Updated outdated descriptions and added multi-turn optimization (#4362)

### What problem does this PR solve?

_Briefly describe what this PR aims to solve. Include background context
that will help reviewers understand the purpose of the PR._

### Type of change

- [x] Documentation Update

docs/guides/start_chat.md

@@ -5,6 +5,10 @@ slug: /start_chat
 
 # Start an AI-powered chat
 
+Initiate a chat with a configured chat assistant.
+
+---
+
 Knowledge base, hallucination-free chat, and file management are the three pillars of RAGFlow. Chats in RAGFlow are based on a particular knowledge base or multiple knowledge bases. Once you have created your knowledge base and finished file parsing, you can go ahead and start an AI conversation.
 
 ## Start an AI chat
@@ -21,16 +25,23 @@ You start an AI conversation by creating an assistant.
    - **Empty response**:
      - If you wish to *confine* RAGFlow's answers to your knowledge bases, leave a response here. Then, when it doesn't retrieve an answer, it *uniformly* responds with what you set here.
      - If you wish RAGFlow to *improvise* when it doesn't retrieve an answer from your knowledge bases, leave it blank, which may give rise to hallucinations.
-   - **Show quote**: This is a key feature of RAGFlow and enabled by default. RAGFlow does not work like a black box. instead, it clearly shows the sources of information that its responses are based on.
+   - **Show quote**: This is a key feature of RAGFlow and enabled by default. RAGFlow does not work like a black box. Instead, it clearly shows the sources of information that its responses are based on.
    - Select the corresponding knowledge bases. You can select one or multiple knowledge bases, but ensure that they use the same embedding model, otherwise an error would occur.
 
 3. Update **Prompt Engine**:
 
    - In **System**, you fill in the prompts for your LLM, you can also leave the default prompt as-is for the beginning.
    - **Similarity threshold** sets the similarity "bar" for each chunk of text. The default is 0.2. Text chunks with lower similarity scores are filtered out of the final response.
-   - **Vector similarity weight** is set to 0.3 by default. RAGFlow uses a hybrid score system, combining keyword similarity and vector similarity, for evaluating the relevance of different text chunks. This value sets the weight assigned to the vector similarity component in the hybrid score.
+   - **Keyword similarity weight** is set to 0.7 by default. RAGFlow uses a hybrid score system to evaluate the relevance of different text chunks. This value sets the weight assigned to the keyword similarity component in the hybrid score.
+     - If **Rerank model** is left empty, the hybrid score system uses keyword similarity and vector similarity, and the default weight assigned to the vector similarity component is 1-0.7=0.3.
+     - If **Rerank model** is selected, the hybrid score system uses keyword similarity and reranker score, and the default weight assigned to the reranker score is 1-0.7=0.3.
    - **Top N** determines the *maximum* number of chunks to feed to the LLM. In other words, even if more chunks are retrieved, only the top N chunks are provided as input.
-   - **Variable**:
+   - **Multi-turn optimization** enhances user queries using existing context in a multi-round conversation. It is enabled by default. When enabled, it will consume additional LLM tokens and significantly increase the time to generate answers.
+   - **Rerank model** sets the reranker model to use. It is left empty by default.
+     - If **Rerank model** is left empty, the hybrid score system uses keyword similarity and vector similarity, and the default weight assigned to the vector similarity component is 1-0.7=0.3.
+     - If **Rerank model** is selected, the hybrid score system uses keyword similarity and reranker score, and the default weight assigned to the reranker score is 1-0.7=0.3.
+   - **Variable** refers to the variables (keys) to be used in the system prompt. `{knowledge}` is a reserved variable. Click **Add** to add more variables for the system prompt.
+      - If you are uncertain about the logic behind **Variable**, leave it *as-is*.
 
 4. Update **Model Setting**:
 
@@ -42,9 +53,18 @@ You start an AI conversation by creating an assistant.
 
