Editorial updates to Docker README (#3223)

### What problem does this PR solve? ### Type of change - [x] Documentation Update
infiniflow · Nov 6, 2024 · af74bf0 · af74bf0
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diff --git a/docker/README.md b/docker/README.md
@@ -8,66 +8,75 @@ Look into [.env](./.env), there're some important variables.
 
 - `STACK_VERSION`  
   The Elasticsearch version. Defaults to `8.11.3`
-
 - `ES_PORT`  
   Port to expose Elasticsearch HTTP API to the host. Defaults to `1200`.
-
 - `ELASTIC_PASSWORD`  
   The Elasticsearch password.
-
 - `MYSQL_PASSWORD`  
   The MySQL password. When updated, you must also revise the `mysql.password` entry in  [service_conf.yaml](./service_conf.yaml) accordingly.
-
 - `MYSQL_PORT`  
-  The exported port number of MySQL Docker container, needed when you access the database from outside the docker containers.
-
+  The exported port number of MySQL Docker container, needed when you access the database from outside the Docker container.
 - `MINIO_USER`  
   The MinIO username. When updated, you must also revise the `minio.user` entry in  [service_conf.yaml](./service_conf.yaml) accordingly.
-
 - `MINIO_PASSWORD`  
   The MinIO password. When updated, you must also revise the `minio.password` entry in  [service_conf.yaml](./service_conf.yaml) accordingly.
-
-
-
 - `SVR_HTTP_PORT`  
   The port number on which RAGFlow's backend API server listens.
-
+- `TIMEZONE`  
+  The local time zone.
 - `RAGFLOW-IMAGE`  
   The Docker image edition. Available options:  
   - `infiniflow/ragflow:dev-slim` (default): The RAGFlow Docker image without embedding models  
-  - `infiniflow/ragflow:dev`: The RAGFlow Docker image with embedding models. See the 
-
-- `TIMEZONE`  
-  The local time zone.
+  - `infiniflow/ragflow:dev`: The RAGFlow Docker image with embedding models including:
+    - Embedded embedding models:
+      - `BAAI/bge-large-zh-v1.5` 
+      - `BAAI/bge-reranker-v2-m3`
+      - `maidalun1020/bce-embedding-base_v1`
+      - `maidalun1020/bce-reranker-base_v1`
+    - Embedding models that will be downloaded once you select them in the RAGFlow UI:
+      - `BAAI/bge-base-en-v1.5`
+      - `BAAI/bge-large-en-v1.5`
+      - `BAAI/bge-small-en-v1.5`
+      - `BAAI/bge-small-zh-v1.5`
+      - `jinaai/jina-embeddings-v2-base-en`
+      - `jinaai/jina-embeddings-v2-small-en`
+      - `nomic-ai/nomic-embed-text-v1.5`
+      - `sentence-transformers/all-MiniLM-L6-v2`
 
 
 ##  Service Configuration
 
-[service_conf.yaml](./service_conf.yaml) defines the system-level configuration for RAGFlow and is used by RAGFlow's *API server* and *task executor*.
+[service_conf.yaml](./service_conf.yaml) defines the system-level configuration for RAGFlow and is used by its API server and task executor.
 
 - `ragflow`
+
   - `host`: The IP address of the API server.
   - `port`: The serving port of API server.
-
+  
 - `mysql`
-  - `name`: The database name in MySQL used by RAGFlow.
-  - `user`: The database name in MySQL used by RAGFlow.
-  - `password`: The database password. When updated, you must also revise the `MYSQL_PASSWORD` variable in [.env](./.env) accordingly.
-  - `port`: The serving port of MySQL inside the container. When updated, you must also revise the `MYSQL_PORT` variable in [.env](./.env) accordingly.
+
+  - `name`: The database name in MySQL used by RAGFlow. Defaults to `rag_flow`.
+  - `user`: The MySQL user name.
+  - `password`: The MySQL password. When updated, you must also revise the `MYSQL_PASSWORD` variable in [.env](./.env) accordingly.
+  - `port`: The serving port of MySQL inside the Docker container. When updated, you must also revise the `MYSQL_PORT` variable in [.env](./.env) accordingly.
   - `max_connections`: The maximum database connection.
-  - `stale_timeout`: The timeout duration in seconds.
-
+  - `stale_timeout`: Timeout in seconds.
+  
 - `minio`
+
   - `user`: The MinIO username. When updated, you must also revise the `MINIO_USER` variable in [.env](./.env) accordingly.
   - `password`: The MinIO password. When updated, you must also revise the `MINIO_PASSWORD` variable in [.env](./.env) accordingly.
-  - `host`: The serving IP and port inside the docker container. This is not updating until changing the minio part in [docker-compose.yml](./docker-compose.yml)
-
-- `user_default_llm`  
-  Newly signed-up users use LLM configured by this part; otherwise, you need to configure your own LLM on the *Settings* page.  
+  - `host`: The serving IP and port inside the docker container. This is not updated until changing the minio part in [docker-compose.yml](./docker-compose.yml)
+
+- `user_default_llm`   
+
+  The default LLM to use for a new RAGFlow user. It is disabled by default. If you have not set it here, you can configure the default LLM on the **Settings** page in the RAGFlow UI. Newly signed-up users use LLM configured by this part; otherwise, you need to configure your own LLM on the *Settings* page.  
+
   - `factory`: The LLM suppliers. "OpenAI"， "Tongyi-Qianwen", "ZHIPU-AI", "Moonshot", "DeepSeek", "Baichuan", and "VolcEngine" are supported.
   - `api_key`: The API key for the specified LLM.
-
+  
 - `oauth`  
-  The OAuth configuration for signing up or signing in to RAGFlow using a third-party account.  
-  - `github`: Go to [Github](https://github.com/settings/developers), register a new application, the *client_id* and *secret_key* will be given.
+  The OAuth configuration for signing up or signing in to RAGFlow using a third-party account.  It is disabled by default. To enable this feature, uncomment the corresponding lines in **service_conf.yaml**.
+
+  - `github`: The GitHub authentication settings for your application. Visit the [Github Developer Settings page](https://github.com/settings/developers) to obtain your client_id and secret_key.
 
