Updated obsolete faqs (infiniflow#3575)

### What problem does this PR solve?

### Type of change

- [x] Documentation Update

docker/README.md

@@ -77,7 +77,7 @@ The [.env](./.env) file contains important environment variables for Docker.
 
   - `infiniflow/ragflow:dev-slim` (default): The RAGFlow Docker image without embedding models.  
   - `infiniflow/ragflow:dev`: The RAGFlow Docker image with embedding models including:
-    - Embedded embedding models:
+    - Built-in embedding models:
       - `BAAI/bge-large-zh-v1.5` 
       - `BAAI/bge-reranker-v2-m3`
       - `maidalun1020/bce-embedding-base_v1`
@@ -117,6 +117,11 @@ The [.env](./.env) file contains important environment variables for Docker.
 - `MACOS`  
   Optimizations for MacOS. It is disabled by default. You can uncomment this line if your OS is MacOS.
 
+### Maximum file size
+
+- `MAX_CONTENT_LENGTH`  
+  The maximum file size for each uploaded file, in bytes. You can uncomment this line if you wish to change 128M file size limit.
+
 ## 🐋 Service configuration
 
 [service_conf.yaml](./service_conf.yaml) specifies the system-level configuration for RAGFlow and is used by its API server and task executor. In a dockerized setup, this file is automatically created based on the [service_conf.yaml.template](./service_conf.yaml.template) file (replacing all environment variables by their values).
@@ -154,4 +159,4 @@ The [.env](./.env) file contains important environment variables for Docker.
   - `api_key`: The API key for the specified LLM. You will need to apply for your model API key online.
 
 > [!TIP]  
-> If you do not set the default LLM here, configure the default LLM on the **Settings** page in the RAGFlow UI.
+> If you do not set the default LLM here, configure the default LLM on the **Settings** page in the RAGFlow UI.

docs/configurations.md

@@ -64,7 +64,7 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con
 ### MySQL
 
 - `MYSQL_PASSWORD`  
-  The password for MySQL. 
+  The password for MySQL.
 - `MYSQL_PORT`  
   The port used to expose the MySQL service to the host machine, allowing **external** access to the MySQL database running inside the Docker container. Defaults to `5455`.
 
@@ -75,7 +75,7 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con
 - `MINIO_PORT`  
   The port used to expose the MinIO API service to the host machine, allowing **external** access to the MinIO object storage service running inside the Docker container. Defaults to `9000`.
 - `MINIO_USER`  
-  The username for MinIO. 
+  The username for MinIO.
 - `MINIO_PASSWORD`  
   The password for MinIO. accordingly.
 
@@ -95,7 +95,7 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con
 
   - `infiniflow/ragflow:dev-slim` (default): The RAGFlow Docker image without embedding models.  
   - `infiniflow/ragflow:dev`: The RAGFlow Docker image with embedding models including:
-    - Embedded embedding models:
+    - Built-in embedding models:
       - `BAAI/bge-large-zh-v1.5` 
       - `BAAI/bge-reranker-v2-m3`
       - `maidalun1020/bce-embedding-base_v1`
@@ -181,4 +181,4 @@ The default LLM to use for a new RAGFlow user. It is disabled by default. To ena
 
 :::tip NOTE  
 If you do not set the default LLM here, configure the default LLM on the **Settings** page in the RAGFlow UI.
-:::
+:::

docs/quickstart.mdx

@@ -286,15 +286,15 @@ 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 [FAQ 4.3](https://ragflow.io/docs/dev/faq#43-why-does-my-document-parsing-stall-at-under-one-percent). 
-- If your file parsing gets stuck at near completion, see [FAQ 4.4](https://ragflow.io/docs/dev/faq#44-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](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)
 :::
 
-## Intervene with file parsing 
+## Intervene with file parsing
 
-RAGFlow features visibility and explainability, allowing you to view the chunking results and intervene where necessary. To do so: 
+RAGFlow features visibility and explainability, allowing you to view the chunking results and intervene where necessary. To do so:
 
-1. Click on the file that completes file parsing to view the chunking results: 
+1. Click on the file that completes file parsing to view the chunking results:
 
    _You are taken to the **Chunk** page:_
 
@@ -306,8 +306,8 @@ RAGFlow features visibility and explainability, allowing you to view the chunkin
 
    ![update chunk](https://github.com/infiniflow/ragflow/assets/93570324/1d84b408-4e9f-46fd-9413-8c1059bf9c76)
 
-:::caution NOTE 
-You can add keywords to a file chunk to improve its ranking for queries containing those keywords. This action increases its keyword weight and can improve its position in search list.  
+:::caution NOTE
+You can add keywords to a file chunk to improve its ranking for queries containing those keywords. This action increases its keyword weight and can improve its position in search list.
 :::
 
 4. In Retrieval testing, ask a quick question in **Test text** to double check if your configurations work:
@@ -318,17 +318,17 @@ You can add keywords to a file chunk to improve its ranking for queries containi
 
 ## Set up an AI chat
 
-Conversations 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. 
+Conversations 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.
 
 1. Click the **Chat** tab in the middle top of the mage **>** **Create an assistant** to show the **Chat Configuration** dialogue *of your next dialogue*.
    > RAGFlow offer the flexibility of choosing a different chat model for each dialogue, while allowing you to set the default models in **System Model Settings**.
 
-2. Update **Assistant Setting**: 
+2. Update **Assistant Setting**:
 
    - Name your assistant and specify your knowledge bases.
    - **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. 
+     - 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.
 
 3. Update **Prompt Engine** or leave it as is for the beginning.
 
@@ -347,4 +347,4 @@ RAGFlow also offers HTTP and Python APIs for you to integrate RAGFlow's capabili
 - [Acquire a RAGFlow API key](./guides/develop/acquire_ragflow_api_key.md)
 - [HTTP API reference](./references/http_api_reference.md)
 - [Python API reference](./references/python_api_reference.md)
-:::
+:::