 5. Now, let's start the show:
 
-   ![question1](https://github.com/infiniflow/ragflow/assets/93570324/bb72dd67-b35e-4b2a-87e9-4e4edbd6e677)
+   ![question1](https://github.com/user-attachments/assets/c4114a3d-74ff-40a3-9719-6b47c7b11ab1)
+
+:::tip NOTE
 
-   ![question2](https://github.com/infiniflow/ragflow/assets/93570324/7cc585ae-88d0-4aa2-817d-0370b2ad7230)
+Click the light bubble logo above the answer to view the expanded system prompt:
+   
+![](https://github.com/user-attachments/assets/515ab187-94e8-412a-82f2-aba52cd79e09)
+   
+Scroll down the expanded prompt to view the time consumed for each task:
+   
+![enlighten](https://github.com/user-attachments/assets/fedfa2ee-21a7-451b-be66-20125619923c)
+:::
 
 ## Update settings of an existing chat assistant
 

docs/references/agent_component_reference/_category_.json

@@ -1,5 +1,5 @@
 {
-  "label": "Agent Component Reference",
+  "label": "Agent Components",
   "position": 3,
   "link": {
     "type": "generated-index",

docs/references/agent_component_reference/begin.mdx

@@ -29,7 +29,7 @@ An opening greeting is the agent's first message to the user. It can be a welcom
 
 ### Global variables
 
-You can set global variables within the **Begin** component, which can be either required or optional. Once established, users will need to provide values for these variables when interacting or with the agent. Click **+ Add variable** to add a global variable, each with the following attributes:
+You can set global variables within the **Begin** component, which can be either required or optional. Once established, users will need to provide values for these variables when interacting or chatting with the agent. Click **+ Add variable** to add a global variable, each with the following attributes:
 
 - **Key**: *Required*  
   The unique variable name.
@@ -41,7 +41,7 @@ You can set global variables within the **Begin** component, which can be either
   - **line**: Accepts a single line of text without line breaks.
   - **paragraph**: Accepts multiple lines of text, including line breaks.
   - **options**: Requires the user to select a value for this variable from a dropdown menu. And you are required to set *at least* one option for the dropdown menu.
-  - **file**: Requires the user to upload a file from their device.
+  - **file**: Requires the user to upload one or multiple files from their device.
   - **integer**: Accepts an integer as input.
   - **boolean**: Requires the user to toggle between on and off.
 - **Optional**: A toggle indicating whether the variable is optional. 

docs/references/faq.md

@@ -81,9 +81,13 @@ No, this feature is not supported.
 
 ---
 
-### Do you support multiple rounds of dialogues, i.e., referencing previous dialogues as context for the current dialogue?
+### Do you support multiple rounds of dialogues, referencing previous dialogues as context for the current query?
 
-This feature and the related APIs are still in development. Contributions are welcome.
+Yes, we support enhancing user queries based on existing context of an ongoing conversation:
+
+1. On the **Chat** page, hover over the desired assistant and select **Edit**.
+2. In the **Chat Configuration** popup, click the **Prompt Engine** tab.
+3. Toggle on **Multi-turn optimization** to enable this feature.
 
 ---
 
@@ -388,6 +392,14 @@ You can use Ollama or Xinference to deploy local LLM. See [here](../guides/deplo
 
 ---
 
+### Is it possible to add an LLM that is not supported?
+
+If your model is not currently supported but has APIs compatible with those of OpenAI, click **OpenAI-API-Compatible** on the **Model providers** page to configure your model:
+
+![openai-api-compatible](https://github.com/user-attachments/assets/b1e964f2-b86e-41af-8528-fd8a96dc5f6f)
+
+---
+
 ### How to interconnect RAGFlow with Ollama?
 
 - If RAGFlow is locally deployed, ensure that your RAGFlow and Ollama are in the same LAN.

docs/references/http_api_reference.md

@@ -3,7 +3,7 @@ sidebar_position: 1
 slug: /http_api_reference
 ---
 
-# HTTP API Reference
+# HTTP API
 
 A complete reference for RAGFlow's RESTful API. Before proceeding, please ensure you [have your RAGFlow API key ready for authentication](https://ragflow.io/docs/dev/acquire_ragflow_api_key).
 

docs/references/python_api_reference.md

@@ -3,7 +3,7 @@ sidebar_position: 2
 slug: /python_api_reference
 ---
 
-# Python API Reference
+# Python API
 
 A complete reference for RAGFlow's Python APIs. Before proceeding, please ensure you [have your RAGFlow API key ready for authentication](https://ragflow.io/docs/dev/acquire_ragflow_api_key).
 

docs/references/supported_models.mdx

@@ -62,6 +62,10 @@ A complete list of models supported by RAGFlow, which will continue to expand.
 </APITable>
 ```
 
+:::danger IMPORTANT
+If your model is not listed here but has APIs compatible with those of OpenAI, click **OpenAI-API-Compatible** on the **Model providers** page to configure your model.
+::: 
+
 :::note
 The list of supported models is extracted from [this source](https://github.com/infiniflow/ragflow/blob/main/rag/llm/__init__.py) and may not be the most current. For the latest supported model list, please refer to the Python file.
 :::