger.warning(f"[Router] 预测失败, 使用默认: {e}")
+ tier = DEFAULT_TIER
+ probs = {}
+ else:
+ # 无预测器: 简单启发式
+ tier = self._heuristic_route(current_text, history_texts)
+ probs = {}
+
+ # 3. 应用 sticky tier (防抖)
+ tier = self._apply_sticky(tier)
+
+ # 4. 级联降级: 确保模型可用
+ final_tier = self._cascade(tier, available_tiers)
+
+ # 5. 记录
+ self._route_history.append(final_tier)
+ trajectory = classify_trajectory(self._route_history)
+
+ elapsed = (time.time() - start) * 1000
+
+ from .config import get_model_config
+ cfg = get_model_config(final_tier)
+ decision = RouterDecision(
+ tier=final_tier,
+ model=cfg["model"],
+ provider=cfg["provider"],
+ probs=probs,
+ trajectory=trajectory,
+ latency_ms=elapsed,
+ )
+ self._last_decision = decision
+ # 埋点: 写入 JSONL 日志
+ try:
+ import json
+ log_entry = {
+ "ts": time.time(), "tier": final_tier, "model": cfg["model"],
+ "traj": str(trajectory), "latency_ms": round(elapsed, 1),
+ "text_len": len(current_text) if current_text else 0,
+ }
+ with open(self._log_path, "a", encoding="utf-8") as lf:
+ lf.write(json.dumps(log_entry, ensure_ascii=False) + "\n")
+ except Exception:
+ pass
+ return decision
+
+ def _heuristic_route(self, text: str, history: list) -> str:
+ """无预测器时的启发式路由:
+ - 短文本(<=50字)且轮次少 -> c0/c1
+ - 包含复杂关键词 -> c2/c3
+ """
+ text_len = len(text)
+ total_turns = len(history) if history else 0
+
+ complex_keywords = [
+ "分析", "总结", "解释", "optimize", "debug", "refactor",
+ "架构", "设计", "比较", "优缺点", "影响",
+ "complex", "difficult", "challenging",
+ ]
+
+ has_complex = any(kw in text.lower() for kw in complex_keywords)
+
+ if text_len < 50 and not has_complex and total_turns < 3:
+ return "c0"
+ elif text_len < 200 and not has_complex:
+ return "c1"
+ elif has_complex or text_len > 500:
+ return "c2"
+ return "c1"
+
+ def _apply_sticky(self, new_tier: str) -> str:
+ """KV-cache 感知的 sticky tier: 避免频繁切换"""
+ if self._sticky_tier and self._sticky_tier != new_tier:
+ new_idx = tier_index(new_tier)
+ sticky_idx = tier_index(self._sticky_tier)
+ # 如果当前预测比 sticky 低且 sticky 还较新 -> 保持
+ if new_idx < sticky_idx and self._sticky_count < 3:
+ self._sticky_count += 1
+ return self._sticky_tier
+ self._sticky_tier = new_tier
+ self._sticky_count = 0
+ return new_tier
+
+ def _cascade(self, tier: str, available: list[str] | None) -> str:
+ """级联降级: 如果选定 tier 不可用，往下降"""
+ if not available:
+ return tier
+ t = tier
+ while t not in available and tier_index(t) >= 0:
+ idx = tier_index(t)
+ if idx <= 0:
+ return DEFAULT_TIER
+ t = TIER_ORDER[idx - 1]
+ return t
+
+ def report_llm_failure(self, tier_used: str):
+ """反馈: LLM 调用失败，记录供下次降级使用"""
+ logger.info(f"[Router] LLM failure for tier={tier_used}, will cascade next time")
+
+ def reset(self):
+ self._route_history.clear()
+ self._sticky_tier = None
+ self._sticky_count = 0
