Teknium
77743eac8a
- usage_pricing: _snap() builder for official-docs pricing entries (table values identical, verified by dump), shared source/version dicts, drop dead DEFAULT_PRICING - models_dev: _registry_models/_iter_model_entries/_extract_limit helpers replace repeated registry walking; drop dead ModelInfo.format_cost - billing_view/subscription_view: OrgRoleCapability mixin replaces duplicated is_admin/can_change_plan; shared fetch_portal_state/parse_org_fields - reasoning_effort/timeouts/summaries, thinking_timeout_guidance, portal_tags: dispatch tables and compacted comment essays; drop dead CODEX_RESPONSES_EFFORTS alias and _match_any
54 lines
2.3 KiB
Python
54 lines
2.3 KiB
Python
"""LM Studio reasoning-effort resolution shared by the chat-completions
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transport and run_agent's iteration-limit summary path.
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LM Studio publishes per-model ``capabilities.reasoning.allowed_options``
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(``["off","on"]`` for toggle models, ``["off","minimal","low"]`` for graduated
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ones). We map the user's ``reasoning_config`` onto LM Studio's OpenAI-compatible
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vocabulary, then clamp against the model's allowed set so the server doesn't 400.
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"""
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from __future__ import annotations
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from typing import List, Optional
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# Top-level reasoning_effort values LM Studio's OpenAI-compatible endpoint accepts.
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_LM_VALID_EFFORTS = {"none", "minimal", "low", "medium", "high", "xhigh"}
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# Toggle-style models publish allowed_options as ["off","on"]; map onto the
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# request vocabulary. Also applied to the published allowed_options themselves.
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_LM_EFFORT_ALIASES = {"off": "none", "on": "medium"}
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# Hermes' ladder grew past LM Studio's vocabulary ("max", "ultra"). Without this
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# ceiling clamp they miss _LM_VALID_EFFORTS, keep the "medium" default and are
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# conflated with unparseable input — asking for more yields less than "xhigh".
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# Kept separate from _LM_EFFORT_ALIASES, which must not rewrite allowed_options.
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_LM_EFFORT_CLAMP = {"max": "xhigh", "ultra": "xhigh"}
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def resolve_lmstudio_effort(
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reasoning_config: Optional[dict],
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allowed_options: Optional[List[str]],
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) -> Optional[str]:
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"""Return the ``reasoning_effort`` to send to LM Studio, or ``None``.
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``None`` means "omit the field": the user picked a level the model can't
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honor, so LM Studio falls back to the model's declared default rather than
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a silently substituted effort. Falsy ``allowed_options`` (probe failed)
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skips clamping and sends the resolved effort anyway.
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"""
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effort = "medium"
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if reasoning_config and isinstance(reasoning_config, dict):
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if reasoning_config.get("enabled") is False:
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effort = "none"
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else:
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raw = (reasoning_config.get("effort") or "").strip().lower()
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raw = _LM_EFFORT_ALIASES.get(raw, raw)
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raw = _LM_EFFORT_CLAMP.get(raw, raw)
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if raw in _LM_VALID_EFFORTS:
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effort = raw
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if allowed_options:
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allowed = {_LM_EFFORT_ALIASES.get(opt, opt) for opt in allowed_options}
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if effort not in allowed:
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return None
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return effort
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