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https://github.com/NousResearch/hermes-agent.git
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221cd60242
Map Hermes xhigh→max to unlock DeepSeek V4's 'Max thinking' tier through Ollama Cloud's OpenAI-compatible /v1/chat/completions endpoint. low/medium/high pass through unchanged; disabled/none suppress reasoning entirely. Empirically confirmed: reasoning_effort:max produces ~2.5× more thinking tokens than high on deepseek-v4-pro:cloud (1576 vs 642).
73 lines
2.5 KiB
Python
73 lines
2.5 KiB
Python
"""Ollama Cloud provider profile.
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Ollama Cloud's OpenAI-compatible ``/v1/chat/completions`` endpoint
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supports top-level ``reasoning_effort`` with values ``none``, ``low``,
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``medium``, ``high``, and ``max`` (the last being undocumented but
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empirically confirmed for DeepSeek V4 — ``max`` produces ~2.5× more
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thinking tokens than ``high``).
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This profile maps Hermes's ``xhigh`` → ``max`` to unlock DeepSeek V4's
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"Max thinking" tier through Ollama Cloud. ``low`` / ``medium`` / ``high``
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pass through unchanged.
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When reasoning is explicitly disabled (``enabled: false`` or
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``effort: "none"``), ``reasoning_effort`` is omitted entirely so the
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model runs in non-thinking mode.
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"""
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from __future__ import annotations
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from typing import Any
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from providers import register_provider
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from providers.base import ProviderProfile
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class OllamaCloudProfile(ProviderProfile):
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"""Ollama Cloud — maps xhigh→max via top-level reasoning_effort."""
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def build_api_kwargs_extras(
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self,
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*,
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reasoning_config: dict | None = None,
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**ctx: Any,
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) -> tuple[dict[str, Any], dict[str, Any]]:
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"""Emit top-level ``reasoning_effort`` for Ollama Cloud.
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The ``supports_reasoning`` flag passed by the transport is
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deliberately ignored — this profile always handles reasoning
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when ``reasoning_config`` is present.
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"""
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top_level: dict[str, Any] = {}
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if reasoning_config and isinstance(reasoning_config, dict):
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enabled = reasoning_config.get("enabled", True)
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if enabled is False:
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return {}, {} # omit → model runs without thinking
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effort = (reasoning_config.get("effort") or "").strip().lower()
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if not effort:
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# No explicit effort requested — let the model decide
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return {}, {}
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if effort == "none":
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return {}, {} # explicit none → suppress thinking
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if effort in ("xhigh", "max"):
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top_level["reasoning_effort"] = "max"
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elif effort in ("low", "medium", "high"):
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top_level["reasoning_effort"] = effort
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else:
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# Unknown value — forward as-is, let the API decide
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top_level["reasoning_effort"] = effort
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return {}, top_level
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ollama_cloud = OllamaCloudProfile(
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name="ollama-cloud",
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aliases=("ollama_cloud",),
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default_aux_model="nemotron-3-nano:30b",
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env_vars=("OLLAMA_API_KEY",),
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base_url="https://ollama.com/v1",
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)
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register_provider(ollama_cloud)
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