File size: 2,258 Bytes
033ca06 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | 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
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