yumoqing
8e32cb85f3
- selection.CHAT_CAPS=('t2t','i2t','m2t') 作为会话形态能力白名单唯一事实源
- model_options/resolve_model_name 加 capabilities 参数('chat'哨兵),
IN 列表展开占位符(sqlor传list会崩),capability 空串按 t2t 归一(COALESCE+NULLIF)
- chat_inference 同步门禁从「只认 t2t」放宽到 CHAT_CAPS——
实测根因:测试库 6 个机构策略主模型全是 qwen3.8-max(i2t),
16:28 已产生 FAILED「capability mismatch: i2t != t2t」,会话agent选它必挂
- m2t 入字典四处同步:种子 init/data.json + 端点注释 models.dspy
+ design-spec §6 能力表(+ 提取提示词在 pipeline-platform)
189 lines
8.3 KiB
Python
189 lines
8.3 KiB
Python
"""pipeline_llm.selection — 模型选择的唯一收敛点（下拉数据/引用解析/缺省模型）。
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2026-09-04 收敛改造：此前模型选择逻辑散在 pipeline-sdlc（cockpit/get_model_options/
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set_agent_model）、pipeline-core（agent_model_options、旧 llm CRUD）、pipeline-service
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（gateway/agent_loop 内联 SQL）多处，各查各的表、语义漂移。现全部收敛到本模块：
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- model_options() 所有模型下拉的唯一数据源
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- resolve_model_name() 模型引用（id/vendor_model_id/name）→ 注册名的唯一解析点
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- org_available_models() 机构可用模型清单（冒泡检测用）
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- 缺省模型由机构策略决定（inference._pick_default_model_name），不再写死模型名
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其他模块只允许薄壳委托（dspy 3-5 行）或函数调用，禁止再内联模型表 SQL。
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"""
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import logging
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from sqlor.dbpools import DBPools
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from ahserver.serverenv import ServerEnv
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logger = logging.getLogger("pipeline_llm.selection")
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# 会话/chat 形态可用的能力类型（2026-09-06 用户定夺）：文本输出的对话能力。
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# 会话 agent 模型下拉只列这些；embedding/rerank/图视频生成等形态各有专属入口。
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CHAT_CAPS = ('t2t', 'i2t', 'm2t')
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def _norm_caps(capabilities):
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"""capabilities 参数归一：'chat' 哨兵 → CHAT_CAPS；逗号串 → tuple；
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tuple/list 原样。返回 tuple（空 = 不过滤）。dspy 薄壳只传 'chat'，零 import。"""
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if isinstance(capabilities, str):
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s = capabilities.strip().lower()
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if not s:
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return ()
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if s == 'chat':
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return CHAT_CAPS
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return tuple(c.strip().lower() for c in s.split(',') if c.strip())
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return tuple(str(c).strip().lower() for c in (capabilities or ()) if str(c or '').strip())
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def _get_sor():
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env = ServerEnv()
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fn = getattr(env, 'get_module_dbname', None)
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dbname = 'pipeline'
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if callable(fn):
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try:
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dbname = fn('pipeline_llm') or 'pipeline'
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except Exception:
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dbname = 'pipeline'
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return DBPools(), dbname
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async def model_options(org_id, uid='', session_id='', pipeline_id='',
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value_field='id', capabilities=()):
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"""模型选择下拉的唯一数据源（对齐 llmage 分类：capability=能力类型）。
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机构语义与推理链一致：本机构 + 系统级共享（org_id 空/'0'）可见。
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selected 标记：项目已设模型（sd_projects.default_model，存 name）>
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个人全局选择（pipeline_agent_settings.default_llm_id，存 id）。
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value_field: 'id'=下拉值用模型 id（AgentIO 场景）；'name'=用注册名（角色模型配置场景）。
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capabilities: 能力类型白名单（tuple/list，如会话 agent 传 CHAT_CAPS=('t2t','i2t','m2t')）。
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空 = 不过滤（历史行为）。注意：存量模型 capability 为空的行按 't2t' 语义对待，
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过滤时用 COALESCE+NULLIF 把空串归一成 't2t' 再比对（DDL 有默认值，
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但历史迁移行可能是空串）。
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"""
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db, dbname = _get_sor()
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rows = []
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caps = _norm_caps(capabilities)
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async with db.sqlorContext(dbname) as sor:
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sql = ("SELECT m.id, m.name, m.vendor_model_id, m.capability, v.name AS vendor_name "
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"FROM llm_model m LEFT JOIN llm_vendor v ON v.id=m.vendor_id "
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"WHERE m.status='active'")
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params = {}
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if org_id and org_id != '0':
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sql += " AND (m.org_id=${org}$ OR m.org_id='' OR m.org_id='0')"
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params['org'] = org_id
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if caps:
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# sqlor 的 IN 列表必须展开占位符（传 list 会崩）：${c0}$,${c1}$,...
