minor corrections in 2.3.-AI-Setup.md

Author: kaixxx

docs/doc/en/2.3.-AI-Setup.md

@@ -112,6 +112,7 @@ large_model = <The exact name of the model in the API>
 large_model_context_window = <The maximum number of tokens in a single request>
 fast_model = <Can be identical to large_model or name a smaller model, used for simple tasks>
 fast_model_context_window = <The maximum number of tokens for the small model>
+reasoning_effort = default
 api_base = <The URL of the API base, e.g., http://localhost:11434/v1 for a local Ollama>
 api_key = <The API key if needed, or "None" instead. Do not leave this field empty.>
 ```
@@ -147,7 +148,7 @@ Technical note: The QualCoder local AI memory is a hybrid system based on [E5 se
 
 ## Improve AI Usability in Your Project
 
-The AI agent in QualCoder should be able to read and understand the structure of your project, your empirical documents, codes, and memos. It should also have a clear picture of the goals, research questions, and methods that drive your research. This allows it to provide much more targeted answers and suggestions. Some suggestions:
+The AI agent in QualCoder should be able to read and understand the structure of your project, your empirical documents, codes, and memos. It should also have a clear picture of the goals, research questions, and methods that drive your research. This allows it to provide much more targeted answers. Some suggestions:
 
 - **Update your project memo** (menu "Project > Project Memo") with a short description of your research topics, questions, objectives, and the empirical data collected. This information will accompany every request sent to the AI, resulting in much more useful answers.
 - **Give your empirical documents readable names** so the AI agent can infer the type of data, e.g., "Interview Alice.txt". You can rename documents directly in the "Manage files" tab without re-importing them.