Updated obsolete faqs (#3554)

### What problem does this PR solve?


### Type of change


- [x] Documentation Update

docker/.env

@@ -1,5 +1,7 @@
 # The type of doc engine to use.
-# Supported values are `elasticsearch`, `infinity`.
+# Available options:
+# - `elasticsearch` (default) 
+# - `infinity` (https://github.com/infiniflow/infinity)
 DOC_ENGINE=${DOC_ENGINE:-elasticsearch}
 
 # ------------------------------
@@ -20,7 +22,7 @@ ES_HOST=es01
 ES_PORT=1200
 
 # The password for Elasticsearch. 
-# When updated, you must revise the `es.password` entry in  service_conf.yaml accordingly.
+# When updated, you must revise the `es.password` entry in service_conf.yaml accordingly.
 ELASTIC_PASSWORD=infini_rag_flow
 
 # The port used to expose the Kibana service to the host machine, 
@@ -85,7 +87,7 @@ RAGFLOW_IMAGE=infiniflow/ragflow:dev-slim
 # RAGFLOW_IMAGE=infiniflow/ragflow:dev
 # 
 # The Docker image of the dev edition includes:
-# - Embedded embedding models:
+# - Built-in embedding models:
 #   - BAAI/bge-large-zh-v1.5
 #   - BAAI/bge-reranker-v2-m3
 #   - maidalun1020/bce-embedding-base_v1
@@ -123,3 +125,7 @@ TIMEZONE='Asia/Shanghai'
 # Optimizations for MacOS
 # Uncomment the following line if your OS is MacOS:
 # MACOS=1
+
+# The maximum file size for each uploaded file, in bytes.
+# You can uncomment this line and update the value if you wish to change 128M file size limit
+# MAX_CONTENT_LENGTH=134217728

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).

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`

docs/quickstart.mdx

@@ -286,8 +286,8 @@ 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 [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