LLM/llm_models.py

from .models import LLMProviderType, LLMModelType
from .llm_provider import LLMProvider


use_gemini = True

base_provider = LLMProviderType.GEMINI if use_gemini else LLMProviderType.HF

base_model = LLMModelType.gemini.gemini_2_5_pro if use_gemini else LLMModelType.open_source.deepseek_v3_terminus



orchestrator_model = LLMProvider(base_provider, base_model).get_model()

supabase_model = LLMProvider(base_provider, base_model).get_model()
websearch_model = LLMProvider(base_provider, base_model).get_model()

# CV analyzer uses the same HF/opensource model as orchestrator
cv_analyzer_model = LLMProvider(base_provider, base_model).get_model()

context_compression_model = LLMProvider(LLMProviderType.OPENAI, LLMModelType.openai.gpt_5_1).get_model()
metaprompting_model = LLMProvider(LLMProviderType.OPENAI, LLMModelType.openai.gpt_5_1).get_model()

prompt_structure_model = LLMProvider(base_provider, base_model).get_model()