+ self._last_decision = None
+
+ def get_stats(self) -> dict:
+ return {
+ "total_turns": len(self._route_history),
+ "history": self._route_history[-10:],
+ "last_tier": self._route_history[-1] if self._route_history else None,
+ }
+
+
+# ── 便捷函数 ──────────────────────────────────────────
+_DEFAULT_ROUTER: Optional[CascadeRouter] = None
+
+def get_router() -> CascadeRouter:
+ global _DEFAULT_ROUTER
+ if _DEFAULT_ROUTER is None:
+ _DEFAULT_ROUTER = CascadeRouter()
+ return _DEFAULT_ROUTER
+
+def route_decision(text: str,
+ history: list[str] | None = None,
+ force_tier: str | None = None,
+ available: list[str] | None = None) -> RouterDecision:
+ router = get_router()
+ return router.decide(
+ current_text=text,
+ history_texts=history or [],
+ force_tier=force_tier,
+ available_tiers=available,
+ )
diff --git a/squilla_router/config.py b/squilla_router/config.py
new file mode 100644
index 000000000..8ee22e95b
--- /dev/null
+++ b/squilla_router/config.py
@@ -0,0 +1,60 @@
+"""SquillaRouter 配置: Tier模型映射 + 模型路径"""
+
+import os
+
+_PKG_DIR = os.path.dirname(os.path.abspath(__file__))
+
+# Tier -> 模型配置映射
+# 用户在 mykey.py 中覆盖此映射
+TIER_MODEL_MAP = {
+ "c0": {
+ "provider": "native_oai",
+ "model": "deepseek-chat",
+ "max_tokens": 4096,
+ "reasoning": False,
+ "description": "极轻量模型 - 简单问答/翻译",
+ },
+ "c1": {
+ "provider": "native_oai",
+ "model": "deepseek-chat",
+ "max_tokens": 8192,
+ "reasoning": False,
+ "description": "中等模型 - 常规对话",
+ },
+ "c2": {
+ "provider": "native_oai",
+ "model": "deepseek-v4-pro",
+ "max_tokens": 32768,
+ "reasoning": False,
+ "description": "强模型(Pro) - 复杂推理/代码",
+ },
+ "c3": {
+ "provider": "native_oai",
+ "model": "deepseek-reasoner",
+ "max_tokens": 32768,
+ "reasoning": True,
+ "description": "最强模型+深度思考 - 高难度分析",
+ },
+}
+
+# BGE 模型目录 (ONNX INT8)
+BGE_MODEL_DIR = os.path.join(_PKG_DIR, "models", "bge_onnx")
+
+# LightGBM 模型目录
+LGBM_MODEL_DIR = os.path.join(_PKG_DIR, "models", "lightgbm")
+
+# MLP 校准模型目录
+MLP_MODEL_DIR = os.path.join(_PKG_DIR, "models", "mlp")
+
+# 运行时配置目录
+V4_BUNDLE_DIR = os.path.join(_PKG_DIR, "models", "v4_bundle")
+
+
+def get_model_config(tier: str) -> dict:
+ """获取指定 tier 的模型配置"""
+ return TIER_MODEL_MAP.get(tier, TIER_MODEL_MAP["c1"])
+
+
+def list_tiers() -> list[str]:
+ """返回所有可用 tier 列表"""
+ return sorted(TIER_MODEL_MAP.keys())
diff --git a/squilla_router/controller.py b/squilla_router/controller.py
new file mode 100644
index 000000000..1fb9eb75d
--- /dev/null
+++ b/squilla_router/controller.py
@@ -0,0 +1,164 @@
+"""Post-processing controllers: derive thinking mode and prompt policy.
+
+Pure functions — no I/O and no model runtime dependency. The bundled v4
+router usually returns T0-T3 / P0-P2 directly; synthetic probability vectors
+are retained only for safe fallback/default handling.
