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AI search vs. chat (#6569)

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### What problem does this PR solve?


### Type of change

- [x] Documentation Update
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docs/faq.md → docs/faq.mdx
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@ -9,6 +9,10 @@ Answers to questions about general features, troubleshooting, usage, and more.
---
import TOCInline from '@theme/TOCInline';
<TOCInline toc={toc} />
## General features
---
@ -120,6 +124,13 @@ Yes, we support enhancing user queries based on existing context of an ongoing c
---
### Key differences between AI search and chat?
- **AI search**: This is a single-turn AI conversation using a predefined retrieval strategy (a hybrid search of weighted keyword similarity and weighted vector similarity) and the system's default chat model. It does not involve advanced RAG strategies like knowledge graph, auto-keyword, or auto-question. Retrieved chunks will be listed below the chat model's response.
- **AI chat**: This is a multi-turn AI conversation where you can define your retrieval strategy (a weighted reranking score can be used to replace the weighted vector similarity in a hybrid search) and choose your chat model. In an AI chat, you can configure advanced RAG strategies, such as knowledge graphs, auto-keyword, and auto-question, for your specific case. Retrieved chunks are not displayed along with the answer.
When debugging your chat assistant, you can use AI search as a reference to verify your model settings and retrieval strategy.
## Troubleshooting
---

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docs/guides/agent/agent_component_reference/generate.mdx
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@ -24,7 +24,7 @@ Click the dropdown menu of **Model** to show the model configuration window.
- **Model**: The chat model to use.
- Ensure you set the chat model correctly on the **Model providers** page.
- You can use different models for different components to increase flexibility or improve overall performance.
- **Preset configurations**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.
- **Freedom**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.
This parameter has three options:
- **Improvise**: Produces more creative responses.
- **Precise**: (Default) Produces more conservative responses.
@ -43,9 +43,6 @@ Click the dropdown menu of **Model** to show the model configuration window.
- **Frequency penalty**: Discourages the model from repeating the same words or phrases too frequently in the generated text.
- A higher **frequency penalty** value results in the model being more conservative in its use of repeated tokens.
- Defaults to 0.7.
- **Max tokens**: Sets the maximum length of the model's output, measured in the number of tokens.
- Defaults to 512.
- If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses.
:::tip NOTE
- It is not necessary to stick with the same model for all components. If a specific model is not performing well for a particular task, consider using a different one.

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docs/quickstart.mdx
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@ -302,8 +302,8 @@ Once you have selected an embedding model and used it to parse a file, you are n
_When the file parsing completes, its parsing status changes to **SUCCESS**._
:::caution NOTE
- If your file parsing gets stuck at below 1%, see [this FAQ](https://ragflow.io/docs/dev/faq#why-does-my-document-parsing-stall-at-under-one-percent).
- If your file parsing gets stuck at near completion, see [this FAQ](https://ragflow.io/docs/dev/faq#why-does-my-pdf-parsing-stall-near-completion-while-the-log-does-not-show-any-error)
- If your file parsing gets stuck at below 1%, see [this FAQ](./faq.mdxfaq#why-does-my-document-parsing-stall-at-under-one-percent).
- If your file parsing gets stuck at near completion, see [this FAQ](./faq.mdx#why-does-my-pdf-parsing-stall-near-completion-while-the-log-does-not-show-any-error)
:::
## Intervene with file parsing