Accelerate answering

import APITable from '@site/src/components/APITable';

A checklist to speed up question answering for your chat assistant.

Please note that some of your settings may consume a significant amount of time. If you often find that your question answering is time-consuming, here is a checklist to consider:

Disabling Multi-turn optimization will reduce the time required to get an answer from the LLM.
Leaving the Rerank model field empty will significantly decrease retrieval time.
Disabling the Reasoning toggle will reduce the LLM's thinking time. For a model like Qwen3, you also need to add /no_think to the system prompt to disable reasoning.
When using a rerank model, ensure you have a GPU for acceleration; otherwise, the reranking process will be prohibitively slow.

:::tip NOTE Please note that rerank models are essential in certain scenarios. There is always a trade-off between speed and performance; you must weigh the pros against cons for your specific case. :::

Disabling Keyword analysis will reduce the time to receive an answer from the LLM.
When chatting with your chat assistant, click the light bulb icon above the current dialogue and scroll down the popup window to view the time taken for each task:

mdx-code-block

<APITable>

Item name	Description
Total	Total time spent on this conversation round, including chunk retrieval and answer generation.
Check LLM	Time to validate the specified LLM.
Create retriever	Time to create a chunk retriever.
Bind embedding	Time to initialize an embedding model instance.
Bind LLM	Time to initialize an LLM instance.
Tune question	Time to optimize the user query using the context of the multi-turn conversation.
Bind reranker	Time to initialize an reranker model instance for chunk retrieval.
Generate keywords	Time to extract keywords from the user query.
Retrieval	Time to retrieve the chunks.
Generate answer	Time to generate the answer.

mdx-code-block

</APITable>