+"""
+
+from __future__ import annotations
+
+from squilla_router.router_tiers import TEXT_TIERS
+
+TIER_ORDER: list[str] = list(TEXT_TIERS)
+
+_SYNTHETIC_PEAK = 0.85
+
+
+def synthetic_one_hot(tier: str, dominant: float = _SYNTHETIC_PEAK) -> list[float]:
+ """Return a synthetic 4-class probability vector peaking on *tier*."""
+ n = len(TIER_ORDER)
+ residual = (1.0 - dominant) / max(n - 1, 1)
+ idx = TIER_ORDER.index(tier) if tier in TIER_ORDER else 1
+ probs = [residual] * n
+ probs[idx] = dominant
+ return probs
+
+DIFFICULTY_WEIGHTS: list[float] = [0.0, 1.0, 2.0, 3.0]
+
+_THINKING_MODE_LEVEL: dict[str, str | None] = {
+ "T0": None,
+ "T1": "low",
+ "T2": "medium",
+ "T3": "high",
+}
+
+_P0_HINT_EN = "Answer directly, keep thinking short, avoid irrelevant expansion."
+_P0_HINT_ZH = "直接作答，缩短思考长度，避免无关展开。"
+_P0_HINT = _P0_HINT_EN
+
+_PROMPT_HINTS: dict[str, dict[str, str]] = {
+ "P0": {
+ "hint_zh": _P0_HINT_ZH,
+ "hint_en": _P0_HINT_EN,
+ },
+}
+
+_CJK_RANGES = (
+ ("\u4e00", "\u9fff"),
+ ("\u3400", "\u4dbf"),
+ ("\uf900", "\ufaff"),
+)
+
+_DEEP_FLAGS = frozenset({"high_risk", "debug", "long_context"})
+_FULL_PROMPT_FLAGS = frozenset({"high_risk", "long_context", "debug", "strict_format"})
+_COMPRESS_BLOCK_FLAGS = frozenset({"high_risk", "strict_format", "debug"})
+
+
+def compute_difficulty(probs: list[float]) -> float:
+ return sum(w * p for w, p in zip(DIFFICULTY_WEIGHTS, probs))
+
+
+def compute_margin(probs: list[float]) -> float:
+ if len(probs) < 2:
+ return probs[0] if probs else 0.0
+ ordered = sorted(probs, reverse=True)
+ return max(0.0, ordered[0] - ordered[1])
+
+
+def _has_any_flag(flags: dict | object | None, flag_names: frozenset[str]) -> bool:
+ if flags is None:
+ return False
+ if isinstance(flags, dict):
+ return any(flags.get(f) for f in flag_names)
+ return any(getattr(flags, f, False) for f in flag_names)
+
+
+def derive_thinking_mode(
+ probs: list[float],
+ flags: dict | object | None = None,
+ *,
+ t3_min_idx: int = 2,
+ t0_max_idx: int = 0,
+ t0_min_margin: float = 0.5,
+ t1_max_idx: int = 1,
+ t1_min_margin: float = 0.4,
+) -> str:
+ top1_idx = int(max(range(len(probs)), key=lambda i: probs[i]))
+ margin = compute_margin(probs)
+
+ if top1_idx >= len(TIER_ORDER) - 1:
+ return "T3"
+ if top1_idx >= t3_min_idx and _has_any_flag(flags, _DEEP_FLAGS):
+ return "T3"
+ if top1_idx <= t0_max_idx and margin >= t0_min_margin:
+ return "T0"
+ if top1_idx <= t1_max_idx and margin >= t1_min_margin:
+ return "T1"
+ return "T2"
+
+
+def derive_prompt_policy(
+ probs: list[float],
+ flags: dict | object | None = None,
+ *,
+ max_difficulty: float = 0.8,
+ min_margin: float = 0.4,
+) -> str:
+ if _has_any_flag(flags, _FULL_PROMPT_FLAGS):
+ return "P2"
+ difficulty = compute_difficulty(probs)
+ margin = compute_margin(probs)
+ if (
+ difficulty <= max_difficulty
+ and margin >= min_margin
+ and not _has_any_flag(flags, _COMPRESS_BLOCK_FLAGS)
+ ):
+ return "P0"
+ return "P1"
+
+
+def normalize_decisions(thinking_mode: str, prompt_policy: str) -> tuple[str, str]:
+ """Forbid THINK_DEEP + P0 (compress) — contradictory."""
