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55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
"""Runtime helpers for request-scoped model selection."""
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from __future__ import annotations
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from contextvars import Token
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from typing import Any
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from deeptutor.services.config.provider_runtime import ResolvedLLMConfig, resolve_llm_runtime_config
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from deeptutor.services.llm import config as llm_config_module
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from deeptutor.services.llm.config import LLMConfig
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def llm_config_from_resolved(resolved: ResolvedLLMConfig) -> LLMConfig:
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"""Convert provider-runtime output into the LLM service config shape."""
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return LLMConfig(
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model=resolved.model,
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api_key=resolved.api_key,
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base_url=resolved.base_url,
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effective_url=resolved.effective_url,
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binding=resolved.binding,
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provider_name=resolved.provider_name,
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provider_mode=resolved.provider_mode,
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api_version=resolved.api_version,
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extra_headers=resolved.extra_headers,
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reasoning_effort=resolved.reasoning_effort,
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context_window=resolved.context_window,
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)
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def resolve_llm_config_for_selection(selection: Any) -> LLMConfig:
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"""Resolve the LLM config for a chat/session selection reference."""
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if selection is None:
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return llm_config_module.get_llm_config()
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return llm_config_from_resolved(resolve_llm_runtime_config(llm_selection=selection))
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def activate_llm_selection(selection: Any) -> tuple[LLMConfig, Token[LLMConfig | None]]:
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"""Resolve and install a scoped LLM config for the current async context."""
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config = resolve_llm_config_for_selection(selection)
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token = llm_config_module.set_scoped_llm_config(config)
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return config, token
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def reset_llm_selection(token: Token[LLMConfig | None] | None) -> None:
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if token is not None:
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llm_config_module.reset_scoped_llm_config(token)
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__all__ = [
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"activate_llm_selection",
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"llm_config_from_resolved",
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"reset_llm_selection",
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"resolve_llm_config_for_selection",
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]
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