diff --git a/docs/guides/llm_api_key_setup.md b/docs/guides/llm_api_key_setup.md
@@ -9,24 +9,7 @@ An API key is required for RAGFlow to interact with an online AI model. This gui
 
 ## Get model API key
 
-For now, RAGFlow supports the following online LLMs. Click the corresponding link to apply for your model API key. Most LLM providers grant newly-created accounts trial credit, which will expire in a couple of months, or a promotional amount of free quota.
-
-- [OpenAI](https://platform.openai.com/login?launch)
-- [Azure-OpenAI](https://ai.azure.com/)
-- [Gemini](https://aistudio.google.com/)
-- [Groq](https://console.groq.com/)
-- [Mistral](https://mistral.ai/)
-- [Bedrock](https://aws.amazon.com/cn/bedrock/)
-- [Tongyi-Qianwen](https://dashscope.console.aliyun.com/model)
-- [ZHIPU-AI](https://open.bigmodel.cn/)
-- [MiniMax](https://platform.minimaxi.com/)
-- [Moonshot](https://platform.moonshot.cn/docs)
-- [DeepSeek](https://platform.deepseek.com/api-docs/)
-- [Baichuan](https://www.baichuan-ai.com/home)
-- [VolcEngine](https://www.volcengine.com/docs/82379)
-- [Jina](https://jina.ai/reader/)
-- [OpenRouter](https://openrouter.ai/)
-- [StepFun](https://platform.stepfun.com/)
+RAGFlow supports most mainstream LLMs. Please refer to [Supported Models](./references/supported_models.mdx) for a complete list of supported models. You will need to apply for your model API key online. Note that most LLM providers grant newly-created accounts trial credit, which will expire in a couple of months, or a promotional amount of free quota.
 
 :::note
 If you find your online LLM is not on the list, don't feel disheartened. The list is expanding, and you can [file a feature request](https://github.com/infiniflow/ragflow/issues/new?assignees=&labels=feature+request&projects=&template=feature_request.yml&title=%5BFeature+Request%5D%3A+) with us! Alternatively, if you have customized or locally-deployed models, you can [bind them to RAGFlow using Ollama, Xinference, or LocalAI](./deploy_local_llm.mdx).

diff --git a/docs/guides/manage_files.md b/docs/guides/manage_files.md
@@ -49,7 +49,7 @@ You can link your file to one knowledge base or multiple knowledge bases at one
 
 ## Search files or folders
 
-As of RAGFlow v0.13.0, the search feature is still in a rudimentary form, supporting only file and folder search in the current directory by name (files or folders in the child directory will not be retrieved).
+**File Management** only supports file name and folder name filtering in the current directory (files or folders in the child directory will not be retrieved).
 
 ![search file](https://github.com/infiniflow/ragflow/assets/93570324/77ffc2e5-bd80-4ed1-841f-068e664efffe)
 
@@ -73,7 +73,7 @@ To bulk delete files or folders:
 ![bulk delete](https://github.com/infiniflow/ragflow/assets/93570324/519b99ab-ec7f-4c8a-8cea-e0b6dcb3cb46)
 
 > - You are not allowed to delete the **root/.knowledgebase** folder. 
-> - Deleting files that have been linked to knowledge bases will AUTOMATICALLY REMOVE all associated file references across the knowledge bases. 
+> - Deleting files that have been linked to knowledge bases will **AUTOMATICALLY REMOVE** all associated file references across the knowledge bases.
 
