feat: implement mvp with email-first login flow and langgraph architecture

src/ea_chatbot/utils/llm_factory.py

@@ -0,0 +1,36 @@
+from typing import Optional, cast, TYPE_CHECKING, Literal, Dict, List, Tuple, Any
+from langchain_core.language_models.chat_models import BaseChatModel
+from langchain_openai import ChatOpenAI
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_core.callbacks import BaseCallbackHandler
+from ea_chatbot.config import LLMConfig
+
+def get_llm_model(config: LLMConfig, callbacks: Optional[List[BaseCallbackHandler]] = None) -> BaseChatModel:
+    """
+    Factory function to get a LangChain chat model based on configuration.
+    
+    Args:
+        config: LLMConfig object containing model settings.
+        callbacks: Optional list of LangChain callback handlers.
+        
+    Returns:
+        Initialized BaseChatModel instance.
+        
+    Raises:
+        ValueError: If the provider is not supported.
+    """
+    params = {
+        "temperature": config.temperature,
+        "max_tokens": config.max_tokens,
+        **config.provider_specific
+    }
+    
+    # Filter out None values to allow defaults to take over if not specified
+    params = {k: v for k, v in params.items() if v is not None}
+
+    if config.provider.lower() == "openai":
+        return ChatOpenAI(model=config.model, callbacks=callbacks, **params)
+    elif config.provider.lower() == "google" or config.provider.lower() == "google_genai":
+        return ChatGoogleGenerativeAI(model=config.model, callbacks=callbacks, **params)
+    else:
+        raise ValueError(f"Unsupported LLM provider: {config.provider}")