ai-agents-chat-engine-empty-re-when-condensepluscontextchatengine-retrieves-zero--80835c19

THEN Modify the chat engine to not short-circuit on empty retrieval. Instead, pass an empty context to the LLM and let it generate a response based on its training and system prompt, or use a default context. Override the `chat` method to check for empty nodes and still invoke the LLM with a fallback context.

class CustomCondensePlusContextChatEngine(CondensePlusContextChatEngine):
    def chat(self, message: str) -> AgentChatResponse:
        nodes = self._retrieve(message)
        if not nodes:
            # Fallback: let LLM respond without context
            return self.llm.chat([ChatMessage(role=USER, content=message)])
        return super().chat(message)