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ph = []
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for i, c in enumerate(caps):
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k = 'c%d' % i
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ph.append('${%s}$' % k)
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params[k] = c
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sql += (" AND COALESCE(NULLIF(m.capability,''),'t2t') IN (%s)"
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% ','.join(ph))
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sql += " ORDER BY m.name"
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recs = await sor.sqlExe(sql, params)
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# 项目已设模型（按会话解析当前项目）
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project_model = ''
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if uid:
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try:
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from pipeline_service.workspace import get_session_project_id
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_pid = await get_session_project_id(
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sor, uid, session_id or '', pipeline_id or '')
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if _pid:
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_p = await sor.sqlExe(
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"SELECT default_model FROM sd_projects WHERE id=${p}$", {"p": _pid})
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await sor.sqlExe("COMMIT", {})
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if _p:
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project_model = getattr(_p[0], 'default_model', '') or ''
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except Exception as e:
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logger.debug("model_options 项目模型解析跳过: %s", e)
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# 个人全局默认选择
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current_llm_id = ''
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if uid:
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try:
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_s = await sor.sqlExe(
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"SELECT default_llm_id FROM pipeline_agent_settings WHERE user_id=${u}$",
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{"u": uid})
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if _s:
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current_llm_id = getattr(_s[0], 'default_llm_id', '') or ''
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except Exception:
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pass
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for r in (recs or []):
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vname = getattr(r, 'vendor_name', '') or ''
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rows.append({
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'value': r.id if value_field != 'name' else r.name,
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'text': r.name + (' (' + vname + ')' if vname else ''),
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'provider': vname,
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'model_id': r.id,
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'model_id_text': r.name,
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'capabilities': getattr(r, 'capability', '') or 't2t',
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'selected': ((r.name == project_model) if project_model
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else (r.id == current_llm_id)),
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})
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return rows
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async def resolve_model_name(model_ref, org_id='', capabilities=()):
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"""模型引用解析的唯一入口：id / vendor_model_id / name → 模型注册名。
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机构隔离：非系统级机构只能解析「本机构 + 系统级共享」模型。
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capabilities: 能力白名单（'chat' 哨兵 / tuple），非空时能力不符也解析失败
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（会话 agent 个人默认模型/角色模型入口传 'chat'，防把 embedding 等非对话
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模型持久化成会话模型）。
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解析不到返回 ''（调用方决定回退/报错，禁止自行另查表）。
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"""
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if not model_ref:
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return ''
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caps = _norm_caps(capabilities)
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db, dbname = _get_sor()
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async with db.sqlorContext(dbname) as sor:
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recs = await sor.sqlExe(
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"SELECT name, org_id, capability FROM llm_model WHERE status='active' "
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"AND (id=${m}$ OR vendor_model_id=${m}$ OR name=${m}$) LIMIT 1",
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{"m": model_ref})
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await sor.sqlExe("COMMIT", {})
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if not recs:
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return ''
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m_org = getattr(recs[0], 'org_id', '') or ''
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if org_id and org_id != '0' and m_org not in ('', '0', org_id):
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logger.warning("resolve_model_name: 模型 %s 不属于机构 %s", model_ref, org_id)
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return ''
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if caps:
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cap = (getattr(recs[0], 'capability', '') or 't2t').strip().lower()
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if cap not in caps:
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logger.warning("resolve_model_name: 模型 %s 能力 %s 不在白名单 %s",
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model_ref, cap, caps)
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return ''
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return getattr(recs[0], 'name', '') or ''
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async def org_available_models(org_id, capability=''):
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"""机构可用模型注册名列表（本机构 + 系统级共享）。空 = 机构未配置模型。"""
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db, dbname = _get_sor()
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async with db.sqlorContext(dbname) as sor:
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sql = "SELECT name, capability FROM llm_model WHERE status='active'"
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params = {}
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if org_id and org_id != '0':
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sql += " AND (org_id=${org}$ OR org_id='' OR org_id='0')"
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params['org'] = org_id
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if capability:
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sql += " AND capability=${c}$"
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params['c'] = capability
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recs = await sor.sqlExe(sql, params)
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await sor.sqlExe("COMMIT", {})
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return [getattr(r, 'name', '') or '' for r in (recs or [])]
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def load_selection():
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"""注册到 ServerEnv（供各模块 dspy 薄壳调用）。"""
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env = ServerEnv()
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env.llm_model_options = model_options
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env.llm_resolve_model_name = resolve_model_name
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env.llm_org_available_models = org_available_models
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logger.info("[pipeline_llm] selection loaded")
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