+ if thinking_mode in ("T2", "T3") and prompt_policy == "P0":
+ return thinking_mode, "P1"
+ return thinking_mode, prompt_policy
+
+
+def thinking_mode_to_level(mode: str | None) -> str | None:
+ if mode is None:
+ return None
+ return _THINKING_MODE_LEVEL.get(mode)
+
+
+def prompt_hint_locale(text: str | None) -> str:
+ """Return ``zh`` when the prompt is substantially CJK, else ``en``."""
+ if not text:
+ return "en"
+ cjk_count = 0
+ latin_count = 0
+ for char in text:
+ if any(start <= char <= end for start, end in _CJK_RANGES):
+ cjk_count += 1
+ elif char.isascii() and char.isalpha():
+ latin_count += 1
+ if cjk_count >= 2:
+ return "zh"
+ return "en"
+
+
+def select_localized_prompt_hint(policy_cfg: dict, text: str | None) -> str | None:
+ """Select hint_zh or hint_en from a prompt policy using current input language."""
+ if prompt_hint_locale(text) == "zh":
+ return policy_cfg.get("hint_zh") or policy_cfg.get("hint_en") or None
+ return policy_cfg.get("hint_en") or policy_cfg.get("hint_zh") or None
+
+
+def get_prompt_hint(policy: str | None, text: str | None = None) -> str | None:
+ if policy is None:
+ return None
+ hint_cfg = _PROMPT_HINTS.get(policy)
+ if not hint_cfg:
+ return None
+ if text is None:
+ return hint_cfg.get("hint_en") or hint_cfg.get("hint_zh")
+ return select_localized_prompt_hint(hint_cfg, text)
diff --git a/squilla_router/models/bge_onnx/.gitkeep b/squilla_router/models/bge_onnx/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/squilla_router/models/lightgbm/.gitkeep b/squilla_router/models/lightgbm/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/squilla_router/models/mlp/.gitkeep b/squilla_router/models/mlp/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/squilla_router/models/v4_bundle/.gitkeep b/squilla_router/models/v4_bundle/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/squilla_router/models/v4_bundle/PROVENANCE.md b/squilla_router/models/v4_bundle/PROVENANCE.md
new file mode 100644
index 000000000..876a069a2
--- /dev/null
+++ b/squilla_router/models/v4_bundle/PROVENANCE.md
@@ -0,0 +1,62 @@
+# SquillaRouter V4 Phase 3 Bundle Provenance
+
+This directory contains the local inference bundle used by
+`opensquilla.squilla_router.v4_phase3.V4Phase3Strategy`.
+
+## Purpose
+
+The bundle provides the V4 Phase 3 local model router used to classify a turn
+into route classes `R0` through `R3`, which are then mapped to configured model
+tiers by OpenSquilla gateway configuration. This provenance file does not change
+runtime behavior; it records the assets that the existing runtime loads.
+
+## Bundled Asset Groups
+
+- `lgbm_main.bin` and `lgbm_aux.bin`: LightGBM booster files for router heads.
+- `mlp/model.onnx` and `mlp/scaler.joblib`: MLP head model and scaler.
+- `features/tfidf.pkl`, `features/svd.pkl`, `features/config.pkl`, and
+ `features/bge_pca.joblib`: scikit-learn/joblib feature extraction artifacts.
+- `bge_onnx/*`: ONNX export and tokenizer files derived from
+ `BAAI/bge-small-zh-v1.5`.
