Function _call_llm_via_litellm

codewiki/src/be/llm_services.py:228–258

Call LLM via litellm for Bedrock/Anthropic providers. litellm handles the provider-specific API translation automatically.

(
    prompt: str,
    config: Config,
    model: str,
    temperature: float = 0.0
)

    # litellm exposes an OpenAI-compatible Router we can use,
    # but the simplest path is to use litellm.completion() directly.
    # For pydantic-ai integration, we create a proxy client.
    return OpenAI(
        api_key=config.llm_api_key or "not-needed-for-bedrock",
        base_url=config.llm_base_url or "https://api.openai.com/v1",
    )


def create_main_model(config: Config) -> CachingOpenAIModel:
    """Create the main LLM model from configuration."""
    return CachingOpenAIModel(
        model_name=config.main_model,
        prompt_caching=config.prompt_caching,
        cache_registry_key=config.llm_base_url or "",
        provider=OpenAIProvider(base_url=config.llm_base_url, api_key=config.llm_api_key),
        settings=_build_model_settings(config, config.main_model),
    )


def create_fallback_model(config: Config) -> CachingOpenAIModel:
    """Create the fallback LLM model from configuration."""
    return CachingOpenAIModel(
        model_name=config.fallback_model,
        prompt_caching=config.prompt_caching,
        cache_registry_key=config.llm_base_url or "",
        provider=OpenAIProvider(base_url=config.llm_base_url, api_key=config.llm_api_key),
        settings=_build_model_settings(config, config.fallback_model),
    )


def create_fallback_models(config: Config) -> FallbackModel:
    """Create fallback models chain from configuration."""
    main = create_main_model(config)
    fallback = create_fallback_model(config)