RandomZ / app /llm /generation_facade.py
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"""Unified async entry points for section generation LLM calls.
Callers in async handlers should use these helpers instead of branching on
``enable_async_pipeline`` at every call site.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from app.async_executor import run_sync_in_executor
from app.config import settings
from app.generator.adapter import get_llm_adapter
from app.llm.async_llm_adapter import get_async_llm_adapter
if TYPE_CHECKING:
from app.models.schemas import WritingStyleProfile
async def generate_section(
*,
skeleton: str,
bullets: list[str],
snippets: list[str],
style_profile: "WritingStyleProfile | None" = None,
temperature: float = 0.2,
creativity_hint: str = "",
document_context: list[str] | None = None,
style_anchor: str | None = None,
hierarchy_section_snippets: list[str] | None = None,
paragraph_snippets: list[str] | None = None,
identity_facts: str | None = None,
survey_level: int | None = None,
reference_only_context: bool = False,
ai_percent: int | None = None,
interference_level: str | None = None,
tenant_id: str | None = None,
) -> str:
if settings.enable_async_pipeline:
return await get_async_llm_adapter().generate_section(
skeleton=skeleton,
bullets=bullets,
snippets=snippets,
style_profile=style_profile,
temperature=temperature,
creativity_hint=creativity_hint,
document_context=document_context,
style_anchor=style_anchor,
hierarchy_section_snippets=hierarchy_section_snippets,
paragraph_snippets=paragraph_snippets,
identity_facts=identity_facts,
survey_level=survey_level,
reference_only_context=reference_only_context,
ai_percent=ai_percent,
interference_level=interference_level,
tenant_id=tenant_id,
)
return await run_sync_in_executor(
get_llm_adapter().generate_section,
skeleton=skeleton,
bullets=bullets,
snippets=snippets,
style_profile=style_profile,
temperature=temperature,
creativity_hint=creativity_hint,
document_context=document_context,
style_anchor=style_anchor,
hierarchy_section_snippets=hierarchy_section_snippets,
paragraph_snippets=paragraph_snippets,
identity_facts=identity_facts,
survey_level=survey_level,
reference_only_context=reference_only_context,
ai_percent=ai_percent,
interference_level=interference_level,
tenant_id=tenant_id,
)
async def proofread(
*,
text: str,
bullets: list[str],
style_profile: "WritingStyleProfile | None" = None,
temperature: float = 0.15,
creativity_hint: str = "",
) -> str:
if settings.enable_async_pipeline:
return await get_async_llm_adapter().proofread(
text=text,
bullets=bullets,
style_profile=style_profile,
temperature=temperature,
creativity_hint=creativity_hint,
)
return await run_sync_in_executor(
get_llm_adapter().proofread,
text=text,
bullets=bullets,
style_profile=style_profile,
temperature=temperature,
creativity_hint=creativity_hint,
)
async def enhance(
*,
text: str,
bullets: list[str],
snippets: list[str],
style_profile: "WritingStyleProfile | None" = None,
temperature: float = 0.2,
creativity_hint: str = "",
) -> str:
if settings.enable_async_pipeline:
return await get_async_llm_adapter().enhance(
text=text,
bullets=bullets,
snippets=snippets,
style_profile=style_profile,
temperature=temperature,
creativity_hint=creativity_hint,
)
return await run_sync_in_executor(
get_llm_adapter().enhance,
text=text,
bullets=bullets,
snippets=snippets,
style_profile=style_profile,
temperature=temperature,
creativity_hint=creativity_hint,
)
async def validate_section_compliance(
*,
survey_level: int | None,
section_code: str,
bullets: list[str],
evidence_snippets: list[str],
text: str,
) -> str:
if settings.enable_async_pipeline:
return await get_async_llm_adapter().validate_section_compliance(
survey_level=survey_level,
section_code=section_code,
bullets=bullets,
evidence_snippets=evidence_snippets,
text=text,
)
return await run_sync_in_executor(
get_llm_adapter().validate_section_compliance,
survey_level=survey_level,
section_code=section_code,
bullets=bullets,
evidence_snippets=evidence_snippets,
text=text,
)
async def constrained_weave(
*,
section_code: str,
section_title: str | None,
bullets: list[str],
standard_passages: list[str],
survey_level: int | None = None,
tenant_id: str | None = None,
) -> str:
if settings.enable_async_pipeline:
return await get_async_llm_adapter().constrained_weave(
section_code=section_code,
section_title=section_title,
bullets=bullets,
standard_passages=standard_passages,
survey_level=survey_level,
tenant_id=tenant_id,
)
return await run_sync_in_executor(
get_llm_adapter().constrained_weave,
section_code=section_code,
section_title=section_title,
bullets=bullets,
standard_passages=standard_passages,
survey_level=survey_level,
tenant_id=tenant_id,
)