LLM

To build conversational AI with large language model chat completions, you use a skill that processes user inputs, manages multi-turn conversations, and applies system prompts. This requires product-factory-sdk for backend integration to handle context state and generate responses.

Context management for multi-turn conversations maintains conversation state across multiple user interactions. The system uses previous dialogue history and system prompts to generate coherent responses, ensuring the AI assistant remembers prior context within the active session.

Yes, you need product-factory-sdk to generate text for AI assistants. It provides the required backend implementation and integration framework to process large language model chat completions and handle multi-turn conversational logic.

Yes, you can use system prompts to control large language model behavior. System prompts enable custom behavior configuration for conversational AI applications, allowing you to define specific roles, constraints, and response styles for your chatbot or AI assistant.

The best way to handle multi-turn dialogues in text generation systems is leveraging a framework with built-in context management. This approach maintains conversation state across interactions, applying system prompts to ensure coherent and contextually relevant responses throughout the chat.