Customization

from langchat.adapters.services.openai_service import OpenAILLMService

class CustomLLMAdapter(OpenAILLMService):
    def invoke(self, messages, **kwargs):
        # Custom logic here
        return super().invoke(messages, **kwargs)

from langchat.adapters.vector_db.pinecone_adapter import PineconeVectorAdapter

class CustomVectorAdapter(PineconeVectorAdapter):
    def get_retriever(self, k=5):
        # Custom retrieval logic
        return super().get_retriever(k=k)

from langchat.core.session import UserSession

class CustomSession(UserSession):
    def save_message(self, query: str, response: str) -> None:
        # Custom save logic
        super().save_message(query, response)