+- `router.runtime.yaml`, `version.json`, and `inference_manifest.json`: router
+ runtime configuration and inference metadata.
+
+## Upstream Model Attribution
+
+The BGE assets are derived from `BAAI/bge-small-zh-v1.5`:
+
+- Hugging Face model: https://huggingface.co/BAAI/bge-small-zh-v1.5
+- Upstream project: https://github.com/FlagOpen/FlagEmbedding
+- License: MIT
+
+The upstream MIT notice is recorded in the repository root
+`THIRD_PARTY_NOTICES.md`.
+
+## Conversion Notes
+
+The repository contains runtime router metadata including feature dimensions,
+route classes, and the BGE model name. Runtime behavior is defined by the
+checked-in artifacts and configuration listed below.
+
+Current known metadata:
+
+- `version.json` records the router version, feature channels,
+ `BAAI/bge-small-zh-v1.5`, and backend `onnx`.
+- `inference_manifest.json` records feature dimensions, route classes,
+ temperature, class alpha values, BGE backend, and BGE ONNX directory.
+
+## Safety Notes
+
+The current runtime deserializes `.pkl` and `.joblib` artifacts through
+`joblib.load`. Treat those files as executable-code-equivalent inputs. Only use
+assets shipped with a trusted OpenSquilla release or assets whose size and
+sha256 match `artifact_manifest.json`.
+
+## Update Procedure
+
+When any router asset changes:
+
+1. Re-run `python scripts/update_router_artifact_manifest.py`.
+2. Review the changed `artifact_manifest.json` entries.
+3. Run `uv run pytest tests/test_ci/test_router_artifact_manifest.py -q`.
+4. Include any required notice or provenance changes in the same commit.
diff --git a/squilla_router/models/v4_bundle/artifact_manifest.json b/squilla_router/models/v4_bundle/artifact_manifest.json
new file mode 100644
index 000000000..4afecbea6
--- /dev/null
+++ b/squilla_router/models/v4_bundle/artifact_manifest.json
@@ -0,0 +1,133 @@
+{
+ "schema_version": 1,
+ "bundle": "src/opensquilla/squilla_router/models/v4.2_phase3_inference",
+ "description": "Checksums and provenance notes for SquillaRouter V4 Phase 3 assets.",
+ "files": [
+ {
+ "path": "bge_onnx/config.json",
+ "size_bytes": 688,
+ "sha256": "a7ef8b7733d4d54670d88617be0a426b56152296844e5ff603ef6fda92633da0",
+ "kind": "json_metadata",
+ "source_note": "Derived from BAAI/bge-small-zh-v1.5; see PROVENANCE.md."
+ },
+ {
+ "path": "bge_onnx/model.onnx",
+ "size_bytes": 23902398,
+ "sha256": "87847793fac866d65b19cee2e73a6b2a2446a1262ab0911b1dbf9b3e9399ef9d",
+ "kind": "onnx_model",
+ "source_note": "Derived from BAAI/bge-small-zh-v1.5; see PROVENANCE.md."
+ },
+ {
+ "path": "bge_onnx/special_tokens_map.json",
+ "size_bytes": 695,
+ "sha256": "5d5b662e421ea9fac075174bb0688ee0d9431699900b90662acd44b2a350503a",
+ "kind": "json_metadata",
+ "source_note": "Derived from BAAI/bge-small-zh-v1.5; see PROVENANCE.md."
+ },
+ {
+ "path": "bge_onnx/tokenizer.json",
+ "size_bytes": 439125,
+ "sha256": "48cea5d44424912a6fd1ea647bf4fe50b55ab8b1e5879c3275f80e339e8fae26",
+ "kind": "json_metadata",
+ "source_note": "Derived from BAAI/bge-small-zh-v1.5; see PROVENANCE.md."
