ragflow/docs/guides/chat/accelerate_question_answering.mdx

---
sidebar_position: 2
slug: /accelerate_question_answering
---

# Accelerate answering
import APITable from '@site/src/components/APITable';

A checklist to speed up question answering.

---

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:

- In the **Prompt Engine** tab of your **Chat Configuration** dialogue, disabling **Multi-turn optimization** will reduce the time required to get an answer from the LLM.
- In the **Prompt Engine** tab of your **Chat Configuration** dialogue, leaving the **Rerank model** field empty will significantly decrease retrieval time.
- 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.
:::

- In the **Assistant settings** tab of your **Chat Configuration** dialogue, 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:  
   ![enlighten](https://github.com/user-attachments/assets/fedfa2ee-21a7-451b-be66-20125619923c)  


```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 mult-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>
```