 ## Download uploaded file
 

diff --git a/docs/quickstart.mdx b/docs/quickstart.mdx
@@ -223,24 +223,7 @@ With the default settings, you only need to enter `http://IP_OF_YOUR_MACHINE` (*
 
 ## Configure LLMs
 
-RAGFlow is a RAG engine, and it needs to work with an LLM to offer grounded, hallucination-free question-answering capabilities. For now, RAGFlow supports the following LLMs, and the list is expanding:
-
-- [OpenAI](https://platform.openai.com/login?launch)
-- [Azure-OpenAI](https://ai.azure.com/)
-- [Gemini](https://aistudio.google.com/)
-- [Groq](https://console.groq.com/)
-- [Mistral](https://mistral.ai/)
-- [Bedrock](https://aws.amazon.com/cn/bedrock/)
-- [Tongyi-Qianwen](https://dashscope.console.aliyun.com/model)
-- [ZHIPU-AI](https://open.bigmodel.cn/)
-- [MiniMax](https://platform.minimaxi.com/)
-- [Moonshot](https://platform.moonshot.cn/docs)
-- [DeepSeek](https://platform.deepseek.com/api-docs/)
-- [Baichuan](https://www.baichuan-ai.com/home)
-- [VolcEngine](https://www.volcengine.com/docs/82379)
-- [Jina](https://jina.ai/reader/)
-- [OpenRouter](https://openrouter.ai/)
-- [StepFun](https://platform.stepfun.com/)
+RAGFlow is a RAG engine and needs to work with an LLM to offer grounded, hallucination-free question-answering capabilities. RAGFlow supports most mainstream LLMs. For a complete list of supported models, please refer to [Supported Models](./references/supported_models.mdx).
 
 :::note 
 RAGFlow also supports deploying LLMs locally using Ollama, Xinference, or LocalAI, but this part is not covered in this quick start guide. 

diff --git a/docs/references/faq.md b/docs/references/faq.md
@@ -5,6 +5,8 @@ slug: /faq
 
 # Frequently asked questions
 
+Queries regarding general usage, troubleshooting, features, performance, and more.
+
 ## General
 
 ### 1. What sets RAGFlow apart from other RAG products?
@@ -98,7 +100,7 @@ docker build -t infiniflow/ragflow:vX.Y.Z. --network host
 
 #### 2.1 Cannot access https://huggingface.co
 
-A *locally* deployed RAGflow downloads OCR and embedding modules from [Huggingface website](https://huggingface.co) by default. If your machine is unable to access this site, the following error occurs and PDF parsing fails: 
+A *locally* deployed RAGflow downloads OCR and embedding modules from [Huggingface website](https://huggingface.co) by default. If your machine is unable to access this site, the following error occurs and PDF parsing fails:
 
 ```
 FileNotFoundError: [Errno 2] No such file or directory: '/root/.cache/huggingface/hub/models--InfiniFlow--deepdoc/snapshots/be0c1e50eef6047b412d1800aa89aba4d275f997/ocr.res'

diff --git a/docs/references/supported_models.mdx b/docs/references/supported_models.mdx
@@ -12,15 +12,15 @@ A complete list of models supported by RAGFlow, which will continue to expand.
 <APITable>
 ```
 
-| Provider              | Chat               | Embedding          | Rerank             | Multi-modal        | ASR/STT            | TTS                |
+| Provider              | Chat               | Embedding          | Rerank             | Multimodal         | ASR                | TTS                |
 | --------------------- | ------------------ | ------------------ | ------------------ | ------------------ | ------------------ | ------------------ |
 | Anthropic             | :heavy_check_mark: |                    |                    |                    |                    |                    |
 | Azure-OpenAI          | :heavy_check_mark: | :heavy_check_mark: |                    | :heavy_check_mark: | :heavy_check_mark: |                    |
 | BAAI                  |                    | :heavy_check_mark: | :heavy_check_mark: |                    |                    |                    |
 | BaiChuan              | :heavy_check_mark: | :heavy_check_mark: |                    |                    |                    |                    |
 | BaiduYiyan            | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |                    |                    |
 | Bedrock               | :heavy_check_mark: | :heavy_check_mark: |                    |                    |                    |                    |
-| cohere                | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |                    |                    |
+| Cohere                | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |                    |                    |
 | DeepSeek              | :heavy_check_mark: |                    |                    |                    |                    |                    |
 | FastEmbed             |                    | :heavy_check_mark: |                    |                    |                    |                    |
 | Fish Audio            |                    |                    |                    |                    |                    | :heavy_check_mark: |
@@ -62,5 +62,6 @@ A complete list of models supported by RAGFlow, which will continue to expand.
 </APITable>
 ```
 
-
-
+:::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.
+:::