+ },
+ {
+ "path": "bge_onnx/tokenizer_config.json",
+ "size_bytes": 1273,
+ "sha256": "470cff6e0353b08e2a6e9b4f61729ecdc47ccb3ced335fa5520e9ce334572d59",
+ "kind": "json_metadata",
+ "source_note": "Derived from BAAI/bge-small-zh-v1.5; see PROVENANCE.md."
+ },
+ {
+ "path": "bge_onnx/vocab.txt",
+ "size_bytes": 109540,
+ "sha256": "45bbac6b341c319adc98a532532882e91a9cefc0329aa57bac9ae761c27b291c",
+ "kind": "text_asset",
+ "source_note": "Derived from BAAI/bge-small-zh-v1.5; see PROVENANCE.md."
+ },
+ {
+ "path": "features/bge_pca.joblib",
+ "size_bytes": 135059,
+ "sha256": "9ee12bcd481a94516b074160e39f0b909c089393d73ffbf0167d3beba995fc23",
+ "kind": "pickle_joblib_artifact",
+ "source_note": "Router runtime feature extraction artifact."
+ },
+ {
+ "path": "features/config.pkl",
+ "size_bytes": 26,
+ "sha256": "9e1225d053527975dca018deab6e3ae3fea2070ded20cd01ef0e7eea711cce82",
+ "kind": "pickle_joblib_artifact",
+ "source_note": "Router runtime feature extraction artifact."
+ },
+ {
+ "path": "features/meta.json",
+ "size_bytes": 160,
+ "sha256": "fa7c412e32fee37088e03480494e3d0b8ed859b12222e37f22e33aec3778a3de",
+ "kind": "json_metadata",
+ "source_note": "Router runtime feature extraction artifact."
+ },
+ {
+ "path": "features/svd.pkl",
+ "size_bytes": 8003143,
+ "sha256": "5d2af9e78565e58e919fb83c7a01973e394436fd43cf6813c7cd2280aa140172",
+ "kind": "pickle_joblib_artifact",
+ "source_note": "Router runtime feature extraction artifact."
+ },
+ {
+ "path": "features/tfidf.pkl",
+ "size_bytes": 344158,
+ "sha256": "bb90fb1af13ff1b15104d22b8d1dfc712ae32bf8d7db959ca56b3d7c92872293",
+ "kind": "pickle_joblib_artifact",
+ "source_note": "Router runtime feature extraction artifact."
+ },
+ {
+ "path": "inference_manifest.json",
+ "size_bytes": 679,
+ "sha256": "1addef2deddaac2a60800eb631c5878765a49ad100ede4d54022d2d3bf8e2df2",
+ "kind": "json_metadata",
+ "source_note": "Router V4 Phase 3 bundle metadata or runtime configuration."
+ },
+ {
+ "path": "lgbm_aux.bin",
+ "size_bytes": 3481929,
+ "sha256": "e8749e412d2db861928cb9d8a9b39cdd134a4d71091430ffae014337d4b1aed4",
+ "kind": "lightgbm_model",
+ "source_note": "Router runtime LightGBM head artifact."
+ },
+ {
+ "path": "lgbm_main.bin",
+ "size_bytes": 39684725,
+ "sha256": "5f312db09577bbaf30f87358941974eef6edce7f1424d0e9de21cbd38a646d53",
+ "kind": "lightgbm_model",
+ "source_note": "Router runtime LightGBM head artifact."
+ },
+ {
+ "path": "mlp/model.onnx",
+ "size_bytes": 2367544,
+ "sha256": "e7358ac3f827e8f38a6384ba4f7c6f3227c18898ced95d145adb9272c72137d6",
+ "kind": "onnx_model",
+ "source_note": "Router runtime MLP head artifact."
+ },
+ {
+ "path": "mlp/scaler.joblib",
+ "size_bytes": 37447,
+ "sha256": "be1d8d9615ac5d20d26b7287dae485f13804b22fdb42c3aea1e1a9186914b9ee",
+ "kind": "pickle_joblib_artifact",
+ "source_note": "Router runtime MLP head artifact."
