feat(v2): 模型设置（用户可调小模型/大模型/管线，/config + UI）
This commit is contained in:
tzt
+58
-3
@@ -39,6 +39,7 @@ _router: Optional[Router] = None
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_pipeline: Optional["CollaborativePipeline"] = None
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_v2stats = V2Stats() if _V2_OK else None
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_review = None
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_settings = None
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def get_router() -> Router:
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@@ -56,8 +57,23 @@ def get_review() -> "ReviewQueue":
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return _review
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def settings_store():
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"""用户可调整设置（懒加载单例）。"""
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global _settings
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if _settings is None:
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from gateway.settings import load_settings
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_settings = load_settings()
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return _settings
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def rebuild_pipeline() -> None:
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"""清除管线单例，下次调用重建（配置改动后生效）。"""
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global _pipeline
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_pipeline = None
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def build_v2_pipeline(worker_cfg_override: Optional[dict] = None):
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"""从配置构建 v2 协作管线（architect + worker + pipeline）。
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"""从配置 + 用户设置构建 v2 协作管线（architect + worker + pipeline）。
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worker_cfg_override 可注入（测试/演示用 mock）。无 API key 时 /chat 会走
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本地降级路径（不崩溃）。
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@@ -65,13 +81,27 @@ def build_v2_pipeline(worker_cfg_override: Optional[dict] = None):
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global _pipeline
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if _pipeline is None:
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cfg = load_config()
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s = settings_store().to_dict() if _V2_OK else {}
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kb = KnowledgeBase()
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architect = build_architect(cfg.get("architect", {}))
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# architect（合并用户设置）
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acfg = dict(cfg.get("architect", {}))
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acfg.update(s.get("architect", {}))
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architect = build_architect(acfg)
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# worker（合并用户设置；backend 可 mock/openai/llama_server）
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wcfg = dict(cfg.get("worker", {}))
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wcfg.update(s.get("worker", {}))
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if worker_cfg_override:
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wcfg.update(worker_cfg_override)
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worker = build_worker(wcfg, kb=kb)
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_pipeline = build_pipeline(cfg, architect, worker)
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# pipeline（合并用户设置）
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cfg2 = dict(cfg)
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pcfg = dict(cfg.get("pipeline", {}))
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pcfg.update(s.get("pipeline", {}))
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cfg2["pipeline"] = pcfg
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_pipeline = build_pipeline(cfg2, architect, worker)
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return _pipeline
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@@ -221,6 +251,31 @@ try:
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raise HTTPException(status_code=404, detail=f"审核记录不存在或已审核: {review_id}")
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return {"ok": True, "review_id": review_id, "verdict": verdict}
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# ---------------- 模型设置（用户可调整） ----------------
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@app.get("/config", tags=["settings"])
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async def get_config():
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"""读取当前可调整设置（小模型 / 大模型 / 管线）。"""
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return settings_store().to_dict()
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@app.put("/config", tags=["settings"])
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async def put_config(patch: dict):
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"""部分更新设置并重建管线。示例：
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{"worker": {"backend": "openai", "base_url": "http://127.0.0.1:11434/v1", "temperature": 0.4}}
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"""
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try:
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merged = settings_store().update(patch)
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except Exception as e:
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raise HTTPException(status_code=400, detail=f"设置非法: {e}")
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rebuild_pipeline()
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return merged
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@app.post("/config/reset", tags=["settings"])
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async def reset_config():
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"""恢复默认设置并重建管线。"""
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merged = settings_store().reset()
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rebuild_pipeline()
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return merged
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# ---------------- metrics ----------------
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@app.get("/metrics", tags=["system"])
