| import logging |
|
|
| from langchain.chat_models import BaseChatModel |
|
|
| from src.config import get_app_config, get_tracing_config, is_tracing_enabled |
| from src.reflection import resolve_class |
|
|
| logger = logging.getLogger(__name__) |
|
|
|
|
| def create_chat_model(name: str | None = None, thinking_enabled: bool = False, **kwargs) -> BaseChatModel: |
| """Create a chat model instance from the config. |
| |
| Args: |
| name: The name of the model to create. If None, the first model in the config will be used. |
| |
| Returns: |
| A chat model instance. |
| """ |
| config = get_app_config() |
| if name is None: |
| name = config.models[0].name |
| model_config = config.get_model_config(name) |
| if model_config is None: |
| raise ValueError(f"Model {name} not found in config") from None |
| model_class = resolve_class(model_config.use, BaseChatModel) |
| model_settings_from_config = model_config.model_dump( |
| exclude_none=True, |
| exclude={ |
| "use", |
| "name", |
| "display_name", |
| "description", |
| "supports_thinking", |
| "when_thinking_enabled", |
| "supports_vision", |
| }, |
| ) |
| if thinking_enabled and model_config.when_thinking_enabled is not None: |
| if not model_config.supports_thinking: |
| raise ValueError(f"Model {name} does not support thinking. Set `supports_thinking` to true in the `config.yaml` to enable thinking.") from None |
| model_settings_from_config.update(model_config.when_thinking_enabled) |
| model_instance = model_class(**kwargs, **model_settings_from_config) |
|
|
| if is_tracing_enabled(): |
| try: |
| from langchain_core.tracers.langchain import LangChainTracer |
|
|
| tracing_config = get_tracing_config() |
| tracer = LangChainTracer( |
| project_name=tracing_config.project, |
| ) |
| existing_callbacks = model_instance.callbacks or [] |
| model_instance.callbacks = [*existing_callbacks, tracer] |
| logger.debug(f"LangSmith tracing attached to model '{name}' (project='{tracing_config.project}')") |
| except Exception as e: |
| logger.warning(f"Failed to attach LangSmith tracing to model '{name}': {e}") |
| return model_instance |
|
|