+ },
+ {
+ "path": "router.runtime.yaml",
+ "size_bytes": 5069,
+ "sha256": "b49ae2024242bb56a3428e9fde0dfd57ddf2d3cc04f362b1d886e90c1aef965c",
+ "kind": "yaml_config",
+ "source_note": "Router V4 Phase 3 bundle metadata or runtime configuration."
+ },
+ {
+ "path": "version.json",
+ "size_bytes": 240,
+ "sha256": "806a413d0a8caa5f6b566060c0131b38466e68efce0b09b2d4902f4aef8bfd1c",
+ "kind": "json_metadata",
+ "source_note": "Router V4 Phase 3 bundle metadata or runtime configuration."
+ }
+ ]
+}
diff --git a/squilla_router/models/v4_bundle/bge_onnx/config.json b/squilla_router/models/v4_bundle/bge_onnx/config.json
new file mode 100644
index 000000000..99a4d6392
--- /dev/null
+++ b/squilla_router/models/v4_bundle/bge_onnx/config.json
@@ -0,0 +1,31 @@
+{
+ "architectures": [
+ "BertModel"
+ ],
+ "attention_probs_dropout_prob": 0.1,
+ "classifier_dropout": null,
+ "dtype": "float32",
+ "gradient_checkpointing": false,
+ "hidden_act": "gelu",
+ "hidden_dropout_prob": 0.1,
+ "hidden_size": 512,
+ "id2label": {
+ "0": "LABEL_0"
+ },
+ "initializer_range": 0.02,
+ "intermediate_size": 2048,
+ "label2id": {
+ "LABEL_0": 0
+ },
+ "layer_norm_eps": 1e-12,
+ "max_position_embeddings": 512,
+ "model_type": "bert",
+ "num_attention_heads": 8,
+ "num_hidden_layers": 4,
+ "pad_token_id": 0,
+ "position_embedding_type": "absolute",
+ "transformers_version": "4.57.6",
+ "type_vocab_size": 2,
+ "use_cache": true,
+ "vocab_size": 21128
+}
diff --git a/squilla_router/models/v4_bundle/bge_onnx/model.onnx b/squilla_router/models/v4_bundle/bge_onnx/model.onnx
new file mode 100644
index 000000000..8c5955230
Binary files /dev/null and b/squilla_router/models/v4_bundle/bge_onnx/model.onnx differ
diff --git a/squilla_router/models/v4_bundle/bge_onnx/special_tokens_map.json b/squilla_router/models/v4_bundle/bge_onnx/special_tokens_map.json
new file mode 100644
index 000000000..9bbecc17c
--- /dev/null
+++ b/squilla_router/models/v4_bundle/bge_onnx/special_tokens_map.json
@@ -0,0 +1,37 @@
+{
+ "cls_token": {
+ "content": "[CLS]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
+ "mask_token": {
+ "content": "[MASK]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
+ "pad_token": {
+ "content": "[PAD]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
+ "sep_token": {
+ "content": "[SEP]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
+ "unk_token": {
+ "content": "[UNK]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ }
+}
diff --git a/squilla_router/models/v4_bundle/bge_onnx/tokenizer.json b/squilla_router/models/v4_bundle/bge_onnx/tokenizer.json
new file mode 100644
index 000000000..cdb3043fc
--- /dev/null
+++ b/squilla_router/models/v4_bundle/bge_onnx/tokenizer.json
@@ -0,0 +1,21278 @@
+{
+ "version": "1.0",
+ "truncation": null,
+ "padding": null,
+ "added_tokens": [
+ {
+ "id": 0,
+ "content": "[PAD]",
+ "single_word": false,
+ "lstrip": false,
+ "rstrip": false,
+ "normalized": false,
+ "special": true
+ },