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async def metrics():
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@@ -0,0 +1,114 @@
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"""可调整的运行设置（SettingsStore）—— 让用户自定义内置小模型 / 大模型 / 管线。
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用户可在 Web 界面"模型设置"里调整并持久化到 config/settings.json（gitignore），
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重启后保留。调整会触发 v2 管线重建（gateway.api.build_v2_pipeline 重新读取）。
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默认值与 config/config.yaml 的 v2 段一致；settings.json 只存用户改动覆盖项。
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"""
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from __future__ import annotations
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import json
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from pathlib import Path
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from typing import Any, Dict, Optional
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_SETTINGS_PATH = Path(__file__).resolve().parent.parent / "config" / "settings.json"
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# 可调整项（含默认值）；用户改动存这里
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DEFAULTS: Dict[str, Any] = {
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"worker": {
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"backend": "llama_server", # mock | openai/api | llama_server
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"model": "models/qwen3.5-4b-q4_k_m.gguf",
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"base_url": "", # openai 后端填 http://127.0.0.1:11434/v1 等
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"port": 8901, # llama_server 端口
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"temperature": 0.3,
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"max_fix_attempts": 2,
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"code_timeout_s": 10,
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},
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"architect": {
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"model": "deepseek-chat",
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"base_url": "https://api.deepseek.com/v1",
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"api_key_env": "DEEPSEEK_API_KEY",
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},
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"pipeline": {
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"fast_path": True,
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"rounds_cap": 6,
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"api_token_cap": 8000,
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"breach_policy": "architect_do",
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},
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}
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class SettingsStore:
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"""用户可调整设置（内存 + settings.json 持久化）。"""
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def __init__(self, path: Optional[Path] = None):
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self._path = Path(path) if path else _SETTINGS_PATH
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self._data: Dict[str, Any] = {}
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self.load()
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# ---------- 持久化 ----------
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def load(self) -> None:
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if self._path.exists():
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try:
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self._data = json.loads(self._path.read_text(encoding="utf-8"))
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except Exception:
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self._data = {}
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else:
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self._data = {}
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def save(self) -> None:
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self._path.parent.mkdir(parents=True, exist_ok=True)
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self._path.write_text(
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json.dumps(self._data, ensure_ascii=False, indent=2), encoding="utf-8")
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# ---------- 访问 ----------
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def to_dict(self) -> Dict[str, Any]:
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"""返回 默认值 + 用户覆盖 合并后的完整设置。"""
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merged: Dict[str, Any] = {}
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for section, defaults in DEFAULTS.items():
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ov = self._data.get(section, {})
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merged[section] = {**defaults, **(ov if isinstance(ov, dict) else {})}
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return merged
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def get(self, section: str, key: str, default: Any = None) -> Any:
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merged = self.to_dict()
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return merged.get(section, {}).get(key, default)
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def update(self, patch: Dict[str, Any]) -> Dict[str, Any]:
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"""应用部分更新（可只传改动的 section/key）。返回合并后的完整设置。"""
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for section, values in patch.items():
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if section not in DEFAULTS or not isinstance(values, dict):
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continue
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cur = self._data.setdefault(section, {})
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for k, v in values.items():
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if k in DEFAULTS[section]:
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cur[k] = _coerce(v, DEFAULTS[section][k])
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self.save()
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return self.to_dict()
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def reset(self) -> Dict[str, Any]:
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"""恢复默认。"""
