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773a0faca0
Closes #26924 (and supersedes #26926) in spirit. DeepSeek was missing `default_aux_model` on its `ProviderProfile`, so `_get_aux_model_for_provider("deepseek")` returned an empty string and the compression / vision / session-search paths emitted "No auxiliary LLM provider configured -- context compression will drop middle turns without a summary." on every DeepSeek session, even when the user had perfectly working DeepSeek credentials. Fix lands at the profile layer rather than the legacy `_API_KEY_PROVIDER_AUX_MODELS_FALLBACK` dict the original PR targeted. Every modern provider (gemini, zai, minimax, anthropic, kimi-coding, stepfun, ollama-cloud, gmi, novita, kilocode, ai-gateway, opencode-zen) sets `default_aux_model` on its `ProviderProfile`; the fallback dict only exists for providers that predate the profiles system. Tests added under `tests/plugins/model_providers/test_deepseek_profile.py`: - `test_profile_advertises_deepseek_chat` -- pins the profile attribute - `test_consumer_api_returns_deepseek_chat` -- pins the consumer API behavior - `test_consumer_api_returns_non_empty` -- regression guard for the symptom in the issue Original diagnosis and aux-model choice from @kriscolab in PR #26926; moved one layer up. Co-authored-by: kriscolab <71590782+kriscolab@users.noreply.github.com>
100 lines
3.6 KiB
Python
100 lines
3.6 KiB
Python
"""DeepSeek provider profile.
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DeepSeek's V4 family (and the legacy ``deepseek-reasoner``) defaults to
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thinking-mode ON when ``extra_body.thinking`` is unset. The API then returns
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``reasoning_content`` and starts enforcing the contract that subsequent turns
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echo it back; combined with how Hermes replays history this lands on the
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notorious HTTP 400 ``reasoning_content must be passed back`` error after the
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first tool call (#15700, #17212, #17825).
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This profile overrides :meth:`build_api_kwargs_extras` to mirror the Kimi /
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Moonshot wire shape that DeepSeek's OpenAI-compat endpoint expects:
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{"reasoning_effort": "<low|medium|high|max>",
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"extra_body": {"thinking": {"type": "enabled" | "disabled"}}}
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Non-thinking models (only ``deepseek-chat`` today, which is V3) are left as
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no-ops so we don't perturb the V3 wire format.
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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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def _model_supports_thinking(model: str | None) -> bool:
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"""DeepSeek thinking-capable model families.
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Currently covers the V4 family (``deepseek-v4-pro``, ``deepseek-v4-flash``,
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and any future ``deepseek-v4-*`` variants) and the legacy
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``deepseek-reasoner`` (R1). ``deepseek-chat`` is V3 with no thinking mode.
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"""
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m = (model or "").strip().lower()
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if not m:
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return False
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if m.startswith("deepseek-v") and not m.startswith("deepseek-v3"):
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# deepseek-v4-*, deepseek-v5-*, etc. — every V4+ generation has
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# thinking. v3 explicitly excluded.
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return True
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if m == "deepseek-reasoner":
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return True
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return False
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class DeepSeekProfile(ProviderProfile):
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"""DeepSeek — extra_body.thinking + top-level reasoning_effort."""
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def build_api_kwargs_extras(
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self, *, reasoning_config: dict | None = None, model: str | None = None, **context
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) -> tuple[dict[str, Any], dict[str, Any]]:
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extra_body: dict[str, Any] = {}
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top_level: dict[str, Any] = {}
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if not _model_supports_thinking(model):
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# V3 / unknown — leave wire format untouched, current behavior.
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return extra_body, top_level
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# Determine enabled/disabled. Default is enabled to match DeepSeek's
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# API default; the API requires this to be set explicitly to avoid the
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# reasoning_content echo trap on subsequent turns.
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enabled = True
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if isinstance(reasoning_config, dict) and reasoning_config.get("enabled") is False:
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enabled = False
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extra_body["thinking"] = {"type": "enabled" if enabled else "disabled"}
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if not enabled:
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return extra_body, top_level
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# Effort mapping. Pass low/medium/high through; xhigh/max → max.
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# When no effort is set we omit reasoning_effort so DeepSeek applies
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# its server default (currently high).
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if isinstance(reasoning_config, dict):
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effort = (reasoning_config.get("effort") or "").strip().lower()
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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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return extra_body, top_level
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deepseek = DeepSeekProfile(
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name="deepseek",
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aliases=("deepseek-chat",),
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env_vars=("DEEPSEEK_API_KEY",),
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display_name="DeepSeek",
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description="DeepSeek — native DeepSeek API",
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signup_url="https://platform.deepseek.com/",
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fallback_models=(
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"deepseek-chat",
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"deepseek-reasoner",
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),
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base_url="https://api.deepseek.com/v1",
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default_aux_model="deepseek-chat",
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)
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register_provider(deepseek)
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