Added supported LLMs (#1517)

### 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/configure_knowledge_base.md

@@ -107,6 +107,10 @@ 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 increase its relevance. 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:
 
    _As you can tell from the following, RAGFlow responds with truthful citations._

docs/guides/llm_api_key_setup.md

@@ -12,8 +12,14 @@ An API key is required for RAGFlow to interact with an online AI model. This gui
 For now, RAGFlow supports the following online LLMs. Click the corresponding link to apply for your 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,
+- Gemini,
+- Groq,
+- Mistral,
+- Bedrock,
 - [Tongyi-Qianwen](https://dashscope.console.aliyun.com/model),
 - [ZHIPU-AI](https://open.bigmodel.cn/),
+- MiniMax
 - [Moonshot](https://platform.moonshot.cn/docs),
 - [DeepSeek](https://platform.deepseek.com/api-docs/),
 - [Baichuan](https://www.baichuan-ai.com/home),