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self._data = {}
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self.save()
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return self.to_dict()
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def _coerce(value: Any, template: Any) -> Any:
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"""按默认值的类型把输入转成一致类型（数值容错）。"""
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if isinstance(template, bool):
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return bool(value)
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if isinstance(template, int):
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try:
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return int(float(value))
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except (TypeError, ValueError):
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return template
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if isinstance(template, float):
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try:
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return float(value)
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except (TypeError, ValueError):
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return template
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return value
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def load_settings(path: Optional[Path] = None) -> SettingsStore:
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return SettingsStore(path)
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@@ -58,6 +58,9 @@ input,select{background:var(--panel2);border:1px solid var(--line);color:var(--t
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.muted{color:var(--muted)}
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.history{max-height:220px;overflow:auto;margin-top:8px}
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table{width:100%;border-collapse:collapse;font-size:13px}
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.form-grid{display:grid;grid-template-columns:repeat(auto-fill,minmax(220px,1fr));gap:12px}
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.form-grid label{display:flex;flex-direction:column;gap:5px;font-size:12px;color:var(--muted)}
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.form-grid input,.form-grid select{width:100%}
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th,td{text-align:left;padding:8px;border-bottom:1px solid var(--line)}
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th{color:var(--muted);font-weight:600}
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footer{padding:8px 20px;color:var(--muted);font-size:11px;border-top:1px solid var(--line);background:var(--panel)}
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@@ -74,6 +77,7 @@ footer{padding:8px 20px;color:var(--muted);font-size:11px;border-top:1px solid v
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<button data-tab="work">🔗 协作过程</button>
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<button data-tab="review">🧑💻 人工检验</button>
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<button data-tab="metrics">📊 指标</button>
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<button data-tab="settings">⚙️ 模型设置</button>
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</nav>
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<main>
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<!-- 对话 -->
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@@ -115,6 +119,53 @@ footer{padding:8px 20px;color:var(--muted);font-size:11px;border-top:1px solid v
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<div class="row-btns" style="margin-bottom:10px"><button class="small" id="refreshMetrics">刷新</button></div>
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<div id="metricsResult"></div>
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</section>
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<!-- 模型设置 -->
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<section class="panel" id="panel-settings">
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<div class="card">
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<h3>⚙️ 内置小模型（Worker）</h3>
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<div class="form-grid">
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<label>后端 backend
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<select id="set-worker-backend">
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<option value="llama_server">llama_server（内置本地模型）</option>
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<option value="openai">openai/api（Ollama / vLLM 等兼容端点）</option>
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<option value="mock">mock（演示，零运行时）</option>
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</select>
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</label>
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<label>模型路径/名称 <input id="set-worker-model" type="text" placeholder="models/xxx.gguf 或模型名"></label>
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<label>端点 base_url（openai 用） <input id="set-worker-baseurl" type="text" placeholder="http://127.0.0.1:11434/v1"></label>
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<label>端口（llama_server） <input id="set-worker-port" type="number"></label>
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<label>temperature <input id="set-worker-temperature" type="number" step="0.1"></label>
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<label>max_fix_attempts <input id="set-worker-fix" type="number"></label>
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</div>
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</div>
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<div class="card">
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<h3>🧠 大模型（Architect / API）</h3>
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<div class="form-grid">
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<label>model <input id="set-arch-model" type="text"></label>
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<label>base_url <input id="set-arch-baseurl" type="text"></label>
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<label>api_key_env <input id="set-arch-keyenv" type="text"></label>
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</div>
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</div>
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<div class="card">
