Yes, you can use OpenAI’s models for multi-turn conversations. These models are designed to handle context across multiple interactions, making them suitable for chat applications, customer support bots, and interactive systems. Multi-turn conversation involves maintaining context from one user input to the next, allowing the model to understand and respond appropriately based on the previous exchanges.
To implement multi-turn conversations effectively, you need to manage the context during the interaction. This can be done by keeping track of previous messages in the conversation and including them as part of the input for each new request to the model. For example, if a user asks about a product and then follows up with a question regarding its features, you would send the entire conversation history (or a relevant subset) to the model for context. This way, the model can generate responses that feel more coherent and relevant to the ongoing discussion.
However, it's essential to be mindful of token limits and manage the amount of conversation history you include. OpenAI’s models have a maximum token limit for each request, which includes both the input and the model's output. If the conversation history becomes too long, you'll need to truncate it or summarize previous exchanges to stay within this limit. By doing this, you can maintain a quality interaction while efficiently using the model's capabilities for multi-turn conversations.