Fix typo and error (#5479)

### 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] Bug Fix (non-breaking change which fixes an issue)
- [x] Documentation Update

---------

Signed-off-by: Jin Hai <haijin.chn@gmail.com>

docs/guides/agent/text2sql_agent.md

@@ -5,7 +5,7 @@ slug: /text2sql_agent
 
 # Create a Text2SQL agent
 
-Build a Text2SQL agent leverging RAGFlow's RAG capabilities. Contributed by @TeslaZY.
+Build a Text2SQL agent leveraging RAGFlow's RAG capabilities. Contributed by @TeslaZY.
 
 ## Scenario
 
@@ -343,7 +343,7 @@ Synonyms: laptop computer,laptop pc
 3. Create a Retrieval node and name it Thesaurus; create an ExeSQL node.
 4. Configure the Q->SQL, DDL, DB_Description, and TextSQL_Thesaurus knowledge bases. Please refer to the following:
    ![Configure Retrieval node](https://github.com/user-attachments/assets/25d67b01-954e-4eb4-87f5-c54262cf9a3e)
-5. Configure the Generate node, named LLM‘s prompt:
+5. Configure the Generate node, named LLM's prompt:
    - Add this content to the prompt provided by the template to provide the thesaurus content to the LLM:
      ```plaintext
      ## You may use the following Thesaurus statements. For example, what I ask is from Synonyms, you must use Standard noun to generate SQL. Use responses to past questions also to guide you: {sql_thesaurus}.

docs/guides/configure_knowledge_base/construct_knowledge_graph.md

@@ -25,7 +25,7 @@ Knowledge graphs are especially useful for multi-hop question-answering involvin
 
 ## Prerequisites
 
-The system's default chat model is used to generate knowledge graph. Before proceeding, ensure that you have an chat model properly configured:
+The system's default chat model is used to generate knowledge graph. Before proceeding, ensure that you have a chat model properly configured:
 
 ![Image](https://github.com/user-attachments/assets/6bc34279-68c3-4d99-8d20-b7bd1dafc1c1)
 
@@ -60,10 +60,10 @@ In a knowledge graph, a community is a cluster of entities linked by relationshi
 
 1. On the **Configuration** page of your knowledge base, switch on **Extract knowledge graph** or adjust its settings as needed, and click **Save** to confirm your changes.
 
-   - *The default knowledge graph configurations for your knowlege base are now set and files uploaded from this point onward will automatically use these settings during parsing.*
+   - *The default knowledge graph configurations for your knowledge base are now set and files uploaded from this point onward will automatically use these settings during parsing.*
    - *Files parsed before this update will retain their original knowledge graph settings.*
 
-2. The knowledge graph of your knowlege base does *not* automatically update *until* a newly uploaded file is parsed.
+2. The knowledge graph of your knowledge base does *not* automatically update *until* a newly uploaded file is parsed.
 
    _A **Knowledge graph** entry appears under **Configuration** once a knowledge graph is created._
 

docs/guides/deploy_local_llm.mdx

@@ -59,20 +59,20 @@ success
 
 ### 2. Ensure Ollama is accessible
 
-If RAGFlow runs in Docker and Ollama runs on the same host machine, check if ollama is accessiable from inside the RAGFlow container:
+If RAGFlow runs in Docker and Ollama runs on the same host machine, check if ollama is accessible from inside the RAGFlow container:
 ```bash
 sudo docker exec -it ragflow-server bash
 root@8136b8c3e914:/ragflow# curl  http://host.docker.internal:11434/
 Ollama is running
 ```
 
-If RAGFlow runs from source code and Ollama runs on the same host machine, check if ollama is accessiable from RAGFlow host machine:
+If RAGFlow runs from source code and Ollama runs on the same host machine, check if ollama is accessible from RAGFlow host machine:
 ```bash
 curl  http://localhost:11434/
 Ollama is running
 ```
 
-If RAGFlow and Ollama run on different machines, check if ollama is accessiable from RAGFlow host machine:
+If RAGFlow and Ollama run on different machines, check if ollama is accessible from RAGFlow host machine:
 ```bash
 curl  http://${IP_OF_OLLAMA_MACHINE}:11434/
 Ollama is running

docs/references/faq.md

@@ -22,7 +22,7 @@ The "garbage in garbage out" status quo remains unchanged despite the fact that
 
 ---
 
-### Where to find the version of RAGFlow? How to interprete it?
+### Where to find the version of RAGFlow? How to interpret it?
 
 You can find the RAGFlow version number on the **System** page of the UI:
 
@@ -345,13 +345,13 @@ Your IP address or port number may be incorrect. If you are using the default co
 A correct Ollama IP address and port is crucial to adding models to Ollama:
 
 - If you are on demo.ragflow.io, ensure that the server hosting Ollama has a publicly accessible IP address. Note that 127.0.0.1 is not a publicly accessible IP address.
-- If you deploy RAGFlow locally, ensure that Ollama and RAGFlow are in the same LAN and can comunicate with each other.
+- If you deploy RAGFlow locally, ensure that Ollama and RAGFlow are in the same LAN and can communicate with each other.
 
 See [Deploy a local LLM](../guides/deploy_local_llm.mdx) for more information.
 
 ---
 
-#### Do you offer examples of using deepdoc to parse PDF or other files?
+#### Do you offer examples of using DeepDoc to parse PDF or other files?
 
 Yes, we do. See the Python files under the **rag/app** folder.
 

docs/references/python_api_reference.md

@@ -42,7 +42,7 @@ Whether to receive the response as a stream. Set this to `false` explicitly if y
 
 #### Returns
 
-- Success: Respose [message](https://platform.openai.com/docs/api-reference/chat/create) like OpenAI
+- Success: Response [message](https://platform.openai.com/docs/api-reference/chat/create) like OpenAI
 - Failure: `Exception`
 
 #### Examples