Add structural overview

README.md

@@ -2,7 +2,7 @@
 
 This repository contains two projects:
 
-* The **AutoDev Python project** providing the core functionality (`./autodev`), including
+* The [**AutoDev Python project**](autodev/README.md) providing the core functionality (`./autodev`), including
   * auto-completion models (that can suggest completions based on the current editing context)
     * fine-tuning of completion models to teach them new languages (or to teach them about your libraries, your code style, etc.)
     * quantitative & qualitative evaluation
@@ -11,9 +11,9 @@ This repository contains two projects:
   * code-based assistance functions, where an instruction-following model is given a task based on an existing code snippet (e.g. reviewing code, adding comments or input checks, explaining code, etc.)
   * an inference service, which provides access to the above functions
   * question answering on document databases (including source code documents)
-* A Java project implementing the **AutoDev IntellIJ IDEA plugin** which provides access to the coding assistance functions within JetBrains IDEs such as IntelliJ IDEA, PyCharm and others (`./idea-plugin`).
+* A Java project implementing the [**AutoDev IntellIJ IDEA plugin**](idea-plugin/README.md) which provides access to the coding assistance functions within JetBrains IDEs such as IntelliJ IDEA, PyCharm and others (`./idea-plugin`).
 
-Please refer to the projects' individual README files for further information.
+Please refer to the projects' individual README files for further information (linked above).
 
 ## AutoDev in Action
 
@@ -33,3 +33,11 @@ Identifying potential problems in a piece of code:
 
 ![Example: identifying potential problems](images/potential-problems.gif "Identifying potential problems of a piece of code in IntelliJ IDEA")
 
+## Structural Overview
+
+Here's a structural overview showing the main components and their interactions: 
+
+![Example: auto-completion](images/arch.png "Structural Overview")
+
+* For auto-completion, the model is served directly by the AutoDev inference service, i.e. the model is always locally provided and is either an unmodified open-source model (from the [Hugging Face Hub](https://huggingface.co/docs/hub/index)) or a fine-tuned version thereof. Fine-tuning may use community data or our own data.
+* For other assistance functions built on instruction-following models, you have the option of using either a (fine-tuned) open-source model, as in the previous case, or a proprietary model (such as ChatGPT).