Multi-Turn Conversation
In multi-turn dialogue, the ability of a model to receive new user input while it is still generating a reply. This involves coordinating streaming generation with a message queue, and the degree of API support varies across model vendors. It determines whether a user can interrupt, redirect, or supplement an in-progress response, and how such interleaved input is buffered and ordered.
Core Facts
Timeline (last 90 days)
Multi-turn conversation configuration addresses the context memory problem, determining how many rounds of historical information an agent can retain during continuous dialogue.
The difference between single-turn and multi-turn dialogue lies in context memory and state management; overcoming the limitations typically requires maintaining conversation history on the server side and introducing a tool-calling mechanism.
Evaluating the overall quality of a multi-turn conversational workflow of an Agent is more complex than evaluating a single response.
All Facts (4)
Multi-turn conversation configuration addresses the context memory problem, determining how many rounds of historical information an agent can retain during continuous dialogue.
75%UnverifiedMulti-turn dialogue is implemented by re-inputting all previous conversation history to the model with each request, rather than the model having genuine memory capability.
60%UnverifiedThe difference between single-turn and multi-turn dialogue lies in context memory and state management; overcoming the limitations typically requires maintaining conversation history on the server side and introducing a tool-calling mechanism.
50%UnverifiedEvaluating the overall quality of a multi-turn conversational workflow of an Agent is more complex than evaluating a single response.
50%