Merge branch 'develop' into feature/tutorial-groups/tutorial-lectures

Author: marlonnienaber

docs/admin/setup/hyperion.rst

@@ -3,82 +3,6 @@
 Hyperion Service
 ----------------
 
-Hyperion extends Artemis with AI-assisted authoring features for programming exercises. It offers
-consistency checks for problem statements and exercise artefacts and can rewrite instructions with the help
-of generative AI. The functionality is provided entirely by Artemis and Spring AI, so no
-EduTelligence service needs to be deployed.
-
-Prerequisites
-^^^^^^^^^^^^^
-
-- A running Artemis instance that loads the ``core`` profile.
-- Network access to an LLM provider that is supported by Spring AI (for example OpenAI or Azure OpenAI).
-- A valid API key for the chosen provider.
-
-Enable the Hyperion module
-^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Hyperion is disabled by default. Activate it by overriding the ``artemis.hyperion.enabled`` property in the
-configuration that the server reads on startup (for example ``application-prod.yml``).
-
-.. code:: yaml
-
-   artemis:
-     hyperion:
-       enabled: true
-
-
-Configure Spring AI
-^^^^^^^^^^^^^^^^^^^^
-
-Hyperion delegates all model interactions to Spring AI. Configure exactly one provider; Artemis currently
-ships the Azure OpenAI starter, but classic OpenAI endpoints work as well when configured through Spring AI.
-
-OpenAI
-""""""
-
-.. code:: yaml
-
-   spring:
-     ai:
-       azure:
-         openai:
-           open-ai-api-key: <openai-api-key> # automatically sets the azure endpoint to https://api.openai.com/v1
-           chat:
-             options:
-               deployment-name: gpt-5-mini # Or another (reasonably capable) model
-               temperature: 1.0 # Required to be 1.0 for gpt-5
-
-Azure OpenAI
-""""""""""""
-
-.. code:: yaml
-
-   spring:
-     ai:
-       azure:
-         openai:
-           api-key: <azure-openai-api-key>
-           endpoint: https://<your-resource-name>.openai.azure.com
-           chat:
-             options:
-               deployment-name: <azure-deployment> # gpt-5-mini deployment recommended
-               temperature: 1.0 # Required to be 1.0 for gpt-5
-
-Verifying the integration
-^^^^^^^^^^^^^^^^^^^^^^^^^
-
-1. Restart the Artemis server and confirm that ``hyperion`` appears in ``activeModuleFeatures`` on
-   ``/management/info``.
-2. Log in as an instructor and open the programming exercise problem statement editor. New Hyperion actions
-   appear in the markdown editor toolbar (rewrite and consistency check).
-3. Run a consistency check to ensure the LLM call succeeds. Inspect the server logs for ``Hyperion`` entries
-   if the request fails; misconfigured credentials and missing network egress are the most common causes.
-
-Operational considerations
-^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-- **Cost control:** Define usage policies and rate limits with your provider. Hyperion requests can process the
-  full problem statement, so costs scale with exercise size.
-- **Data protection:** Model providers receive exercise content. Obtain consent and align with institutional
-  policies before enabling Hyperion in production.
+.. note::
+   This documentation has been migrated to the new documentation system.
+   Please refer to the `Hyperion Setup Guide <https://ls1intum.github.io/Artemis/admin/hyperion>`_ in the new documentation.

docs/dev/setup/server.rst

@@ -47,7 +47,6 @@ You only need to modify them if your specific work or production environments re
        user-management:
            use-external: true
            password-reset:
-                credential-provider: <provider>  # Example: TUMonline
                 links:
                     en: '<link>'
                     de: '<link>'
@@ -258,38 +257,8 @@ Hyperion (Optional)
 
 Hyperion provides AI-assisted exercise creation features via Spring AI. No external Edutelligence service is required, only a LLM provider such as OpenAI or Azure OpenAI.
 
-Quick setup for development
-"""""""""""""""""""""""""""
-
-1. Enable the hyperion service
-
-    In your ``application-local.yml``, enable the hyperion service:
-
-   .. code-block:: yaml
-
-        artemis:
-            hyperion:
-                enabled: true
-
-2. Configure Spring AI
-
-   Set up your preferred provider (Azure OpenAI or OpenAI) in ``application-local.yml``. Examples:
-
-   .. code-block:: yaml
-
-        spring:
-          ai:
-            # https://docs.spring.io/spring-ai/reference/api/chat/azure-openai-chat.html
-            azure:
-              openai:
-                api-key: <azure_openai_key> # comment out if using OpenAI
-                # open-ai-api-key: <openai_key> # Fallback OpenAI key if needed, sets non-azure endpoint automatically
-                endpoint: <azure_openai_endpoint> # comment out if using OpenAI
-                chat:
-                  options:
-                    deployment-name: <azure_openai_deployment_name or openai_model_name>
-                    # Some Azure/OpenAI deployments (e.g., gpt-5-mini) only support the default temperature (1.0)
-                    temperature: 1.0
+.. note::
+   For local development with LM Studio (no cloud API keys required), see the `Spring AI Development Guide <https://ls1intum.github.io/Artemis/staff/spring-ai>`_ in the new documentation.
 