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<h3>🔀 管线 pipeline</h3>
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<div class="form-grid">
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<label>fast_path（快路径直答） <input id="set-pipe-fast" type="checkbox"></label>
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<label>rounds_cap <input id="set-pipe-rounds" type="number"></label>
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<label>api_token_cap <input id="set-pipe-tokens" type="number"></label>
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<label>breach_policy
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<select id="set-pipe-breach">
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<option value="architect_do">architect_do（兜底代做）</option>
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<option value="local_only">local_only（本地降级）</option>
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</select>
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</label>
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</div>
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</div>
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<div class="row-btns">
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<button class="primary" id="saveSettingsBtn">保存并生效</button>
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<button class="small" id="resetSettingsBtn">恢复默认</button>
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<span class="muted" id="settingsMsg"></span>
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</div>
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</section>
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</main>
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<footer>端云协同 LLM 协作系统 · v2 · 交流文本协议 · 北极星：token 下降 ≥80%</footer>
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<script>
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@@ -123,7 +174,7 @@ let lastRequestId=null;
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const esc=s=>{const d=document.createElement("div");d.textContent=s==null?"":String(s);return d.innerHTML;};
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function el(tag,cls,txt){const n=document.createElement(tag);if(cls)n.className=cls;if(txt!=null)n.textContent=txt;return n;}
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function setTab(t){document.querySelectorAll("nav button").forEach(b=>b.classList.toggle("active",b.dataset.tab===t));document.querySelectorAll(".panel").forEach(p=>p.classList.toggle("active",p.id==="panel-"+t));}
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document.querySelectorAll("nav button").forEach(b=>b.onclick=()=>{setTab(b.dataset.tab);if(b.dataset.tab==="review")loadReview();if(b.dataset.tab==="metrics")loadMetrics();});
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document.querySelectorAll("nav button").forEach(b=>b.onclick=()=>{setTab(b.dataset.tab);if(b.dataset.tab==="review")loadReview();if(b.dataset.tab==="metrics")loadMetrics();if(b.dataset.tab==="settings")loadSettings();});
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// ---- 健康状态 ----
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async function health(){try{const r=await fetch("/health");const d=await r.json();$("healthPill").textContent="健康 · "+d.domains.length+" 领域";}catch(e){$("healthPill").textContent="离线";}}
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@@ -154,6 +205,12 @@ async function sendLegacy(){const q=$("query").value.trim();if(!q)return;const h
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const SAMPLES=["用 Python 实现快速排序，并分析时间与空间复杂度","求解方程 x^2 - 5x + 6 = 0","高血压患者日常饮食需要注意什么","解释一下深度学习中的注意力机制"];
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function sample(){$("query").value=SAMPLES[Math.floor(Math.random()*SAMPLES.length)];}
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// ---- 模型设置 ----
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async function loadSettings(){try{const r=await fetch("/config");const s=await r.json();const w=s.worker||{};$("set-worker-backend").value=w.backend||"llama_server";$("set-worker-model").value=w.model||"";$("set-worker-baseurl").value=w.base_url||"";$("set-worker-port").value=w.port||8901;$("set-worker-temperature").value=w.temperature||0.3;$("set-worker-fix").value=w.max_fix_attempts||2;const a=s.architect||{};$("set-arch-model").value=a.model||"";$("set-arch-baseurl").value=a.base_url||"";$("set-arch-keyenv").value=a.api_key_env||"";const p=s.pipeline||{};$("set-pipe-fast").checked=!!p.fast_path;$("set-pipe-rounds").value=p.rounds_cap||6;$("set-pipe-tokens").value=p.api_token_cap||8000;$("set-pipe-breach").value=p.breach_policy||"architect_do";$("settingsMsg").textContent="";}catch(e){$("settingsMsg").textContent="读取失败："+e.message;}}
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async function saveSettings(){const patch={worker:{backend:$("set-worker-backend").value,model:$("set-worker-model").value,base_url:$("set-worker-baseurl").value,port:parseInt($("set-worker-port").value||8901),temperature:parseFloat($("set-worker-temperature").value||0.3),max_fix_attempts:parseInt($("set-worker-fix").value||2)},architect:{model:$("set-arch-model").value,base_url:$("set-arch-baseurl").value,api_key_env:$("set-arch-keyenv").value},pipeline:{fast_path:$("set-pipe-fast").checked,rounds_cap:parseInt($("set-pipe-rounds").value||6),api_token_cap:parseInt($("set-pipe-tokens").value||8000),breach_policy:$("set-pipe-breach").value}};try{const r=await fetch("/config",{method:"PUT",headers:{"Content-Type":"application/json"},body:JSON.stringify(patch)});const d=await r.json();$("settingsMsg").textContent=r.ok?"✅ 已保存并重建管线":"❌ "+(d.detail||"保存失败");}catch(e){$("settingsMsg").textContent="保存失败："+e.message;}}
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async function resetSettings(){try{await fetch("/config/reset",{method:"POST"});$("settingsMsg").textContent="已恢复默认设置";loadSettings();}catch(e){$("settingsMsg").textContent="重置失败："+e.message;}}
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$("saveSettingsBtn").onclick=saveSettings;
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$("resetSettingsBtn").onclick=resetSettings;
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$("sendBtn").onclick=sendChat;
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$("legacyBtn").onclick=sendLegacy;
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$("sampleBtn").onclick=sample;
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