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chore: import upstream snapshot with attribution
2026-07-13 13:28:29 +08:00

38 lines
1.3 KiB
Python

from __future__ import annotations
from typing import Optional
from application.llm.openai import OpenAILLM
from application.llm.providers.base import Provider
class OpenAIProvider(Provider):
name = "openai"
llm_class = OpenAILLM
def get_api_key(self, settings) -> Optional[str]:
if settings.OPENAI_API_KEY:
return settings.OPENAI_API_KEY
if settings.LLM_PROVIDER == self.name and settings.API_KEY:
return settings.API_KEY
return None
def is_enabled(self, settings) -> bool:
# When the deployment is pointed at a custom OpenAI-compatible
# endpoint (Ollama, LM Studio, ...), the cloud-OpenAI catalog is
# suppressed but ``is_enabled`` stays True — necessary so the
# filter below still gets to drop the catalog (rather than the
# registry skipping the provider entirely and missing the rule).
if settings.OPENAI_BASE_URL:
return True
return bool(self.get_api_key(settings))
def filter_yaml_models(self, settings, models):
# Legacy local-endpoint mode hides the cloud catalog. The
# corresponding dynamic models live in OpenAICompatibleProvider.
if settings.OPENAI_BASE_URL:
return []
if not settings.OPENAI_API_KEY:
return []
return models