 Production setup
 """"""""""""""""

docs/index.rst

@@ -24,6 +24,7 @@ All these exercises are supposed to be run either live in the lecture with insta
 
    user/assessment
    user/exercises
+   user/quiz-training
    user/lectures
    user/exam_mode
    user/communication

docs/user/quiz-training.rst

@@ -0,0 +1,7 @@
+.. _quiz-training:
+
+Quiz Training
+=============
+
+This section has been moved to our new documentation:
+https://ls1intum.github.io/Artemis/student/quiz-training

documentation/docs/admin/hyperion.mdx

@@ -0,0 +1,76 @@
+---
+id: hyperion
+title: Hyperion Service
+sidebar_label: Hyperion Setup
+---
+
+import {CalloutVariant} from "../../src/components/Callout/Callout.types";
+import Callout from "../../src/components/Callout/Callout";
+
+# Hyperion Service
+
+Hyperion extends Artemis with AI-assisted authoring features for programming exercises. It offers consistency checks for problem statements and exercise artefacts and can rewrite instructions with the help of generative AI. The functionality is provided entirely by Artemis and Spring AI, so no EduTelligence service needs to be deployed.
+
+<Callout variant={CalloutVariant.info}>
+    For local development setups using LM Studio, refer to the [Spring AI Development Guide](/staff/spring-ai) in the Staff documentation.
+</Callout>
+
+## Prerequisites
+
+- A running Artemis instance that loads the `core` profile.
+- Network access to an LLM provider that is supported by Spring AI (for example OpenAI or Azure OpenAI).
+- A valid API key for the chosen provider.
+
+## Enable the Hyperion module
+
+Hyperion is disabled by default. Activate it by overriding the `artemis.hyperion.enabled` property in the configuration that the server reads on startup (for example `application-prod.yml`).
+
+```yaml
+artemis:
+  hyperion:
+    enabled: true
+```
+
+## Configure Spring AI
+
+Hyperion delegates all model interactions to Spring AI. Configure exactly one provider; Artemis currently ships the Azure OpenAI starter, but classic OpenAI endpoints work as well when configured through Spring AI.
+
+### OpenAI
+
+```yaml
+spring:
+  ai:
+    azure:
+      openai:
+        open-ai-api-key: <openai-api-key> # automatically sets the azure endpoint to https://api.openai.com/v1
+        chat:
+          options:
+            deployment-name: gpt-5-mini # Or another (reasonably capable) model
+            temperature: 1.0 # Required to be 1.0 for gpt-5
+```
+
+### Azure OpenAI
+
+```yaml
+spring:
+  ai:
+    azure:
+      openai:
+        api-key: <azure-openai-api-key>
+        endpoint: https://<your-resource-name>.openai.azure.com
+        chat:
+          options:
+            deployment-name: <azure-deployment> # gpt-5-mini deployment recommended
+            temperature: 1.0 # Required to be 1.0 for gpt-5
+```
+
+## Verifying the integration
+
+1. Restart the Artemis server and confirm that `hyperion` appears in `activeModuleFeatures` on `/management/info`.
+2. Log in as an instructor and open the programming exercise problem statement editor. New Hyperion actions appear in the markdown editor toolbar (rewrite and consistency check).
+3. Run a consistency check to ensure the LLM call succeeds. Inspect the server logs for `Hyperion` entries if the request fails; misconfigured credentials and missing network egress are the most common causes.
+
+## Operational considerations
+
+- **Cost control:** Define usage policies and rate limits with your provider. Hyperion requests can process the full problem statement, so costs scale with exercise size.
+- **Data protection:** Model providers receive exercise content. Obtain consent and align with institutional policies before enabling Hyperion in production.

documentation/docs/admin/intro.md

@@ -2,7 +2,6 @@
 id: intro
 title: Welcome to the Administrator Guide
 sidebar_label: Introduction
-sidebar_position: 1
 ---
 
 # 🔐 Administrator Setup & Security Guide
@@ -13,6 +12,7 @@ This documentation covers:
 
 - Server and production environment setup
 - Security configurations and best practices
+- Hyperion AI-assisted exercise authoring setup
 - Managing SSH access and network routing
 - Monitoring, scaling, and integrating external services
 

documentation/docs/staff/intro.md

@@ -2,18 +2,18 @@
 id: intro
 title: Welcome to the Developer & Staff Guide
 sidebar_label: Introduction
-sidebar_position: 1
 ---
 
 # 🧑‍💻 Developer & Staff Setup Guide
 
 This section provides the technical setup and configuration details needed to develop, maintain, or extend Artemis.
 
-You’ll find information on:
+You'll find information on:
 
 - Setting up a **local development environment**
 - Running the **Artemis server (Spring Boot)** and **client (Angular)**
 - Database and build configuration
 - Integration with version control and CI/CD systems
+- Setting up **local LLM services** for AI-assisted features
 
 Start with the **[Setup Guide](./setup.mdx)** to install and run Artemis on your local machine.