+ {
+ "id": 100,
+ "content": "[UNK]",
+ "single_word": false,
+ "lstrip": false,
+ "rstrip": false,
+ "normalized": false,
+ "special": true
+ },
+ {
+ "id": 101,
+ "content": "[CLS]",
+ "single_word": false,
+ "lstrip": false,
+ "rstrip": false,
+ "normalized": false,
+ "special": true
+ },
+ {
+ "id": 102,
+ "content": "[SEP]",
+ "single_word": false,
+ "lstrip": false,
+ "rstrip": false,
+ "normalized": false,
+ "special": true
+ },
+ {
+ "id": 103,
+ "content": "[MASK]",
+ "single_word": false,
+ "lstrip": false,
+ "rstrip": false,
+ "normalized": false,
+ "special": true
+ }
+ ],
+ "normalizer": {
+ "type": "BertNormalizer",
+ "clean_text": true,
+ "handle_chinese_chars": true,
+ "strip_accents": null,
+ "lowercase": false
+ },
+ "pre_tokenizer": {
+ "type": "BertPreTokenizer"
+ },
+ "post_processor": {
+ "type": "TemplateProcessing",
+ "single": [
+ {
+ "SpecialToken": {
+ "id": "[CLS]",
+ "type_id": 0
+ }
+ },
+ {
+ "Sequence": {
+ "id": "A",
+ "type_id": 0
+ }
+ },
+ {
+ "SpecialToken": {
+ "id": "[SEP]",
+ "type_id": 0
+ }
+ }
+ ],
+ "pair": [
+ {
+ "SpecialToken": {
+ "id": "[CLS]",
+ "type_id": 0
+ }
+ },
+ {
+ "Sequence": {
+ "id": "A",
+ "type_id": 0
+ }
+ },
+ {
+ "SpecialToken": {
+ "id": "[SEP]",
+ "type_id": 0
+ }
+ },
+ {
+ "Sequence": {
+ "id": "B",
+ "type_id": 1
+ }
+ },
+ {
+ "SpecialToken": {
+ "id": "[SEP]",
+ "type_id": 1
+ }
+ }
+ ],
+ "special_tokens": {
+ "[CLS]": {
+ "id": "[CLS]",
+ "ids": [
+ 101
+ ],
+ "tokens": [
+ "[CLS]"
+ ]
+ },
+ "[SEP]": {
+ "id": "[SEP]",
+ "ids": [
+ 102
+ ],
+ "tokens": [
+ "[SEP]"
+ ]
+ }
+ }
+ },
+ "decoder": {
+ "type": "WordPiece",
+ "prefix": "##",
+ "cleanup": true
+ },
+ "model": {
+ "type": "WordPiece",
+ "unk_token": "[UNK]",
+ "continuing_subword_prefix": "##",
+ "max_input_chars_per_word": 100,
+ "vocab": {
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\ No newline at end of file
diff --git a/squilla_router/models/v4_bundle/bge_onnx/tokenizer_config.json b/squilla_router/models/v4_bundle/bge_onnx/tokenizer_config.json
new file mode 100644
index 000000000..4af6573d6
--- /dev/null
+++ b/squilla_router/models/v4_bundle/bge_onnx/tokenizer_config.json
@@ -0,0 +1,58 @@
+{
+ "added_tokens_decoder": {
+ "0": {
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+ "single_word": false,
+ "special": true
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+ "extra_special_tokens": {},
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+ "never_split": null,
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+ "strip_accents": null,
+ "tokenize_chinese_chars": true,
+ "tokenizer_class": "BertTokenizer",
+ "unk_token": "[UNK]"
+}
diff --git a/squilla_router/models/v4_bundle/bge_onnx/vocab.txt b/squilla_router/models/v4_bundle/bge_onnx/vocab.txt
new file mode 100644
index 000000000..ca4f97810
--- /dev/null
+++ b/squilla_router/models/v4_bundle/bge_onnx/vocab.txt
@@ -0,0 +1,21128 @@
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